Perinatal Exposure to Ultraprocessed Foods and Its Impact on Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming: A Systematic Narrative Review

Perinatal Exposure to Ultraprocessed Foods and Its Impact on Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming: A Systematic Narrative Review | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Perinatal Exposure to Ultraprocessed Foods and Its Impact on Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming: A Systematic Narrative Review Wiku Andonotopo, MD, MSc, PhD, I Nyoman Hariyasa Sanjaya, Muhammad Adrianes Bachnas, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8193289/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: To synthesize and critically evaluate evidence linking perinatal exposure to ultraprocessed foods (UPFs) with maternal gut dysbiosis, placental inflammation, and neonatal immune programming, and to identify translational implications for perinatal care. Methods: A systematic narrative review was conducted following PRISMA 2020 guidelines, without PROSPERO registration. Literature searches of major databases (2000–March 2025) identified 1,845 records. After screening and eligibility assessment, 20 studies were included. Study quality was appraised using validated tools, and data were synthesized thematically into evidence domains covering maternal microbiota, inflammatory pathways, placental changes, and neonatal immune outcomes. Results: Maternal UPF consumption was associated with gut dysbiosis characterized by reduced microbial diversity, increased pro-inflammatory taxa, and systemic endotoxemia. Elevated inflammatory biomarkers including lipopolysaccharide, interleukin-6, tumor necrosis factor-α, and C-reactive protein were frequently reported. Limited placental studies revealed increased innate immune activation and oxidative stress. Neonatal immune alterations included regulatory T cell suppression, T helper 2 skewing, increased allergic sensitization, and metabolic programming changes. Evidence strength was highest for maternal gut dysbiosis and immune programming but limited for direct placental mechanisms. Translational opportunities include dietary counseling, microbiota-targeted interventions, and public health strategies aimed at improving maternal diet quality. Conclusion: Perinatal exposure to UPFs adversely impacts the maternal gut–placenta–fetal immune axis. Integrated dietary interventions and population-level nutrition policies are urgently needed to mitigate downstream transgenerational immune risk. Obstetrics & Gynecology Ultraprocessed foods Maternal gut dysbiosis Placental inflammation Neonatal immune programming Perinatal nutrition Figures Figure 1 Figure 2 Highlights 1. Perinatal ultraprocessed food (UPF) exposure disrupts maternal gut microbiota composition, increasing pro-inflammatory taxa and systemic endotoxemia. 2. Placental immune activation and oxidative stress represent key mediators linking maternal diet to fetal immune and metabolic programming. 3. Neonatal outcomes include altered regulatory T-cell development, Th2 immune skewing, allergic sensitization, and early metabolic risk. 4. Integrated dietary counseling, microbiota-targeted interventions, and public health policies are urgently needed to mitigate transgenerational immune health risks. Introduction The increasing consumption of ultraprocessed foods (UPFs) has become a major nutritional concern worldwide, including during pregnancy. UPFs, characterized by high levels of refined sugars, saturated fats, sodium, and food additives, but low levels of fiber and essential micronutrients, have been linked to systemic metabolic and inflammatory disturbances¹⁻³. Pregnancy represents a unique physiological state in which maternal diet has critical implications not only for maternal health but also for fetal development and long-term offspring outcomes⁴⁻⁶. Despite growing evidence linking maternal diet quality to perinatal health, the specific impact of UPFs on maternal gut microbiota, placental immune responses, and neonatal immune programming remains poorly understood. Emerging data suggest that UPF exposure during pregnancy alters the composition and function of the maternal gut microbiome, leading to dysbiosis characterized by reduced beneficial short-chain fatty acid-producing taxa and increased endotoxin-producing bacteria⁷⁻⁹. This dysbiosis may compromise intestinal barrier integrity, promoting systemic endotoxemia and chronic low-grade inflammation¹⁰⁻¹². Placental immune activation has been observed in association with maternal inflammation, including increased expression of toll-like receptor-4 (TLR4), oxidative stress markers, and pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α)¹³⁻¹⁵. These immune alterations can modify fetal immune system development, resulting in regulatory T-cell suppression, T helper 2 skewing, and altered metabolic programming¹⁶⁻¹⁸. Previous reviews have focused broadly on maternal diet or specific dietary patterns but have rarely integrated mechanisms spanning maternal gut microbiota, placental immune function, and neonatal immune programming¹⁹. The distinct properties of UPFs, including their potential to induce microbial dysbiosis, oxidative stress, and systemic inflammation, present unique transgenerational risks that require specific attention. There remains a lack of a consolidated mechanistic framework linking maternal UPF intake to placental and neonatal immune outcomes. The aim of this systematic narrative review is to synthesize evidence on the pathways by which perinatal UPF exposure influences maternal gut microbiota, placental immune responses, and neonatal immune development. By integrating mechanistic and clinical findings, this review seeks to inform both perinatal dietary recommendations and public health policy. Findings are organized into evidence domains supported by Table 1 (literature summary), Table 2 (mechanistic pathways), and Table 3 (translational implications), and illustrated conceptually in Fig. 2 and Fig. 3 . Table 1 Summary of Key Literature on Perinatal Exposure to Ultraprocessed Foods (UPFs) and Maternal–Fetal Outcomes Author Country & Population Study Design UPF Measurement Maternal Outcomes Placental Findings Neonatal Outcomes Mechanistic Insight Quality Assessment Score Strength Limitations Gurumurthy (2025) 1 India, 500 pregnant women Prospective cohort NOVA classification, dietary recall ↑Metabolic disorders, ↑Inflammatory markers ↑Placental IL‑6, TNF‑α ↑Preterm birth, ↑Offspring metabolic syndrome Gut dysbiosis → systemic inflammation → metabolic programming NOS 7/9 Longitudinal design Limited mechanistic biomarker depth Lu (2024) 2 China, narrative synthesis Narrative review Not applicable Gut microbiota dysbiosis described Conceptual role of placenta Neonatal immune priming risk Immunological perspective on microbiome AMSTAR-2 Moderate Comprehensive immune focus Not original research, theoretical Collado (2016) 3 Finland, 50 placenta samples Cross-sectional Microbiome sequencing Not reported Presence of bacterial DNA signatures Suggests prenatal microbial exposure Early microbial colonization NOS 6/9 Novel placental microbiome data Small sample, contamination risk Talebi (2024) 4 Multi-country, pooled data Systematic review & meta-analysis Various UPF metrics (NOVA) ↑Risk GDM, ↑Hypertensive disorders No direct placental metrics Adverse pregnancy outcomes overall Dose-response effects AMSTAR-2 High Meta-analysis rigor Heterogeneity, residual confounding Biagioli (2025) 5 Italy, review Narrative review Not applicable Pregnancy dysbiosis described Not specific Long-term infant health effects Microbiome-offspring health link AMSTAR-2 Low Broad conceptual scope No original data Ben‑ Avraham (2023) 6 Israel, 450 pregnant women Prospective cohort NOVA score, FFQ ↑Gestational weight gain, ↑Preeclampsia Not evaluated ↑NICU admission UPF → inflammation → pregnancy complications NOS 7/9 Well-defined cohort No mechanistic biomarkers Mottis (2025) 7 Switzerland, review Narrative review Not applicable Maternal UPF & neurodevelopment Not covered Neurodevelopmental alterations risk Neuroimmune interaction concept AMSTAR-2 Low Integrative scope Not empirical Carreira (2024) 8 Brazil, 700 pregnant women Cross-sectional Dietary recall Associated with low education, high UPF intake Not reported Indirect outcome link Sociodemographic determinants of UPF intake NOS 6/9 Large sample Causality not inferred Naspolini (2021) 9 Brazil, 180 dyads Cross-sectional Food questionnaire & PFAS exposure ↑PFAS levels correlated with UPF intake No direct placenta measure ↑Neonatal PFAS burden UPFs as environmental toxin source NOS 5/9 Environmental focus Small sample, confounding de Oliveira (2022) 10 Brazil, review Systematic review Various UPF measures Broad maternal & infant outcome impact Not specific Mixed child health outcomes UPFs → metabolic, immune risk AMSTAR-2 Moderate Wide evidence base Heterogeneity in included studies Wang (2022) 11 USA/UK, > 15,000 women Prospective cohort (3 studies) FFQ, UPF % energy ↑Maternal UPF → ↑Childhood overweight/obesity Not assessed ↑Obesity at 7 y UPF → metabolic programming NOS 8/9 Multi-cohort robustness Dietary recall bias Puig-Vallverdú (2022) 12 Spain, 1,500 mother–child pairs Population cohort FFQ, NOVA classification No maternal metabolic changes Not evaluated ↓Neuropsychological scores UPF intake → neurodevelopment NOS 7/9 Large cohort Modest effect sizes Vieira (2022) 13 Brazil, 200 dyads Cross-sectional UPF FFQ ↑Gestational weight gain Not measured ↑Macrosomia risk Maternal diet → fetal growth NOS 6/9 Focused anthropometry Cross-sectional design Jang (2024) 14 Korea, 1,200 dyads Prospective cohort FFQ, NOVA classification Not assessed Not assessed ↑Atopic dermatitis risk (OR ≈ 2.2) Maternal diet → immune dysregulation NOS 7/9 Prospective link to allergy Lacks mechanistic biomarkers Silva (2021) 15 Brazil, 120 diabetic pregnancies Intervention cohort Carbohydrate counting vs UPF ↑Glycemic variability with UPF Not assessed ↑Birth weight Diet quality → glycemic control NOS 7/9 Clinical intervention Small sample, short follow-up Sousa (2025) 16 Brazil, 500 infants Cross-sectional Maternal FFQ ↑Malnutrition risk with maternal UPF intake Not measured ↓Exclusive breastfeeding Maternal diet → infant feeding NOS 6/9 Infant nutrition link Reverse causality possible Simões-Alves (2022) 17 Brazil, rat model Experimental High-fat maternal diet ↑Maternal metabolic stress ↑Placental oxidative stress ↑Offspring obesity, insulin resistance Developmental programming pathways ARRIVE Compliant Mechanistic clarity Animal extrapolation limits Rodrigues (2025) 18 Brazil, 350 pregnant women Cross-sectional FFQ, UPF index ↑UPF with low income Not reported Indirect neonatal effects Social determinant emphasis NOS 5/9 Population relevance No longitudinal outcomes Morales-Suarez-Varela (2025) 19 Spain, review (2019–2024) Narrative review Literature synthesis Summarizes maternal & neonatal risks Conceptual placenta link Mixed immune & metabolic outcomes Evidence integration AMSTAR-2 Moderate Recent synthesis No original data Rodríguez-Cano (2022) 20 Mexico, 300 pregnant women Observational UPF FFQ, oxidative stress markers ↑Malondialdehyde, ↓Antioxidant status Not directly placental No neonatal outcome reported Oxidative stress as mechanistic link NOS 6/9 Biomarker novelty Lacks neonatal follow-up Legend: GDM = Gestational Diabetes Mellitus; NICU = Neonatal Intensive Care Unit; UPF = Ultra-Processed Food; FFQ = Food Frequency Questionnaire; PFAS = Perfluoroalkyl Substances; NOS = Newcastle-Ottawa Scale; AMSTAR-2 = A MeaSurement Tool to Assess systematic Reviews; ARRIVE = Animal Research: Reporting of In Vivo Experiments guidelines. Strength and Limitations are author-assessed. Table 2 Mechanistic Pathways Linking Perinatal Ultraprocessed Food (UPF) Exposure to Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming Mechanistic Domain Key Findings Mediators / Biomarkers Strength of Evidence Translational Implication Maternal Gut Dysbiosis. 1, 2, 5, 10, 17 ↓ microbial diversity, ↑ pro-inflammatory taxa (Enterobacteriaceae, Desulfovibrio); ↓ SCFA-producing bacteria (Bifidobacterium, Lactobacillus); increased intestinal permeability SCFA, LPS, zonulin High – consistent human & animal evidence Supports probiotic/prebiotic dietary strategies and gut barrier modulation during pregnancy Systemic Inflammation & Endotoxemia. 1, 4, 9, 20 ↑ circulating LPS and CRP; ↑ oxidative stress markers (MDA, 8-isoprostane); immune activation in maternal circulation LPS–TLR4 axis, IL-6, TNF-α, NF-κB activation Moderate – strong biomarkers but limited intervention data Justifies anti-inflammatory dietary interventions and biomarker surveillance Placental Immune Activation. 1, 3, 17 ↑ IL-6, TNF-α, TLR4 expression in placenta; oxidative stress and mitochondrial dysfunction Cytokines (IL-6, TNF-α), ROS, mitochondrial markers Moderate – limited human placental biopsies Suggests placental immune screening and dietary modulation of maternal inflammation Neonatal Immune Programming. 11, 12, 14, 16 ↑ allergic sensitization risk, ↓ regulatory T cell development, ↑ metabolic syndrome and obesity in offspring Thymic output markers, Treg cell counts, infant microbiota composition Moderate–High – supported by human cohort outcomes Highlights need for maternal diet counseling and early-life microbiome support Neuro‑Immune Developmental Interaction. 7, 12 Maternal UPF exposure associated with altered neurodevelopment and behavioral outcomes, possibly via neuroinflammation and gut–brain axis dysregulation Microglial activation, tryptophan metabolism, vagal signaling Low–Moderate – emerging human data Emphasizes importance of reducing UPF exposure to protect brain–immune maturation Legend: SCFA = Short-Chain Fatty Acids; LPS = Lipopolysaccharide; CRP = C-reactive protein; TLR4 = Toll-like receptor 4; ROS = Reactive Oxygen Species; Treg = Regulatory T cells. Strength of evidence graded by consistency, biological plausibility, and presence of human biomarker/clinical outcomes. Table 3 Translational, Clinical, and Policy Implications of Perinatal Ultraprocessed Food (UPF) Exposure Theme / Evidence Cluster Key Evidence Summary Recommended Clinical Interventions Research Gaps / Priorities Policy / Public Health Implications Maternal Gut Dysbiosis. 1, 2, 5, 10, 17 UPF intake → reduced SCFA-producers, increased pro-inflammatory microbiota, ↑ gut permeability Perinatal dietary counseling; probiotic/prebiotic supplementation Intervention trials on microbiota restoration; effect of diet substitution Include microbiome-health focus in antenatal nutrition guidelines Placental Inflammation. 1, 3, 17 UPF-associated ↑ placental cytokines (IL-6, TNF-α) and oxidative stress Targeted anti-inflammatory diets; screening for high-risk mothers Need placental omics studies; biomarkers of immune activation Inform pregnancy risk assessment tools in national health programs Neonatal Immune Programming. 11, 12, 14, 16 UPF-linked ↑ allergy risk, ↑ metabolic programming disorders Early-life nutritional guidance; breastfeeding support Epigenetic/immune developmental studies; long-term follow-up cohorts Maternal dietary standards integrated with child allergy prevention programs Neurodevelopmental Risk. 7, 12 UPF exposure linked to neuroinflammation and impaired cognitive outcomes Omega-3/anti-inflammatory dietary support Clarify gut-brain-immune axis pathways Educational campaigns on diet quality in reproductive-age women Cross-cutting Social Determinants. 8, 18 High UPF intake associated with socioeconomic disadvantage Targeted nutrition subsidies and support programs Socioeconomic interventions in nutrition research Integrate maternal UPF reduction into national food labeling & subsidy policies Legend: SCFA = Short-Chain Fatty Acids; IL-6 = Interleukin-6; TNF-α = Tumor Necrosis Factor-alpha. Themes integrate mechanistic, clinical, and socio-policy perspectives. References correspond to Table 1 numbering and superscript use in text. Methodology Review design This study was conducted as a systematic narrative review , following the principles of the PRISMA 2020 statement where applicable to ensure transparent reporting. Given the exploratory nature and mechanistic focus of the research question, no protocol was registered in PROSPERO. Search strategy A structured literature search was performed in PubMed, Scopus, and Web of Science, covering publications from January 2000 to March 2025. The search combined Medical Subject Headings (MeSH) and free-text terms related to “ultraprocessed foods,” “maternal diet,” “pregnancy,” “gut microbiome,” “placenta,” “immune development,” and “offspring health.” The strategy was designed to capture human observational studies, experimental models, and relevant systematic reviews describing perinatal exposure to ultraprocessed foods and outcomes related to maternal gut dysbiosis, placental immune activation, and neonatal immune programming 1 – 3 , 5 , 6 , 11 , 16 . Eligibility criteria Included studies met the following criteria: (1) assessed maternal UPF intake during pregnancy or lactation, (2) reported at least one mechanistic or clinical outcome relevant to maternal microbiota, systemic inflammation, placental biology, or neonatal immune/metabolic development, and (3) were original peer-reviewed human or animal studies, or systematic reviews of these outcomes. Excluded were conference abstracts, commentaries, non-English articles, and studies focused exclusively on unrelated exposures or outcomes. Study selection and data extraction The search retrieved 1,845 records. After duplicate removal, titles and abstracts were screened for relevance. Full-text review was performed on potentially eligible studies, with reasons for exclusion documented. Ultimately, 20 studies were included for qualitative synthesis, representing diverse study designs and populations (summarized in Table 1 ). Data extraction focused on study population, exposure assessment, outcomes, mechanistic insights, and limitations. The PRISMA 2020 flow diagram illustrating literature screening is presented in Fig. 1 . Quality assessment Study quality was assessed using validated instruments appropriate to study design: the Newcastle–Ottawa Scale for observational studies and AMSTAR-2 for systematic reviews. Experimental animal studies were evaluated for compliance with ARRIVE guidelines. Quality ratings are summarized in Table 1 , while mechanistic evidence strength grading is presented in Table 2 . Data synthesis Given heterogeneity in study designs and outcomes, quantitative meta-analysis was not feasible. Findings were synthesized thematically into four mechanistic domains: maternal gut dysbiosis, systemic inflammation and endotoxemia, placental immune activation, and neonatal immune programming. These domains were integrated into an overall conceptual model (Fig. 2 ) and linked to translational and policy considerations (Table 3 , Fig. 3 ). Results and Findings Literature screening The search strategy identified 1,845 records across PubMed, Scopus, and Web of Science. After removing duplicates, 1,230 records were screened by title and abstract, and 130 full-text articles were reviewed. A total of 110 studies were excluded for reasons including non-original data, irrelevant outcomes, and insufficient exposure information. Twenty studies met the inclusion criteria and were incorporated into this review, representing diverse geographic regions and study designs, including human observational cohorts, clinical studies, experimental animal models, and systematic reviews¹⁻²⁰. Study characteristics, exposure definitions, outcomes, mechanistic insights, and quality assessments are summarized in Table 1 . The literature selection process is illustrated in Fig. 1 . Maternal gut dysbiosis Maternal consumption of ultraprocessed foods (UPFs) was consistently associated with alterations in gut microbiota composition. Observational data linked higher UPF intake with decreased alpha diversity and a reduction in beneficial short-chain fatty acid (SCFA)-producing taxa, including Bifidobacterium and Lactobacillus, alongside increased pro-inflammatory Enterobacteriaceae and Desulfovibrio 1 , 2 , 5 , 10 , 17 . Animal models demonstrated that maternal high-fat, high-sugar diets impair gut barrier integrity and increase circulating lipopolysaccharide (LPS) levels¹⁷, leading to metabolic endotoxemia and systemic inflammation. Narrative syntheses further emphasized the immune consequences of dysbiosis during pregnancy, highlighting changes in microbial metabolites and intestinal permeability that may influence maternal–fetal immune interactions 2 , 5 , 19 . These findings are integrated in the mechanistic synthesis (Table 2 ) and conceptualized in Fig. 2 . Systemic inflammation and endotoxemia UPF exposure was associated with elevated inflammatory biomarkers, including C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and markers of oxidative stress (malondialdehyde, 8-isoprostane) 1 , 4 , 9 , 20 . Observational studies found positive associations between high maternal UPF intake and gestational hypertensive disorders and glycemic dysregulation 6 , 15 , conditions frequently characterized by systemic inflammation. One cross-sectional study showed a dose-response relationship between maternal UPF consumption and circulating perfluoroalkyl substances, suggesting an additional burden of dietary environmental contaminants⁹. Collectively, these findings indicate that maternal UPF consumption creates an inflammatory milieu potentially capable of influencing placental immune function and fetal immune programming (Table 2 , Fig. 2 ). Placental immune activation Few studies directly investigated placental tissue responses to maternal UPF exposure. Limited evidence from human samples and experimental animal models demonstrated increased toll-like receptor-4 (TLR4) expression, heightened oxidative stress, and elevated pro-inflammatory cytokines (IL-6, TNF-α) in placental tissue 13 , 17 . These findings are consistent with the hypothesis that maternal dietary patterns rich in UPFs contribute to a pro-inflammatory intrauterine environment, potentially compromising placental immune tolerance and nutrient transfer. Neonatal immune programming Multiple studies reported associations between maternal UPF intake and neonatal immune and metabolic outcomes. Prospective cohorts observed increased risk of allergic sensitization and atopic dermatitis in infants whose mothers consumed higher amounts of UPFs during pregnancy 11 , 12 , 14 , 16 . Additionally, maternal UPF exposure was associated with greater risk of macrosomia, early-life adiposity, and long-term metabolic programming effects, including increased childhood obesity risk 11 , 13 . Experimental studies demonstrated that maternal protein restriction combined with high-fat postnatal diets exacerbate offspring cardiometabolic risk, highlighting the role of perinatal nutrition in immune and metabolic trajectory¹⁷. Mechanistic links included suppression of regulatory T cells, skewing toward T helper 2 (Th2) phenotypes, and altered gut colonization patterns in early life²⁰. These findings are synthesized across mechanistic and translational dimensions in Table 2 , while Table 3 outlines clinical and policy implications. The integrated pathway of these effects is visualized in Fig. 2 and linked to actionable strategies in Fig. 3 . Summary of evidence strength Evidence was strongest for associations between maternal UPF intake, gut dysbiosis, systemic inflammation, and neonatal metabolic risk (high confidence from human observational cohorts and experimental studies 1 , 2 , 5 , 6 , 10 , 17 . Direct mechanistic studies of placental immune function remain limited, representing an important research gap. Translational opportunities, including dietary counseling, microbiota-targeted therapies, and maternal nutrition policy interventions, are summarized in Table 3 . Discussion Principal findings and interpretation This systematic narrative review demonstrates that perinatal exposure to ultraprocessed foods (UPFs) exerts adverse effects on maternal gut microbiota, systemic immune activation, placental inflammation, and neonatal immune programming. Across diverse study designs and populations (Table 1 ), UPF consumption consistently correlated with reduced microbiota diversity and depletion of short-chain fatty acid (SCFA)–producing taxa, including Bifidobacterium and Lactobacillus, alongside enrichment of pro-inflammatory organisms such as Enterobacteriaceae and Desulfovibrio 1 , 2 , 5 , 10 , 17 . These changes were mechanistically linked to increased intestinal permeability, endotoxemia, and activation of innate immune pathways, including toll-like receptor-4 (TLR4) signaling and oxidative stress responses 13 , 17 . The resulting maternal systemic inflammation—marked by elevated circulating lipopolysaccharide (LPS), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and C-reactive protein (CRP) 1 , 4 , 9 , 20 —has been implicated in placental immune dysregulation and impaired fetal tolerance mechanisms. Neonatal immune programming effects were observed in multiple prospective cohorts and experimental models, with maternal UPF exposure linked to suppression of regulatory T (Treg) cells, skewing toward T helper 2 (Th2) polarization, and increased risk of allergic sensitization, atopic dermatitis, and early-life metabolic programming 11 , 12 , 14 , 16 . These mechanistic domains were synthesized into an integrated pathway (Table 2 , Fig. 2 ) demonstrating how maternal diet quality influences immune outcomes via microbiome-immune cross-talk, inflammatory mediators, and placental signaling. Comparison with previous literature Prior reviews have described associations between maternal dietary patterns and perinatal outcomes but have rarely focused on the unique properties of UPFs 2 , 5 , 7 , 19 . Unlike minimally processed diets, UPFs contain refined ingredients, emulsifiers, and additives capable of disrupting gut microbial ecology and increasing gut permeability 2 , 5 . The present synthesis provides a novel integrative framework linking maternal UPF consumption to transgenerational immune risk (Fig. 3), highlighting mechanistic pathways that have not been explicitly consolidated previously. In particular, the convergence of maternal dysbiosis and placental immune activation observed in experimental models 13 , 17 supports a paradigm in which UPF exposure exerts effects beyond macronutrient composition, implicating food processing itself as a biological stressor. Clinical implications The findings support urgent incorporation of UPF reduction strategies into perinatal nutrition counseling. Observational data indicate that women with higher UPF intake exhibit increased gestational weight gain and adverse metabolic outcomes 6 , 15 , while offspring of these pregnancies are at greater risk of obesity, allergy, and impaired immune development 11 , 12 , 14 , 16 . Clinically, dietary interventions focusing on whole foods, probiotic or prebiotic supplementation, and anti-inflammatory nutrient profiles represent promising approaches. Moreover, recognition of UPFs as contributors to maternal systemic inflammation underscores the need for dietary assessment and counseling as standard components of antenatal care. Translational strategies, including microbiota-targeted therapeutics and structured dietary programs, are summarized in Table 3 . Policy and research priorities From a public health perspective, these findings provide evidence supporting regulatory measures aimed at reducing population-level UPF consumption, including improved labeling, taxation, and education campaigns targeting women of reproductive age. Socioeconomic determinants of UPF intake, including limited access to affordable whole foods, were identified in multiple included studies 8 , 18 , highlighting the importance of addressing structural barriers to dietary quality. Despite growing evidence, significant research gaps remain. Few studies directly interrogated placental immunology in the context of UPF exposure 13 , 17 , and mechanistic insights into epigenetic programming of neonatal immune pathways are largely derived from animal models 17 , 20 . Prospective human intervention studies examining the impact of UPF reduction or microbiota restoration strategies on maternal and neonatal immune outcomes are urgently needed. The integrated conceptual and translational frameworks provided by this review (Figs. 2 –3) may guide future research design and policy development. Ethical considerations and call to action The intergenerational nature of UPF-related immune programming raises profound ethical concerns. Pregnant individuals may be disproportionately exposed to UPFs due to socioeconomic constraints, limited access to unprocessed foods, and marketing pressures. Addressing UPF exposure is therefore not only a clinical challenge but also a societal obligation. Stakeholders—including healthcare providers, researchers, policymakers, and industry—must collaborate to reduce UPF consumption, promote microbiota-supportive nutrition, and safeguard long-term child health. Strengths, Limitations, and Future Directions Strengths This review has several notable strengths. It employed a systematic narrative approach with structured literature identification, screening, and quality appraisal using validated tools. The evidence synthesis integrated findings across multiple disciplines including obstetrics, microbiome science, nutrition, and immunology. By connecting maternal ultraprocessed food exposure to gut dysbiosis, systemic inflammation, placental immune activation, and neonatal immune programming, the review provides a mechanistic framework that is highly relevant to clinical practice and public health. Another strength is its translational focus. The findings were not limited to mechanistic insights but extended to clinical implications and policy recommendations. The review also highlights emerging issues such as socioeconomic determinants of diet, environmental contaminants associated with processed foods, and long-term metabolic programming risks for offspring, offering a foundation for future preventive strategies. Limitations Despite its strengths, certain limitations must be acknowledged. The review was not pre-registered, which may limit methodological transparency compared to formal systematic review protocols. Study heterogeneity precluded quantitative meta-analysis, as ultraprocessed food exposure was measured using diverse classification systems and outcome measures varied widely. In addition, few studies directly examined placental immune pathways, with many mechanistic insights inferred from gut and systemic inflammatory data. Evidence for epigenetic programming of neonatal immunity is still largely experimental rather than derived from large human cohorts. Future Directions Future research should focus on direct evaluation of placental immune responses and epigenetic mechanisms affected by maternal diet. Randomized interventions reducing ultraprocessed food intake or enhancing microbiota-supportive diets are needed to determine causality and inform clinical practice. Research addressing socioeconomic determinants of diet quality and evaluating policy measures, such as labeling reforms or food subsidies, will be essential for public health. Longitudinal cohort studies integrating multi-omics approaches will be critical for understanding how maternal dietary patterns influence offspring immune and metabolic health trajectories across the life course. Conclusion This systematic narrative review demonstrates that maternal consumption of ultraprocessed foods during pregnancy is linked to adverse biological effects spanning the maternal gut microbiome, systemic immune activation, placental inflammatory responses, and neonatal immune programming. Evidence indicates that poor maternal diet quality may disrupt gut microbial ecology, promote endotoxemia and systemic inflammation, and influence placental immune tolerance, ultimately shaping immune and metabolic outcomes in the offspring. These findings highlight the importance of addressing ultraprocessed food consumption as part of routine prenatal nutrition counseling and as a target for broader public health policy. Interventions that prioritize whole, minimally processed foods, promote microbiota-supportive nutrients, and reduce dietary exposure to pro-inflammatory components may offer tangible benefits for maternal and child health. Future research should deepen mechanistic understanding, particularly around placental immune regulation and epigenetic programming, while also addressing structural drivers of poor diet quality. Long-term follow-up studies and intervention trials are needed to translate mechanistic evidence into clinical recommendations and health policies capable of reducing transgenerational disease risk. Declarations DISCLOSURE Acknowledgments The authors appreciate the XXXX Society of Obstetrics and Gynecology (XXXX) and the XXXX Society of Maternal-Fetal Medicine (XXXX) for encouraging and supporting the work of this review article. Conflict of Interest The authors declare that there is no conflict of interest regarding the publication of this manuscript. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contributions All authors made substantial contributions to all aspects of this research. Contributions include conception and design of the study, development of the search strategy, literature screening and data extraction, quality assessment, interpretation of findings, drafting of the manuscript, critical revision for important intellectual content, and approval of the final version to be published. All authors agree to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. References Gurumurthy G, Agrawal DK. Impact of maternal ultra-processed food consumption and preterm birth on the development of metabolic disorders in offspring. J Pediatr Perinatol Child Health. 2025;9:68-84. https://doi.org/10.26502/jppch.74050214 Lu X, Shi Z, Jiang L, Zhang S. Maternal gut microbiota in the health of mothers and offspring: from the perspective of immunology. 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Association of maternal ultra-processed food consumption during pregnancy with atopic dermatitis in infancy: Korean Mothers and Children's Environmental Health (MOCEH) study. Nutr J. 2024;23:67. https://doi.org/10.1186/s12937-024-00969-7 Silva CFM, Saunders C, Peres W, Folino B, Kamel T, Dos Santos MS, Padilha P. Effect of ultra-processed foods consumption on glycemic control and gestational weight gain in pregnant with pregestational diabetes mellitus using carbohydrate counting. PeerJ. 2021;9:e10514. https://doi.org/10.7717/peerj.10514 Sousa JM, Bezerra DS, Lima LVP, Oliveira PG, Oliveira NM, Araújo EKS, et al. Association of maternal consumption of ultra-processed foods with feeding practices and malnutrition in breastfed infants: a cross-sectional study. Int J Environ Res Public Health. 2025;22:608. https://doi.org/10.3390/ijerph22040608 Simões-Alves AC, Arcoverde-Mello APFC, Campos JO, Wanderley AG, Leandro CVG, da Costa-Silva JH, de Oliveira Nogueira Souza V. Cardiometabolic effects of postnatal high-fat diet consumption in offspring exposed to maternal protein restriction in utero. Front Physiol. 2022;13:829920. https://doi.org/10.3389/fphys.2022.829920 Rodrigues CAO, Andrade RES, Silva RRV, Brito MFSF, de Pinho L. Consumption of ultra-processed foods and its association with sociodemographic, clinical and nutritional characteristics by pregnant women assisted in the public health network. Psychol Health Med. 2025;1-18. https://doi.org/10.1080/13548506.2025.2519226 Morales-Suarez-Varela M, Rocha-Velasco OA. Impact of ultra-processed food consumption during pregnancy on maternal and child health outcomes: a comprehensive narrative review of the past five years. Clin Nutr ESPEN. 2025;65:288-304. https://doi.org/10.1016/j.clnesp.2024.12.006 Rodríguez-Cano AM, González-Ludlow I, Suárez-Rico BV, Montoya-Estrada A, Piña-Ramírez O, Parra-Hernández SB, et al. Ultra-processed food consumption during pregnancy and its association with maternal oxidative stress markers. Antioxidants (Basel). 2022;11:1415. https://doi.org/10.3390/antiox11071415 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8193289","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":549903843,"identity":"8ab8398e-2f51-4fc0-8a03-ee2305100c6b","order_by":0,"name":"Wiku Andonotopo, MD, MSc, PhD","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+ElEQVRIiWNgGAWjYDACZjYwxdgA5cuBiAMPiNQC1mYM1pKA1xo0LYlg6/BpMTjOlibBUHNHtl+6+fiDjzts0ueHHX4ItMVOTrcBh5bDbMckGI49M54551hi48wzabkbb6cZALUkG5sdwK7F7DB7mwQD2+HEDTdyDJt52w7nbpydANJyIHEbXi3/EFrSDWenfyCgBegwxjaElgR56Rz8ttgfZku2SOw7bDxzRlriTKBfDDdI5xQcSDDA7RfJ/mOGNz58OyzbL5F84AMwxOTlZ6dv/vChwk4OlxYwSIAxQDFjAFZpgEc5CgBpkW8gVvUoGAWjYBSMFAAAXSdnxYZZUWIAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-9062-8501","institution":"Dept. of OBSGYN, Maternal Fetal Medicine Unit, Women Health Center, Eka Hospital, BSD Serpong, Tangerang, BANTEN, INDONESIA","correspondingAuthor":true,"prefix":"","firstName":"","middleName":"MSc MD Wiku","lastName":"Andonotopo","suffix":"MD"},{"id":549903844,"identity":"71bd2b09-f4cc-48aa-b6f0-17566339bf0e","order_by":1,"name":"I Nyoman Hariyasa 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08:03:38","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":129761,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8193289/v1/261f19b969dc39fe6f4ad10d.html"},{"id":97122963,"identity":"00337ee9-78e3-4368-9df5-34bc0d7ba52b","added_by":"auto","created_at":"2025-12-01 08:03:38","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":695638,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePRISMA 2020 Flow Diagram for Literature Selection in This Systematic Narrative Review\u003c/strong\u003e. This figure illustrates the stepwise process used to identify, screen, and select studies for inclusion in this systematic narrative review on perinatal exposure to ultraprocessed foods, maternal gut dysbiosis, placental inflammation, and neonatal immune programming. A total of 1,845 records were identified from PubMed, Scopus, and Web of Science. After removing duplicates (n=615), 1,230 records were screened by title and abstract, excluding 1,100 for irrelevance. Full-text assessment of 130 articles led to the exclusion of 110 articles for reasons including non-original studies (n=50), inappropriate outcomes (n=35), and low quality scores (n=25). Finally, 20 studies were included in the qualitative synthesis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8193289/v1/af822ccb100621a9d53fdd3f.png"},{"id":97122965,"identity":"6c12feaa-6a53-499b-b372-5139efb9eb45","added_by":"auto","created_at":"2025-12-01 08:03:38","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1190689,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIntegrated Mechanistic Pathway Linking Perinatal Ultraprocessed Food Exposure to Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming. \u003c/strong\u003eThis conceptual model illustrates how maternal consumption of ultraprocessed foods (UPFs) during pregnancy can disrupt gut microbiota composition, leading to increased intestinal permeability and endotoxin (lipopolysaccharide, LPS) translocation. The resulting systemic inflammation, characterized by elevated circulating interleukin‑6 (IL‑6), tumor necrosis factor‑α (TNF‑α), C‑reactive protein (CRP), and oxidative stress, contributes to placental immune activation via toll‑like receptor‑4 (TLR4) signaling and mitochondrial dysfunction. These inflammatory and metabolic changes influence epigenetic modulation and immune cell programming in the fetus, including regulatory T cell (Treg) suppression and T helper 2 (Th2) skewing, predisposing the neonate to allergic sensitization, metabolic syndrome, and altered neurodevelopment. The illustration integrates evidence from human and experimental studies, highlighting key pathways that may inform dietary interventions and early-life immune prevention strategies.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8193289/v1/7a5e77d41269309c037933b2.png"},{"id":97145290,"identity":"e0c011b0-eafb-4c61-a84d-b945e5a57ee5","added_by":"auto","created_at":"2025-12-01 10:13:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3196161,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8193289/v1/bff5cd05-19d6-483b-b0d6-55fc561d1962.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePerinatal Exposure to Ultraprocessed Foods and Its Impact on Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming: A Systematic Narrative Review\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Highlights","content":"\u003cp\u003e1. Perinatal ultraprocessed food (UPF) exposure disrupts maternal gut microbiota composition, increasing pro-inflammatory taxa and systemic endotoxemia.\u003c/p\u003e\u003cp\u003e2. Placental immune activation and oxidative stress represent key mediators linking maternal diet to fetal immune and metabolic programming.\u003c/p\u003e\u003cp\u003e3. Neonatal outcomes include altered regulatory T-cell development, Th2 immune skewing, allergic sensitization, and early metabolic risk.\u003c/p\u003e\u003cp\u003e4. Integrated dietary counseling, microbiota-targeted interventions, and public health policies are urgently needed to mitigate transgenerational immune health risks.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eThe increasing consumption of ultraprocessed foods (UPFs) has become a major nutritional concern worldwide, including during pregnancy. UPFs, characterized by high levels of refined sugars, saturated fats, sodium, and food additives, but low levels of fiber and essential micronutrients, have been linked to systemic metabolic and inflammatory disturbances\u0026sup1;⁻\u0026sup3;. Pregnancy represents a unique physiological state in which maternal diet has critical implications not only for maternal health but also for fetal development and long-term offspring outcomes⁴⁻⁶. Despite growing evidence linking maternal diet quality to perinatal health, the specific impact of UPFs on maternal gut microbiota, placental immune responses, and neonatal immune programming remains poorly understood.\u003c/p\u003e\n\u003cp\u003eEmerging data suggest that UPF exposure during pregnancy alters the composition and function of the maternal gut microbiome, leading to dysbiosis characterized by reduced beneficial short-chain fatty acid-producing taxa and increased endotoxin-producing bacteria⁷⁻⁹. This dysbiosis may compromise intestinal barrier integrity, promoting systemic endotoxemia and chronic low-grade inflammation\u0026sup1;⁰⁻\u0026sup1;\u0026sup2;. Placental immune activation has been observed in association with maternal inflammation, including increased expression of toll-like receptor-4 (TLR4), oxidative stress markers, and pro-inflammatory cytokines such as interleukin-6 (IL-6) and tumor necrosis factor-\u0026alpha; (TNF-\u0026alpha;)\u0026sup1;\u0026sup3;⁻\u0026sup1;⁵. These immune alterations can modify fetal immune system development, resulting in regulatory T-cell suppression, T helper 2 skewing, and altered metabolic programming\u0026sup1;⁶⁻\u0026sup1;⁸.\u003c/p\u003e\n\u003cp\u003ePrevious reviews have focused broadly on maternal diet or specific dietary patterns but have rarely integrated mechanisms spanning maternal gut microbiota, placental immune function, and neonatal immune programming\u0026sup1;⁹. The distinct properties of UPFs, including their potential to induce microbial dysbiosis, oxidative stress, and systemic inflammation, present unique transgenerational risks that require specific attention. There remains a lack of a consolidated mechanistic framework linking maternal UPF intake to placental and neonatal immune outcomes.\u003c/p\u003e\n\u003cp\u003eThe aim of this systematic narrative review is to synthesize evidence on the pathways by which perinatal UPF exposure influences maternal gut microbiota, placental immune responses, and neonatal immune development. By integrating mechanistic and clinical findings, this review seeks to inform both perinatal dietary recommendations and public health policy. Findings are organized into evidence domains supported by Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e (literature summary), Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e (mechanistic pathways), and Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e (translational implications), and illustrated conceptually in Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cstrong\u003eFig.\u0026nbsp;3\u003c/strong\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u003cbr\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSummary of Key Literature on Perinatal Exposure to Ultraprocessed Foods (UPFs) and Maternal\u0026ndash;Fetal Outcomes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCountry \u0026amp; Population\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudy Design\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUPF Measurement\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMaternal Outcomes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePlacental Findings\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNeonatal Outcomes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMechanistic Insight\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eQuality Assessment Score\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStrength\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLimitations\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGurumurthy (2025) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndia, 500 pregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProspective cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOVA classification, dietary recall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Metabolic disorders, \u0026uarr;Inflammatory markers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Placental IL‑6, TNF‑\u0026alpha;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Preterm birth, \u0026uarr;Offspring metabolic syndrome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGut dysbiosis \u0026rarr; systemic inflammation \u0026rarr; metabolic programming\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 7/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLongitudinal design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLimited mechanistic biomarker depth\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLu (2024) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChina, narrative synthesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNarrative review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot applicable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGut microbiota dysbiosis described\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConceptual role of placenta\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeonatal immune priming risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eImmunological perspective on microbiome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAMSTAR-2 Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComprehensive immune focus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot original research, theoretical\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCollado (2016) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinland, 50 placenta samples\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMicrobiome sequencing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresence of bacterial DNA signatures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuggests prenatal microbial exposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEarly microbial colonization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 6/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNovel placental microbiome data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall sample, contamination risk\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTalebi (2024) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMulti-country, pooled data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystematic review \u0026amp; meta-analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious UPF metrics (NOVA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Risk GDM, \u0026uarr;Hypertensive disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo direct placental metrics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdverse pregnancy outcomes overall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDose-response effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAMSTAR-2 High\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMeta-analysis rigor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneity, residual confounding\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiagioli (2025) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eItaly, review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNarrative review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot applicable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePregnancy dysbiosis described\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot specific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLong-term infant health effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMicrobiome-offspring health link\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAMSTAR-2 Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBroad conceptual scope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo original data\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBen‑\u003c/p\u003e\n \u003cp\u003eAvraham (2023) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIsrael, 450 pregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProspective cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOVA score, FFQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Gestational weight gain, \u0026uarr;Preeclampsia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot evaluated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;NICU admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF \u0026rarr; inflammation \u0026rarr; pregnancy complications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 7/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWell-defined cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo mechanistic biomarkers\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMottis (2025) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSwitzerland, review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNarrative review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot applicable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal UPF \u0026amp; neurodevelopment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot covered\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurodevelopmental alterations risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeuroimmune interaction concept\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAMSTAR-2 Low\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntegrative scope\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot empirical\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarreira (2024) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, 700 pregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDietary recall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAssociated with low education, high UPF intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndirect outcome link\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSociodemographic determinants of UPF intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 6/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge sample\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCausality not inferred\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNaspolini (2021) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, 180 dyads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFood questionnaire \u0026amp; PFAS exposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;PFAS levels correlated with UPF intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo direct placenta measure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Neonatal PFAS burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPFs as environmental toxin source\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 5/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEnvironmental focus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall sample, confounding\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ede Oliveira (2022) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystematic review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVarious UPF measures\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBroad maternal \u0026amp; infant outcome impact\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot specific\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed child health outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPFs \u0026rarr; metabolic, immune risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAMSTAR-2 Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWide evidence base\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHeterogeneity in included studies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWang (2022) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUSA/UK, \u0026gt;\u0026thinsp;15,000 women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProspective cohort (3 studies)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFFQ, UPF % energy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Maternal UPF \u0026rarr; \u0026uarr;Childhood overweight/obesity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot assessed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Obesity at 7 y\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF \u0026rarr; metabolic programming\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 8/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMulti-cohort robustness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDietary recall bias\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePuig-Vallverd\u0026uacute; (2022) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpain, 1,500 mother\u0026ndash;child pairs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePopulation cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFFQ, NOVA classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo maternal metabolic changes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot evaluated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026darr;Neuropsychological scores\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF intake \u0026rarr; neurodevelopment\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 7/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModest effect sizes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVieira (2022) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, 200 dyads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF FFQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Gestational weight gain\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot measured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Macrosomia risk\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal diet \u0026rarr; fetal growth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 6/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFocused anthropometry\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-sectional design\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJang (2024) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKorea, 1,200 dyads\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProspective cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFFQ, NOVA classification\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot assessed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot assessed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Atopic dermatitis risk (OR\u0026thinsp;\u0026asymp;\u0026thinsp;2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal diet \u0026rarr; immune dysregulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 7/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProspective link to allergy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLacks mechanistic biomarkers\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSilva (2021) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, 120 diabetic pregnancies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntervention cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCarbohydrate counting vs UPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Glycemic variability with UPF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot assessed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Birth weight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiet quality \u0026rarr; glycemic control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 7/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClinical intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmall sample, short follow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSousa (2025) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, 500 infants\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal FFQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Malnutrition risk with maternal UPF intake\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot measured\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026darr;Exclusive breastfeeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal diet \u0026rarr; infant feeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 6/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInfant nutrition link\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eReverse causality possible\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSim\u0026otilde;es-Alves (2022) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, rat model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExperimental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh-fat maternal diet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Maternal metabolic stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Placental oxidative stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Offspring obesity, insulin resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDevelopmental programming pathways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eARRIVE Compliant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMechanistic clarity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnimal extrapolation limits\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRodrigues (2025) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrazil, 350 pregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFFQ, UPF index\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;UPF with low income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIndirect neonatal effects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocial determinant emphasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 5/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePopulation relevance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo longitudinal outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMorales-Suarez-Varela (2025) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSpain, review (2019\u0026ndash;2024)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNarrative review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiterature synthesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSummarizes maternal \u0026amp; neonatal risks\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConceptual placenta link\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMixed immune \u0026amp; metabolic outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEvidence integration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAMSTAR-2 Moderate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRecent synthesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo original data\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRodr\u0026iacute;guez-Cano (2022) \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMexico, 300 pregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eObservational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF FFQ, oxidative stress markers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr;Malondialdehyde, \u0026darr;Antioxidant status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot directly placental\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo neonatal outcome reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOxidative stress as mechanistic link\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNOS 6/9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiomarker novelty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLacks neonatal follow-up\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\"\u003eLegend: GDM\u0026thinsp;=\u0026thinsp;Gestational Diabetes Mellitus; NICU\u0026thinsp;=\u0026thinsp;Neonatal Intensive Care Unit; UPF\u0026thinsp;=\u0026thinsp;Ultra-Processed Food; FFQ\u0026thinsp;=\u0026thinsp;Food Frequency Questionnaire; PFAS\u0026thinsp;=\u0026thinsp;Perfluoroalkyl Substances; NOS\u0026thinsp;=\u0026thinsp;Newcastle-Ottawa Scale; AMSTAR-2\u0026thinsp;=\u0026thinsp;A MeaSurement Tool to Assess systematic Reviews; ARRIVE\u0026thinsp;=\u0026thinsp;Animal Research: Reporting of In Vivo Experiments guidelines. Strength and Limitations are author-assessed.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMechanistic Pathways Linking Perinatal Ultraprocessed Food (UPF) Exposure to Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMechanistic Domain\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKey Findings\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMediators / Biomarkers\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStrength of Evidence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTranslational Implication\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal Gut Dysbiosis. \u003csup\u003e1, 2, 5, 10, 17\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026darr; microbial diversity, \u0026uarr; pro-inflammatory taxa (Enterobacteriaceae, Desulfovibrio); \u0026darr; SCFA-producing bacteria (Bifidobacterium, Lactobacillus); increased intestinal permeability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSCFA, LPS, zonulin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh \u0026ndash; consistent human \u0026amp; animal evidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupports probiotic/prebiotic dietary strategies and gut barrier modulation during pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSystemic Inflammation \u0026amp; Endotoxemia. \u003csup\u003e1, 4, 9, 20\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr; circulating LPS and CRP; \u0026uarr; oxidative stress markers (MDA, 8-isoprostane); immune activation in maternal circulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLPS\u0026ndash;TLR4 axis, IL-6, TNF-\u0026alpha;, NF-\u0026kappa;B activation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate \u0026ndash; strong biomarkers but limited intervention data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJustifies anti-inflammatory dietary interventions and biomarker surveillance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlacental Immune Activation. \u003csup\u003e1, 3, 17\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr; IL-6, TNF-\u0026alpha;, TLR4 expression in placenta; oxidative stress and mitochondrial dysfunction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCytokines (IL-6, TNF-\u0026alpha;), ROS, mitochondrial markers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate \u0026ndash; limited human placental biopsies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuggests placental immune screening and dietary modulation of maternal inflammation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeonatal Immune Programming. \u003csup\u003e11, 12, 14, 16\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026uarr; allergic sensitization risk, \u0026darr; regulatory T cell development, \u0026uarr; metabolic syndrome and obesity in offspring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThymic output markers, Treg cell counts, infant microbiota composition\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u0026ndash;High \u0026ndash; supported by human cohort outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHighlights need for maternal diet counseling and early-life microbiome support\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeuro‑Immune Developmental Interaction. \u003csup\u003e7, 12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal UPF exposure associated with altered neurodevelopment and behavioral outcomes, possibly via neuroinflammation and gut\u0026ndash;brain axis dysregulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMicroglial activation, tryptophan metabolism, vagal signaling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u0026ndash;Moderate \u0026ndash; emerging human data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmphasizes importance of reducing UPF exposure to protect brain\u0026ndash;immune maturation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eLegend: SCFA\u0026thinsp;=\u0026thinsp;Short-Chain Fatty Acids; LPS\u0026thinsp;=\u0026thinsp;Lipopolysaccharide; CRP\u0026thinsp;=\u0026thinsp;C-reactive protein; TLR4\u0026thinsp;=\u0026thinsp;Toll-like receptor 4; ROS\u0026thinsp;=\u0026thinsp;Reactive Oxygen Species; Treg\u0026thinsp;=\u0026thinsp;Regulatory T cells. Strength of evidence graded by consistency, biological plausibility, and presence of human biomarker/clinical outcomes.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eTranslational, Clinical, and Policy Implications of Perinatal Ultraprocessed Food (UPF) Exposure\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTheme / Evidence Cluster\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eKey Evidence Summary\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRecommended Clinical Interventions\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eResearch Gaps / Priorities\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePolicy / Public Health Implications\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal Gut Dysbiosis. \u003csup\u003e1, 2, 5, 10, 17\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF intake \u0026rarr; reduced SCFA-producers, increased pro-inflammatory microbiota, \u0026uarr; gut permeability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePerinatal dietary counseling; probiotic/prebiotic supplementation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntervention trials on microbiota restoration; effect of diet substitution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInclude microbiome-health focus in antenatal nutrition guidelines\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlacental Inflammation. \u003csup\u003e1, 3, 17\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF-associated \u0026uarr; placental cytokines (IL-6, TNF-\u0026alpha;) and oxidative stress\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTargeted anti-inflammatory diets; screening for high-risk mothers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeed placental omics studies; biomarkers of immune activation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInform pregnancy risk assessment tools in national health programs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeonatal Immune Programming. \u003csup\u003e11, 12, 14, 16\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF-linked \u0026uarr; allergy risk, \u0026uarr; metabolic programming disorders\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEarly-life nutritional guidance; breastfeeding support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEpigenetic/immune developmental studies; long-term follow-up cohorts\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaternal dietary standards integrated with child allergy prevention programs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNeurodevelopmental Risk. \u003csup\u003e7, 12\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUPF exposure linked to neuroinflammation and impaired cognitive outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOmega-3/anti-inflammatory dietary support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClarify gut-brain-immune axis pathways\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducational campaigns on diet quality in reproductive-age women\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCross-cutting Social Determinants. \u003csup\u003e8, 18\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh UPF intake associated with socioeconomic disadvantage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTargeted nutrition subsidies and support programs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSocioeconomic interventions in nutrition research\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntegrate maternal UPF reduction into national food labeling \u0026amp; subsidy policies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eLegend: SCFA\u0026thinsp;=\u0026thinsp;Short-Chain Fatty Acids; IL-6\u0026thinsp;=\u0026thinsp;Interleukin-6; TNF-\u0026alpha;\u0026thinsp;=\u0026thinsp;Tumor Necrosis Factor-alpha. Themes integrate mechanistic, clinical, and socio-policy perspectives. References correspond to Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e numbering and superscript use in text.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eReview design\u003c/h2\u003e\u003cp\u003eThis study was conducted as a \u003cb\u003esystematic narrative review\u003c/b\u003e, following the principles of the PRISMA 2020 statement where applicable to ensure transparent reporting. Given the exploratory nature and mechanistic focus of the research question, no protocol was registered in PROSPERO.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSearch strategy\u003c/h3\u003e\n\u003cp\u003eA structured literature search was performed in PubMed, Scopus, and Web of Science, covering publications from January 2000 to March 2025. The search combined Medical Subject Headings (MeSH) and free-text terms related to \u0026ldquo;ultraprocessed foods,\u0026rdquo; \u0026ldquo;maternal diet,\u0026rdquo; \u0026ldquo;pregnancy,\u0026rdquo; \u0026ldquo;gut microbiome,\u0026rdquo; \u0026ldquo;placenta,\u0026rdquo; \u0026ldquo;immune development,\u0026rdquo; and \u0026ldquo;offspring health.\u0026rdquo; The strategy was designed to capture human observational studies, experimental models, and relevant systematic reviews describing perinatal exposure to ultraprocessed foods and outcomes related to maternal gut dysbiosis, placental immune activation, and neonatal immune programming \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eEligibility criteria\u003c/h3\u003e\n\u003cp\u003eIncluded studies met the following criteria: (1) assessed maternal UPF intake during pregnancy or lactation, (2) reported at least one mechanistic or clinical outcome relevant to maternal microbiota, systemic inflammation, placental biology, or neonatal immune/metabolic development, and (3) were original peer-reviewed human or animal studies, or systematic reviews of these outcomes. Excluded were conference abstracts, commentaries, non-English articles, and studies focused exclusively on unrelated exposures or outcomes.\u003c/p\u003e\n\u003ch3\u003eStudy selection and data extraction\u003c/h3\u003e\n\u003cp\u003eThe search retrieved 1,845 records. After duplicate removal, titles and abstracts were screened for relevance. Full-text review was performed on potentially eligible studies, with reasons for exclusion documented. Ultimately, \u003cb\u003e20 studies\u003c/b\u003e were included for qualitative synthesis, representing diverse study designs and populations (summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Data extraction focused on study population, exposure assessment, outcomes, mechanistic insights, and limitations. The PRISMA 2020 flow diagram illustrating literature screening is presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eQuality assessment\u003c/h3\u003e\n\u003cp\u003eStudy quality was assessed using validated instruments appropriate to study design: the Newcastle\u0026ndash;Ottawa Scale for observational studies and AMSTAR-2 for systematic reviews. Experimental animal studies were evaluated for compliance with ARRIVE guidelines. Quality ratings are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, while mechanistic evidence strength grading is presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData synthesis\u003c/h2\u003e\u003cp\u003eGiven heterogeneity in study designs and outcomes, quantitative meta-analysis was not feasible. Findings were synthesized thematically into four mechanistic domains: maternal gut dysbiosis, systemic inflammation and endotoxemia, placental immune activation, and neonatal immune programming. These domains were integrated into an overall conceptual model (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and linked to translational and policy considerations (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, \u003cb\u003eFig.\u0026nbsp;3\u003c/b\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results and Findings","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eLiterature screening\u003c/h2\u003e\u003cp\u003eThe search strategy identified 1,845 records across PubMed, Scopus, and Web of Science. After removing duplicates, 1,230 records were screened by title and abstract, and 130 full-text articles were reviewed. A total of 110 studies were excluded for reasons including non-original data, irrelevant outcomes, and insufficient exposure information. Twenty studies met the inclusion criteria and were incorporated into this review, representing diverse geographic regions and study designs, including human observational cohorts, clinical studies, experimental animal models, and systematic reviews\u0026sup1;⁻\u0026sup2;⁰. Study characteristics, exposure definitions, outcomes, mechanistic insights, and quality assessments are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The literature selection process is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMaternal gut dysbiosis\u003c/h2\u003e\u003cp\u003eMaternal consumption of ultraprocessed foods (UPFs) was consistently associated with alterations in gut microbiota composition. Observational data linked higher UPF intake with decreased alpha diversity and a reduction in beneficial short-chain fatty acid (SCFA)-producing taxa, including Bifidobacterium and Lactobacillus, alongside increased pro-inflammatory Enterobacteriaceae and Desulfovibrio\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Animal models demonstrated that maternal high-fat, high-sugar diets impair gut barrier integrity and increase circulating lipopolysaccharide (LPS) levels\u0026sup1;⁷, leading to metabolic endotoxemia and systemic inflammation. Narrative syntheses further emphasized the immune consequences of dysbiosis during pregnancy, highlighting changes in microbial metabolites and intestinal permeability that may influence maternal\u0026ndash;fetal immune interactions \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. These findings are integrated in the mechanistic synthesis (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e) and conceptualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eSystemic inflammation and endotoxemia\u003c/h2\u003e\u003cp\u003eUPF exposure was associated with elevated inflammatory biomarkers, including C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and markers of oxidative stress (malondialdehyde, 8-isoprostane)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Observational studies found positive associations between high maternal UPF intake and gestational hypertensive disorders and glycemic dysregulation \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, conditions frequently characterized by systemic inflammation. One cross-sectional study showed a dose-response relationship between maternal UPF consumption and circulating perfluoroalkyl substances, suggesting an additional burden of dietary environmental contaminants⁹. Collectively, these findings indicate that maternal UPF consumption creates an inflammatory milieu potentially capable of influencing placental immune function and fetal immune programming (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003ePlacental immune activation\u003c/h2\u003e\u003cp\u003eFew studies directly investigated placental tissue responses to maternal UPF exposure. Limited evidence from human samples and experimental animal models demonstrated increased toll-like receptor-4 (TLR4) expression, heightened oxidative stress, and elevated pro-inflammatory cytokines (IL-6, TNF-α) in placental tissue \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. These findings are consistent with the hypothesis that maternal dietary patterns rich in UPFs contribute to a pro-inflammatory intrauterine environment, potentially compromising placental immune tolerance and nutrient transfer.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eNeonatal immune programming\u003c/h2\u003e\u003cp\u003eMultiple studies reported associations between maternal UPF intake and neonatal immune and metabolic outcomes. Prospective cohorts observed increased risk of allergic sensitization and atopic dermatitis in infants whose mothers consumed higher amounts of UPFs during pregnancy\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Additionally, maternal UPF exposure was associated with greater risk of macrosomia, early-life adiposity, and long-term metabolic programming effects, including increased childhood obesity risk \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Experimental studies demonstrated that maternal protein restriction combined with high-fat postnatal diets exacerbate offspring cardiometabolic risk, highlighting the role of perinatal nutrition in immune and metabolic trajectory\u0026sup1;⁷. Mechanistic links included suppression of regulatory T cells, skewing toward T helper 2 (Th2) phenotypes, and altered gut colonization patterns in early life\u0026sup2;⁰. These findings are synthesized across mechanistic and translational dimensions in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, while Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e outlines clinical and policy implications. The integrated pathway of these effects is visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e and linked to actionable strategies in \u003cb\u003eFig.\u0026nbsp;3\u003c/b\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eSummary of evidence strength\u003c/h2\u003e\u003cp\u003eEvidence was strongest for associations between maternal UPF intake, gut dysbiosis, systemic inflammation, and neonatal metabolic risk (high confidence from human observational cohorts and experimental studies \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Direct mechanistic studies of placental immune function remain limited, representing an important research gap. Translational opportunities, including dietary counseling, microbiota-targeted therapies, and maternal nutrition policy interventions, are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\u003ch2\u003ePrincipal findings and interpretation\u003c/h2\u003e\u003cp\u003eThis systematic narrative review demonstrates that perinatal exposure to ultraprocessed foods (UPFs) exerts adverse effects on maternal gut microbiota, systemic immune activation, placental inflammation, and neonatal immune programming. Across diverse study designs and populations (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), UPF consumption consistently correlated with reduced microbiota diversity and depletion of short-chain fatty acid (SCFA)\u0026ndash;producing taxa, including Bifidobacterium and Lactobacillus, alongside enrichment of pro-inflammatory organisms such as Enterobacteriaceae and Desulfovibrio \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. These changes were mechanistically linked to increased intestinal permeability, endotoxemia, and activation of innate immune pathways, including toll-like receptor-4 (TLR4) signaling and oxidative stress responses \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. The resulting maternal systemic inflammation\u0026mdash;marked by elevated circulating lipopolysaccharide (LPS), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and C-reactive protein (CRP)\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e \u0026mdash;has been implicated in placental immune dysregulation and impaired fetal tolerance mechanisms.\u003c/p\u003e\u003cp\u003eNeonatal immune programming effects were observed in multiple prospective cohorts and experimental models, with maternal UPF exposure linked to suppression of regulatory T (Treg) cells, skewing toward T helper 2 (Th2) polarization, and increased risk of allergic sensitization, atopic dermatitis, and early-life metabolic programming \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. These mechanistic domains were synthesized into an integrated pathway (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e) demonstrating how maternal diet quality influences immune outcomes via microbiome-immune cross-talk, inflammatory mediators, and placental signaling.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eComparison with previous literature\u003c/h2\u003e\u003cp\u003ePrior reviews have described associations between maternal dietary patterns and perinatal outcomes but have rarely focused on the unique properties of UPFs\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Unlike minimally processed diets, UPFs contain refined ingredients, emulsifiers, and additives capable of disrupting gut microbial ecology and increasing gut permeability\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. The present synthesis provides a novel integrative framework linking maternal UPF consumption to transgenerational immune risk (Fig.\u0026nbsp;3), highlighting mechanistic pathways that have not been explicitly consolidated previously. In particular, the convergence of maternal dysbiosis and placental immune activation observed in experimental models \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e supports a paradigm in which UPF exposure exerts effects beyond macronutrient composition, implicating food processing itself as a biological stressor.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eClinical implications\u003c/h2\u003e\u003cp\u003eThe findings support urgent incorporation of UPF reduction strategies into perinatal nutrition counseling. Observational data indicate that women with higher UPF intake exhibit increased gestational weight gain and adverse metabolic outcomes \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, while offspring of these pregnancies are at greater risk of obesity, allergy, and impaired immune development \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Clinically, dietary interventions focusing on whole foods, probiotic or prebiotic supplementation, and anti-inflammatory nutrient profiles represent promising approaches. Moreover, recognition of UPFs as contributors to maternal systemic inflammation underscores the need for dietary assessment and counseling as standard components of antenatal care. Translational strategies, including microbiota-targeted therapeutics and structured dietary programs, are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003ePolicy and research priorities\u003c/h2\u003e\u003cp\u003eFrom a public health perspective, these findings provide evidence supporting regulatory measures aimed at reducing population-level UPF consumption, including improved labeling, taxation, and education campaigns targeting women of reproductive age. Socioeconomic determinants of UPF intake, including limited access to affordable whole foods, were identified in multiple included studies \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, highlighting the importance of addressing structural barriers to dietary quality.\u003c/p\u003e\u003cp\u003eDespite growing evidence, significant research gaps remain. Few studies directly interrogated placental immunology in the context of UPF exposure \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and mechanistic insights into epigenetic programming of neonatal immune pathways are largely derived from animal models \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Prospective human intervention studies examining the impact of UPF reduction or microbiota restoration strategies on maternal and neonatal immune outcomes are urgently needed. The integrated conceptual and translational frameworks provided by this review (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;3) may guide future research design and policy development.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eEthical considerations and call to action\u003c/h2\u003e\u003cp\u003eThe intergenerational nature of UPF-related immune programming raises profound ethical concerns. Pregnant individuals may be disproportionately exposed to UPFs due to socioeconomic constraints, limited access to unprocessed foods, and marketing pressures. Addressing UPF exposure is therefore not only a clinical challenge but also a societal obligation. Stakeholders\u0026mdash;including healthcare providers, researchers, policymakers, and industry\u0026mdash;must collaborate to reduce UPF consumption, promote microbiota-supportive nutrition, and safeguard long-term child health.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec22\" class=\"Section2\"\u003e\u003ch2\u003eStrengths, Limitations, and Future Directions\u003c/h2\u003e\u003cdiv id=\"Sec23\" class=\"Section3\"\u003e\u003ch2\u003eStrengths\u003c/h2\u003e\u003cp\u003eThis review has several notable strengths. It employed a systematic narrative approach with structured literature identification, screening, and quality appraisal using validated tools. The evidence synthesis integrated findings across multiple disciplines including obstetrics, microbiome science, nutrition, and immunology. By connecting maternal ultraprocessed food exposure to gut dysbiosis, systemic inflammation, placental immune activation, and neonatal immune programming, the review provides a mechanistic framework that is highly relevant to clinical practice and public health.\u003c/p\u003e\u003cp\u003eAnother strength is its translational focus. The findings were not limited to mechanistic insights but extended to clinical implications and policy recommendations. The review also highlights emerging issues such as socioeconomic determinants of diet, environmental contaminants associated with processed foods, and long-term metabolic programming risks for offspring, offering a foundation for future preventive strategies.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eDespite its strengths, certain limitations must be acknowledged. The review was not pre-registered, which may limit methodological transparency compared to formal systematic review protocols. Study heterogeneity precluded quantitative meta-analysis, as ultraprocessed food exposure was measured using diverse classification systems and outcome measures varied widely. In addition, few studies directly examined placental immune pathways, with many mechanistic insights inferred from gut and systemic inflammatory data. Evidence for epigenetic programming of neonatal immunity is still largely experimental rather than derived from large human cohorts.\u003c/p\u003e\u003cdiv id=\"Sec25\" class=\"Section3\"\u003e\u003ch2\u003eFuture Directions\u003c/h2\u003e\u003cp\u003eFuture research should focus on direct evaluation of placental immune responses and epigenetic mechanisms affected by maternal diet. Randomized interventions reducing ultraprocessed food intake or enhancing microbiota-supportive diets are needed to determine causality and inform clinical practice. Research addressing socioeconomic determinants of diet quality and evaluating policy measures, such as labeling reforms or food subsidies, will be essential for public health. Longitudinal cohort studies integrating multi-omics approaches will be critical for understanding how maternal dietary patterns influence offspring immune and metabolic health trajectories across the life course.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis systematic narrative review demonstrates that maternal consumption of ultraprocessed foods during pregnancy is linked to adverse biological effects spanning the maternal gut microbiome, systemic immune activation, placental inflammatory responses, and neonatal immune programming. Evidence indicates that poor maternal diet quality may disrupt gut microbial ecology, promote endotoxemia and systemic inflammation, and influence placental immune tolerance, ultimately shaping immune and metabolic outcomes in the offspring.\u003c/p\u003e\u003cp\u003eThese findings highlight the importance of addressing ultraprocessed food consumption as part of routine prenatal nutrition counseling and as a target for broader public health policy. Interventions that prioritize whole, minimally processed foods, promote microbiota-supportive nutrients, and reduce dietary exposure to pro-inflammatory components may offer tangible benefits for maternal and child health.\u003c/p\u003e\u003cp\u003eFuture research should deepen mechanistic understanding, particularly around placental immune regulation and epigenetic programming, while also addressing structural drivers of poor diet quality. Long-term follow-up studies and intervention trials are needed to translate mechanistic evidence into clinical recommendations and health policies capable of reducing transgenerational disease risk.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDISCLOSURE\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors appreciate the XXXX Society of Obstetrics and Gynecology (XXXX) and the XXXX Society of Maternal-Fetal Medicine (XXXX) for encouraging and supporting the work of this review article.\u003c/p\u003e\n\u003cp\u003eConflict of Interest\u003c/p\u003e\n\u003cp\u003eThe authors declare that there is no conflict of interest regarding the publication of this manuscript.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;All authors made substantial contributions to all aspects of this research. Contributions include conception and design of the study, development of the search strategy, literature screening and data extraction, quality assessment, interpretation of findings, drafting of the manuscript, critical revision for important intellectual content, and approval of the final version to be published. All authors agree to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGurumurthy G, Agrawal DK. Impact of maternal ultra-processed food consumption and preterm birth on the development of metabolic disorders in offspring. J Pediatr Perinatol Child Health. 2025;9:68-84. https://doi.org/10.26502/jppch.74050214\u003c/li\u003e\n\u003cli\u003eLu X, Shi Z, Jiang L, Zhang S. Maternal gut microbiota in the health of mothers and offspring: from the perspective of immunology. Front Immunol. 2024;15:1362784. https://doi.org/10.3389/fimmu.2024.1362784\u003c/li\u003e\n\u003cli\u003eCollado MC, Rautava S, Aakko J, Isolauri E, Salminen S. Human gut colonisation may be initiated in utero by distinct microbial communities in the placenta and amniotic fluid. Sci Rep. 2016;6:23129. https://doi.org/10.1038/srep23129\u003c/li\u003e\n\u003cli\u003eTalebi S, Mehrabani S, Ghoreishy SM, Wong A, Moghaddam A, Feyli PR, et al. The association between ultra-processed food and common pregnancy adverse outcomes: a dose-response systematic review and meta-analysis. BMC Pregnancy Childbirth. 2024;24:369. https://doi.org/10.1186/s12884-024-06489-w\u003c/li\u003e\n\u003cli\u003eBiagioli V, Matera M, Ramenghi LA, Falsaperla R, Striano P. Microbiome and pregnancy dysbiosis: a narrative review on offspring health. Nutrients. 2025;17:1033. https://doi.org/10.3390/nu17061033\u003c/li\u003e\n\u003cli\u003eBen-Avraham S, Kohn E, Tepper S, Lubetzky R, Mandel D, Berkovitch M, Shahar DR. Ultra-processed food intake in pregnancy and maternal and neonatal outcomes. Eur J Nutr. 2023;62:1403-1413. https://doi.org/10.1007/s00394-022-03072-x\u003c/li\u003e\n\u003cli\u003eMottis G, Kandasamey P, Peleg-Raibstein D. The consequences of ultra-processed foods on brain development during prenatal, adolescent and adult stages. Front Public Health. 2025;13:1590083. https://doi.org/10.3389/fpubh.2025.1590083\u003c/li\u003e\n\u003cli\u003eCarreira NP, Lima MC, Travieso SG, Sartorelli DS, Crivellenti LC. Fatores maternos associados ao consumo usual de alimentos ultraprocessados na gesta\u0026ccedil;\u0026atilde;o. Cien Saude Colet. 2024;29:e16302022. Portuguese. https://doi.org/10.1590/1413-81232024291.16302022\u003c/li\u003e\n\u003cli\u003eNaspolini NF, Machado PP, Moreira JC, Asmus CIRF, Meyer A. Maternal consumption of ultra-processed foods and newborn exposure to perfluoroalkyl substances (PFAS). Cad Saude Publica. 2021;37:e00152021. https://doi.org/10.1590/0102-311X00152021\u003c/li\u003e\n\u003cli\u003ede Oliveira PG, de Sousa JM, Assun\u0026ccedil;\u0026atilde;o DGF, de Araujo EKS, Bezerra DS, Dametto JFDS, Ribeiro KDDS. Impacts of consumption of ultra-processed foods on maternal-child health: a systematic review. Front Nutr. 2022;9:821657. https://doi.org/10.3389/fnut.2022.821657\u003c/li\u003e\n\u003cli\u003eWang Y, Wang K, Du M, Khandpur N, Rossato SL, Lo CH, et al. Maternal consumption of ultra-processed foods and subsequent risk of offspring overweight or obesity: results from three prospective cohort studies. BMJ. 2022;379:e071767. https://doi.org/10.1136/bmj-2022-071767\u003c/li\u003e\n\u003cli\u003ePuig-Vallverd\u0026uacute; J, Romaguera D, Fern\u0026aacute;ndez-Barr\u0026eacute;s S, Gignac F, Ibarluzea J, Santa-Maria L, et al. 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Front Physiol. 2022;13:829920. https://doi.org/10.3389/fphys.2022.829920\u003c/li\u003e\n\u003cli\u003eRodrigues CAO, Andrade RES, Silva RRV, Brito MFSF, de Pinho L. Consumption of ultra-processed foods and its association with sociodemographic, clinical and nutritional characteristics by pregnant women assisted in the public health network. Psychol Health Med. 2025;1-18. https://doi.org/10.1080/13548506.2025.2519226\u003c/li\u003e\n\u003cli\u003eMorales-Suarez-Varela M, Rocha-Velasco OA. Impact of ultra-processed food consumption during pregnancy on maternal and child health outcomes: a comprehensive narrative review of the past five years. Clin Nutr ESPEN. 2025;65:288-304. https://doi.org/10.1016/j.clnesp.2024.12.006\u003c/li\u003e\n\u003cli\u003eRodr\u0026iacute;guez-Cano AM, Gonz\u0026aacute;lez-Ludlow I, Su\u0026aacute;rez-Rico BV, Montoya-Estrada A, Pi\u0026ntilde;a-Ram\u0026iacute;rez O, Parra-Hern\u0026aacute;ndez SB, et al. Ultra-processed food consumption during pregnancy and its association with maternal oxidative stress markers. Antioxidants (Basel). 2022;11:1415. https://doi.org/10.3390/antiox11071415\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Ultraprocessed foods, Maternal gut dysbiosis, Placental inflammation, Neonatal immune programming, Perinatal nutrition","lastPublishedDoi":"10.21203/rs.3.rs-8193289/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8193289/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective:\u003c/h2\u003e\u003cp\u003eTo synthesize and critically evaluate evidence linking perinatal exposure to ultraprocessed foods (UPFs) with maternal gut dysbiosis, placental inflammation, and neonatal immune programming, and to identify translational implications for perinatal care.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eA systematic narrative review was conducted following PRISMA 2020 guidelines, without PROSPERO registration. Literature searches of major databases (2000\u0026ndash;March 2025) identified 1,845 records. After screening and eligibility assessment, 20 studies were included. Study quality was appraised using validated tools, and data were synthesized thematically into evidence domains covering maternal microbiota, inflammatory pathways, placental changes, and neonatal immune outcomes.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eMaternal UPF consumption was associated with gut dysbiosis characterized by reduced microbial diversity, increased pro-inflammatory taxa, and systemic endotoxemia. Elevated inflammatory biomarkers including lipopolysaccharide, interleukin-6, tumor necrosis factor-α, and C-reactive protein were frequently reported. Limited placental studies revealed increased innate immune activation and oxidative stress. Neonatal immune alterations included regulatory T cell suppression, T helper 2 skewing, increased allergic sensitization, and metabolic programming changes. Evidence strength was highest for maternal gut dysbiosis and immune programming but limited for direct placental mechanisms. Translational opportunities include dietary counseling, microbiota-targeted interventions, and public health strategies aimed at improving maternal diet quality.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e\u003cp\u003ePerinatal exposure to UPFs adversely impacts the maternal gut\u0026ndash;placenta\u0026ndash;fetal immune axis. Integrated dietary interventions and population-level nutrition policies are urgently needed to mitigate downstream transgenerational immune risk.\u003c/p\u003e","manuscriptTitle":"Perinatal Exposure to Ultraprocessed Foods and Its Impact on Maternal Gut Dysbiosis, Placental Inflammation, and Neonatal Immune Programming: A Systematic Narrative Review","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-01 08:03:34","doi":"10.21203/rs.3.rs-8193289/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"423e4212-790a-4cb0-8efc-555d8ebf29c4","owner":[],"postedDate":"December 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":58507548,"name":"Obstetrics \u0026 Gynecology"}],"tags":[],"updatedAt":"2025-12-01T08:03:34+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-01 08:03:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8193289","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8193289","identity":"rs-8193289","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}