Risk factors and interventions for pediatric allergic diseases: an umbrella review

Risk factors and interventions for pediatric allergic diseases: an umbrella review | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 5 January 2026 V1 Latest version Share on Risk factors and interventions for pediatric allergic diseases: an umbrella review Authors : Han Wang 0009-0009-6021-539X [email protected] , Qiuling Hu , Jian Li , Kaining Chen , Xiaoxuan Qi , Rongxin Zhang , Xi Wang , Yongkun Wang , and Yiwen Li Authors Info & Affiliations https://doi.org/10.22541/au.176760020.02216191/v1 147 views 108 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background: The global burden of pediatric allergic diseases continues to rise. However, clinical and public health decisions remain guided by an extensive yet fragmented evidence base characterized by substantial uncertainty, hindering the development of effective preventive and therapeutic strategies. Objective: To address this evidence gap, we conducted a comprehensive umbrella review to establish a hierarchically structured evidence map of all reported risk factors and interventions for pediatric allergic diseases. Methods: We systematically searched PubMed for systematic reviews and meta-analyses (published up to February 23, 2025) on risk factors or interventions for core pediatric allergic conditions. Methodological quality was assessed using AMSTAR 2. Statistically significant associations ( p <0.05) were graded into four evidence levels—strong, highly suggestive, suggestive, or weak—based on predefined criteria including statistical significance, sample size, heterogeneity (I 2 ), small-study effects (Egger’s test), excess significance bias, and robustness in 10% credibility ceiling analysis. Results: This review synthesizes evidence from 60 meta-analyses, encompassing 176 unique associations. Despite the extensive factors discussed in the literature, rigorous grading identified only three risk factors supported by strong evidence: neonatal jaundice, pesticide exposure, and postnatal maternal depression. Six additional associations (involving five factors)—acid suppressants, birthweight, cesarean section, montelukast, and Chinese herbal bath—were graded as highly suggestive. The vast majority of investigated factors, including many nutritional supplements and environmental modifications, were supported by only weak or non-suggestive evidence. Conclusion: This umbrella review reveals a pronounced disparity between the volume of published literature and the strength of available evidence in pediatric allergy. The findings argue for a strategic shift in research focus: from underpowered associative studies toward 1) mechanistic investigation of the identified strong risk factors, and 2) definitive trials for highly suggestive interventions. Risk factors and interventions for pediatric allergic diseases: an umbrella review Running title: Umbrella Review of Pediatric Allergic Diseases Word count: 3364 Number of figures: 1 Number of tables: 5 Han Wang 1* , Qiuling Hu 2 , Jian Li 3 , Kaining Chen 4 , Xiaoxuan Qi 5 , Rongxin Zhang 6 , Xi Wang 7 , Yongkun Wang 8 , Yiwen Li 9 1 Department of Pediatrics, The Second Hospital of Dalian Medical University, Dalian, China 2 Department of Pediatrics, The Second Hospital of Dalian Medical University, Dalian, China 3 Department of Pediatrics, Shengjing Hospital of China Medical University, Shenyang, China 4 Department of Discipline Construction and Scientific Research Management, The Second Hospital of Dalian Medical University, Dalian, China 5 Department of Pediatrics, The Second Hospital of Dalian Medical University, Dalian, China 6 Department of Dermatology, The Second Hospital of Dalian Medical University, Dalian, China 7 Department of Ophthalmology, The Second Hospital of Dalian Medical University, Dalian, China 8 Department of Otolaryngology, The Second Hospital of Dalian Medical University, Dalian, China 9 Department of Pediatrics, Liaoyu Hospital of Dalian, Dalian, China *Correspondence to: Han Wang, Department of Pediatrics, The Second Hospital of Dalian Medical University, Dalian, China. Email: [email protected] Abstract Background: The global burden of pediatric allergic diseases continues to rise. However, clinical and public health decisions remain guided by an extensive yet fragmented evidence base characterized by substantial uncertainty, hindering the development of effective preventive and therapeutic strategies. Objective: To address this evidence gap, we conducted a comprehensive umbrella review to establish a hierarchically structured evidence map of all reported risk factors and interventions for pediatric allergic diseases. Methods: We systematically searched PubMed for systematic reviews and meta-analyses (published up to February 23, 2025) on risk factors or interventions for core pediatric allergic conditions. Methodological quality was assessed using AMSTAR 2. Statistically significant associations ( p <0.05) were graded into four evidence levels—strong, highly suggestive, suggestive, or weak—based on predefined criteria including statistical significance, sample size, heterogeneity (I²), small-study effects (Egger’s test), excess significance bias, and robustness in 10% credibility ceiling analysis. Results: This review synthesizes evidence from 60 meta-analyses, encompassing 176 unique associations. Despite the extensive factors discussed in the literature, rigorous grading identified only three risk factors supported by strong evidence: neonatal jaundice, pesticide exposure, and postnatal maternal depression. Six additional associations (involving five factors)—acid suppressants, birthweight, cesarean section, montelukast, and Chinese herbal bath—were graded as highly suggestive. The vast majority of investigated factors, including many nutritional supplements and environmental modifications, were supported by only weak or non-suggestive evidence. Conclusion: This umbrella review reveals a pronounced disparity between the volume of published literature and the strength of available evidence in pediatric allergy. The findings argue for a strategic shift in research focus: from underpowered associative studies toward 1) mechanistic investigation of the identified strong risk factors, and 2) definitive trials for highly suggestive interventions. Keywords: Pediatric allergic diseases, Umbrella review, Evidence hierarchy, Risk factors, Prevention, Systematic review Key Message: This umbrella review of 60 meta-analyses identifies only three factors—neonatal jaundice, pesticide exposure, and postnatal maternal depression—with robust association to childhood allergy risk. The stark contrast between the volume of literature and the strength of evidence calls for a strategic shift in research priorities toward mechanistic exploration of these factors and definitive trials for promising interventions. Introduction Allergic diseases—including asthma, food allergy, eczema, and allergic rhinoconjunctivitis—represent a spectrum of chronic, complex inflammatory disorders driven by gene-environment interactions. They impose a substantial and growing health burden on children globally, which continues to escalate; for example, the prevalence of food allergy has risen from approximately 1% to 4–7.1% over the past two decades 1-3 . Similarly, allergic rhinitis affects up to 25% of children and 40% of adults 4 . Of particular concern is the increasing proportion of children presenting with multiple coexisting conditions, a pattern described as allergic multimorbidity 5 . Despite this rising burden, clinical management has remained largely reactive. This disconnect highlights an urgent need to shift toward proactive strategies capable of preventing new-onset allergies, modifying disease trajectories, and integrating effective treatments. Children represent an ideal target population for such a transition, given the heightened plasticity of their developing immune systems and their susceptibility to immunomodulation 6 . Therapeutically, the field is evolving toward a proactive paradigm that includes early introduction of allergenic foods, targeted immunomodulatory treatments, skin barrier protection with emollients 7,8 , and immune-nutritional approaches to modulate the gut-immune axis 9 . Furthermore, probiotics 10 , allergen immunotherapy 6 , bacterial products 11 , and biologics 12 are increasingly being incorporated into comprehensive management frameworks. However, the evidence supporting these diverse strategies is vast, fragmented, and of heterogeneous quality, creating a landscape of considerable uncertainty for clinical and public health decision-making. To address this evidence gap and chart a clear path forward, we conducted the present umbrella review. This review systematically appraises and synthesizes the evolving evidence on interventions across the pediatric allergy spectrum—from prevention to management—including the supportive roles of breastfeeding, vitamin D, and microbial exposure. Our objectives are threefold: to evaluate the strength and validity of the available evidence, to provide a clear and hierarchical overview of the current evidence landscape, and thereby to inform evidence-based clinical practice and public health guidelines. 2. Methods 2.1 Protocol and Study Design This umbrella review was conducted in accordance with a prespecified protocol that detailed the research questions, eligibility criteria, search strategy, data extraction, and planned analytical methods. The protocol was developed prior to the initiation of the study and was adhered to throughout the review process to ensure methodological rigor, transparency, and reproducibility. 2.2 Search Strategy and Eligibility Criteria We systematically searched PubMed to identify systematic reviews and meta-analyses published up to February 23, 2025, examining associations between potential risk factors and pediatric allergic diseases. No restrictions were placed on publication date or study design. To ensure comprehensive coverage, we additionally performed manual screening of the reference lists of eligible articles. The search strategy incorporated the following key terms: (child[Title/Abstract] OR adolescent[Title/Abstract] OR teenager[Title/Abstract] OR pediatric[Title/Abstract] OR childhood[Title/Abstract] OR children[Title/Abstract]) AND (Allergic [Title/Abstract] OR Hypersensitivity [Title/Abstract] OR Anaphylaxis [Title/Abstract] OR allergic rhinitis [Title/Abstract] OR Atopic dermatitis[Title/Abstract] OR allergic dermatitis [Title/Abstract] OR Asthma[Title/Abstract] OR allergic eye disease[Title/Abstract] OR food allergy[Title/Abstract] OR Urticaria [Title/Abstract] ) AND (meta-analysis[Title/Abstract] OR systematic review[Title/Abstract]). Following title and abstract screening, potentially relevant articles were identified and subjected to full-text review. Two authors independently performed the study selection process to determine final eligibility. Studies were included if they met all of the following criteria: 1. Systematic reviews or meta-analyses involving pediatric populations (ages 2–18 years) diagnosed with at least one core allergic disease (e.g., asthma, food allergy, eczema, allergic rhinitis). 2. Investigation of risk factors or interventions related to allergic diseases. 3. Reporting of complete outcome measures relevant to allergic diseases (e.g., disease incidence, immunoglobulin E [IgE] levels). 4. Inclusion of at least two original studies in the meta-analysis. If multiple meta-analyses examined the same association, the one with the largest sample size was selected. 5. Published in English in a peer-reviewed journal. 2.3 Data Extraction Two investigators independently extracted data from the included meta-analyses. Discrepancies were resolved through discussion or, if necessary, consultation with a third reviewer. The following data were retrieved from each meta-analysis: first author, allergic disease type(s), number of cases (only studies based on binary data), total population size, effect measure (risk ratio [RR], odds ratio [OR], hazard ratio [HR], standardized mean difference [SMD], or mean difference [MD]) with the corresponding 95% confidence interval (CI). 2.4 Quality Assessment Two authors independently assessed the methodological quality of the included systematic reviews and meta-analyses using AMSTAR 2 13 (A Measurement Tool to Assess Systematic Reviews, version 2.0). Discrepancies were resolved through discussion. AMSTAR 2 comprises 16 items and provides a more comprehensive and structured appraisal of systematic reviews, particularly those incorporating non‑randomized studies, compared with the original 11‑item AMSTAR. Instead of generating an overall numeric score, AMSTAR 2 classifies the methodological quality of each review as high, moderate, low, or critically low. 2.5 Statistical Analysis 2.5.1 Assessment of Summary Effects and Heterogeneity For each association between allergic diseases and a risk factor or intervention, we applied a random‑effects model to obtain a pooled effect estimate (e.g., odds ratio, risk ratio) with its 95% confidence interval (CI) and corresponding p ‑value 14 . Heterogeneity was assessed using Cochran’s Q test and the I ² statistic. To quantify the uncertainty associated with the heterogeneity estimate, we also calculated the 95% confidence interval of I² 15 . 2.5.2 Estimation of Prediction Intervals To further assess between-study heterogeneity and predict the range of effects in future individual studies, we calculated 95% prediction intervals (PIs) for the random-effect summary estimates 16 . 2.5.3 Assessment of Small-Study Effects To evaluate potential small-study effects (which may arise from publication bias, genuine heterogeneity, or chance), we applied Egger’s regression asymmetry test. A p -value<0.10 was considered indicative of statistically significant small-study effects 17 . 2.5.4 Evidence of Excess Significance Bias The excess significance test was employed to assess whether the observed number (O) of studies with statistically significant results ( p <0.05) differed from the expected number (E) of such studies. The expected number (E) was calculated as the sum of the statistical power estimates for each individual study within the meta‑analysis, using an algorithm based on the non‑central t distribution. A positive excess significance test result was defined as O>E with an associated p ‑value<0.10 18 . 2.5.5 10% Credibility Ceiling Analysis As a sensitivity analysis to account for methodological limitations inherent in observational studies, we applied a 10% credibility ceiling. This method posits that, regardless of a study’s scale or quality, the plausible true effect size is unlikely to exceed the observed effect by more than 10%. We accordingly re-estimated the summary effect estimates and between-study heterogeneity under this constraint 19 . 2.6 Grading the Existing Evidence We classified statistically significant associations ( p <0.05) between allergic diseases and risk factors or interventions into four evidence levels: strong, highly suggestive, suggestive, and weak/non-suggestive, based on the following predefined criteria: Strong evidence: required p <10 −6 , more than 1,000 cases for binary outcomes or a total population exceeding 20,000 for continuous outcomes, a statistically significant largest study in the meta-analysis ( p <0.05), low between-study heterogeneity (𝐼 2 0.1), a 95% prediction interval excluding the null value, no excess significance bias ( p >0.1), and survival of the 10% credibility ceiling test ( p <0.05). Highly suggestive evidence: required p 20,000 for continuous outcomes, and a statistically significant largest study ( p <0.05). Suggestive evidence: required p 20,000 for continuous outcomes. Weak evidence: was assigned to associations with p <0.05 that did not meet the criteria for higher evidence levels 20 . All meta-analyses and statistical tests were conducted using Stata (version 12.0; Stata Corp, College Station, TX, USA). 3. Result 3.1 Characteristics of the Included Systematic Reviews and Meta-Analyses A total of 1,848 records were identified through database searches and manual reference screening. After removing duplicates, 1,761 records remained for title and abstract screening, of which 1,656 were excluded. Full-text review was conducted for the remaining 105 articles, resulting in 60 studies that met the inclusion criteria 21-80 . The flowchart is shown in Figure 1, and the full list of the 105 studies and exclusion reasons for 45 of excluded studies are shown in Supplementary Table S1. This umbrella review synthesized evidence from 60 meta-analyses covering a broad spectrum of factors related to childhood allergies, including interventional and therapeutic approaches, risk factors, and maternal determinants such as mode of delivery and maternal health conditions. Table 1 and Table 2 summarize the characteristics of the 176 (128 binary and 48 continuous) exposure–outcome associations derived from the included systematic reviews and meta‑analyses. 3.2 Assessment of Methodological Quality with AMSTAR 2.0 The methodological quality of all included systematic reviews and meta-analyses was rated as low or moderate using the 16-item AMSTAR 2.0 tool. Detailed results, scoring criteria, and rating criteria are provided in Supplementary Table S2. A majority of the included studies had at least one critical flaw, most commonly in items 7 (58/60, 97%) and non-critical flaws, most commonly in items 10 (60/60, 100%). Notably, methodological quality was rated as low if at least one critical flaw was present (irrespective of non‑critical flaws), and as moderate if no critical flaws were identified. 3.3 Summary Effect Size We reanalyzed the 176 associations using a random-effects model to obtain more conservative estimates. Among these, 38 associations (22 binary and 16 continuous) reached a significance level of p <10 −6 (Table 3, Table 4, Supplementary Table S3 and Supplementary Table S4). Notable binary factors among these were neonatal jaundice, pesticide exposure, and postnatal maternal depression. Another 29 associations (20 binary and 9 continuous) showed moderate statistical significance ( p <10 −3 ). These included binary exposures such as overweight, obesity. The remaining 109 associations (86 binary and 23 continuous) were either marginally significant ( p <0.05) or non-significant. 3.4 Heterogeneity Of the 176 associations, 91 (51.7%, 76 binary and 15 continuous) exhibited significant heterogeneity ( p <0.1). Among these heterogeneous associations, 72 associations (43 binary and 29 continuous) showed high heterogeneity, while 48 (44 binary and 4 continuous) presented moderate to high heterogeneity. To further assess between-study heterogeneity, we calculated 95% prediction intervals (PIs). The 95% PIs for 170 associations (125 binary and 45 continuous) excluded the null value (Table 3, Table 4, Supplementary Table S3 and Supplementary Table S4). 3.5 Small-Study Effects Small-study effects were observed in 52 associations (45 binary and 7 continuous). Binary exposures showing this effect included cesarean section, traffic-related NO₂ exposure, and antibiotic use during pregnancy, among others. Continuous variables affected comprised measures such as montelukast and sublingual immunotherapy (SLIT) outcomes, all of which showed a significant Egger’s test result ( p <0.1) (Table 3, Table 4, Supplementary Table S3 and Supplementary Table S4). 3.6 Excess Significance Excess significance was observed in 29 associations (15 binary and 14 continuous), each showing observed greater than expected effects (𝑂>𝐸) and a significance level of p <0.1 (Table 3, Table 4, Supplementary Table S3 and Supplementary Table S4). 3.7 10% Credibility Ceiling Among the 176 associations, 60 (45 binary and 15 continuous) remained statistically significant after applying a 10% credibility ceiling test. These included all associations graded as strong, highly suggestive, or suggestive, as well as most of those classified as weak evidence. Detailed results are presented in Table 3, Table 4, Supplementary Table S3 and Supplementary Table S4. 3.8 Robustness of Evidence Among the 128 binary associations, the evidence was graded as strong for three associations: 1) neonatal jaundice and the higher risk of asthma; 2) pesticide exposure and the higher risk of respiratory tract infection; 3) postnatal maternal depression and the higher risk of asthma. highly suggestive for three associations: 1) acid suppressants and the higher risk of asthma; 2) birthweight and the higher risk of wheeze; 3) cesarean section and the higher risk of allergic rhinitis. suggestive for 8 associations, weak for 56 associations, and not suggestive for 58 associations. Regarding the 48 continuous associations, none were classified as strong or highly suggestive. The majority were graded as weak (33/48), while 15 were not suggestive. Detailed results are provided in Table 3, Table 4, Supplementary Table S3 and Supplementary Table S4. 3.9 Re-grading of Evidence Using an Adjusted (Pragmatic) Sample Size Criterion for Continuous Outcomes The primary evidence grading for continuous variables adhered to a stringent sample size threshold (total population >20,000). However, recognizing that pediatric intervention studies frequently face recruitment challenges leading to smaller sample sizes, we conducted a pre-planned alternate analysis to examine the robustness of our findings by re-applying the evidence grading framework with a pragmatic sample size cutoff. We re-applied the evidence grading framework using the median total sample size across all 48 continuous-variable meta-analyses (n = 420.5) as an alternative, more pragmatic cutoff, while keeping all other statistical criteria unchanged. Under this adjusted criterion, three associations that were graded as weak in the primary analysis met the threshold for highly suggestive evidence: 1) montelukast with the lower interleukin-4 levels; 2) montelukast with the lower IgE levels; and 3) Chinese herbal bath with a lower SCORAD (Scoring Atopic Dermatitis) index. These pertain to two interventions (montelukast and Chinese herbal bath). Importantly, the remaining 45 continuous associations (93.8%) retained their classification of weak or nonsuggestive evidence even under this relaxed sample size criterion, underscoring the overall fragility of the evidence base for continuous outcomes in pediatric allergy. Complete results of this alternate grading analysis are presented in Table 5. The fact that only three associations reached a higher evidence grade even under relaxed sample size criteria underscores the general fragility of continuous outcome evidence in pediatric allergy research. 4. Discussion 4.1 Main Findings and Interpretation in Light of Existing Evidence Our review reveals that the evidence base for pediatric allergic diseases is highly heterogeneous. Our most salient finding is that only three risk factors (neonatal jaundice, pesticide exposure, postnatal maternal depression) attained the highest (‘strong’) evidence grade, while an additional five associations (acid suppressants, birthweight, cesarean section, montelukast, Chinese herbal bath) met the criteria for “highly suggestive” evidence. The vast majority of examined associations were underpinned by only weak or non‑suggestive findings. This stark discrepancy underscores a critical gap between the multitude of factors discussed in the literature and those with sufficient empirical support to reliably guide clinical and public health decision‑making. The identification of neonatal jaundice and postnatal maternal depression as risk factors for childhood asthma supported by strong evidence is particularly instructive, as both point to the potential importance of early‑life stress events in shaping later allergic susceptibility. This observation suggests a significant pathway that is distinct from—yet may interact with—the well‑established paradigm of early‑life microbiota‑immune system interactions in immune development and atopic risk 81 . We hypothesize that neonatal jaundice—with its common management by phototherapy and associated potential for maternal separation—acts as a key physiological and psychosocial stressor during a critical window of immune development. Parallelly, postnatal depression can alter maternal-infant bonding, caregiving behaviors, and the infant’s own stress-response systems. If both are indeed meaningful early‑life stressors, their combined effect could converge to dysregulate the hypothalamic‑pituitary‑adrenal (HPA) axis and promote a pro‑inflammatory state—a mechanism firmly grounded in established psychoneuroimmunological principles 82 . Within the specific context of allergic disease, such inflammatory and neuroendocrine signals represent essential components of functional neuro‑immune crosstalk, which can directly favor a Th2‑skewed immune phenotype 83 . This interpretation aligns with the developmental origins of health and disease (DOHaD) framework and extends it significantly, by integrating neuro‑immune pathways as a central mechanistic dimension 82 . Building directly on our hierarchical evidence grading, the compelling narrative surrounding early-life stressors should not detract from the broader, more sobering picture painted by our analysis. In stark contrast to the few robust associations identified, the overwhelming majority of factors investigated in the literature—encompassing a wide array of nutritional supplements, environmental modifications, and therapeutic agents—are supported by only weak or non-suggestive evidence. This pervasive paucity of robust evidence highlights a state of considerable uncertainty at the heart of pediatric allergy research and practice, echoing broader concerns about the reliability of biomedical research evidence 84 . It forces a critical reevaluation: for many widely debated strategies, the current data are simply insufficient to conclude a meaningful effect or to justify their prioritization in guidelines and resource allocation. The strong evidence grade for pesticide exposure underscores a different, yet equally important, aspect of our findings: the validation of established paradigms. Unlike the novel associations with early-life stress, the link between pesticide exposure and respiratory outcomes is supported by a coherent biological rationale. Modern toxicological studies delineate how environmental toxicants disrupt epithelial barriers and promote immune dysregulation 85 , and epidemiological research has quantified the mediating role of oxidative stress and immune alterations in this association 86 . Our umbrella review consolidates and elevates this knowledge by providing the highest level of quantitative synthesis, significantly reducing the uncertainty that can arise from individual studies. This serves as a critical methodological checkpoint; the fact that our rigorous grading system confidently identifies such an expected, biologically plausible strong signal reinforces the validity and discriminatory power of our approach. The associations graded as “highly suggestive” represent a critical tier of evidence: they are the most compelling candidates for being true effects that meet several but not all of the most stringent criteria. Their interpretation requires careful nuance. For instance, the observed association for montelukast in reducing specific biomarkers like IL-4 and IgE is entirely consistent with its established mechanism as a leukotriene receptor antagonist in the Th2 pathway 87 . This lends considerable biological credibility to the association and strongly supports its use in a biomarker-defined patient subset. However, its classification as highly suggestive rather than strong primarily reflects limitations in the available meta-analyses rather than doubt about the underlying biology 88 . Conversely, the highly suggestive evidence for cesarean section and birth weight as risk factors reinforces the overarching theme of early-life influences, yet its lower grade suggests a more modest effect size, greater susceptibility to unmeasured confounding, or both. These distinctions are precisely what our grading system aims to illuminate: they guide where the next generation of large, well-controlled prospective studies should be directed to convert “highly suggestive” into “strong” evidence. In summary, while the strong evidence for factors like pesticide exposure validates existing pathophysiological paradigms, the highly suggestive evidence for factors such as cesarean section highlights critical early-life influences that require confirmation through more rigorous research. The most profound implication of our review lies not in the few robust signals, but in the vast expanse of associations that failed to achieve strong or even highly suggestive status. This widespread lack of robust evidence for the majority of interventions and risk factors studied demands a fundamental shift in how the field prioritizes research–a shift that is imperative to address the systemic issues of research fragility and waste 84 . For many nutritional supplements, environmental modifications, and even some pharmacological agents, the consistently weak evidence suggests one of three possibilities: (1) the true effect is negligible or absent; (2) the effect exists but is small and highly context-dependent, obscured by excessive heterogeneity; or (3) the existing body of primary research is methodologically inadequate to detect a true effect. Distinguishing between these possibilities is the paramount challenge. Our findings strongly suggest that continued investment in underpowered, duplicative associative studies on these topics may be of limited value. Instead, we advocate for the field to embrace a more strategic, mechanistic, and hypothesis-testing research agenda 89 . Resources should be concentrated on elucidating the pathways identified by strong evidence and on designing definitive trials to verify highly suggestive associations. 4.2 Strengths and Limitations This umbrella review has several key strengths. It is the first, to our knowledge, to apply a comprehensive, prespecified evidence grading framework to the entire landscape of pediatric allergic diseases, allowing for direct comparison across diverse risk factors and interventions. Our methodology was rigorous, employing AMSTAR 2 for quality assessment 13 , evaluating multiple dimensions of evidence, and conducting sensitivity analyses. However, several limitations must be acknowledged. The validity of our synthesis is inherently dependent on the quality of the included meta-analyses. While we adopted a comprehensive, prespecified grading framework 90 , any such framework inevitably involves arbitrary thresholds that can influence classifications. Furthermore, as an umbrella review, we could not control for confounding at the level of the original primary studies. Despite these limitations, our review provides the most systematic and hierarchically structured overview to date, establishing a clear benchmark for future evidence. In summary, this review establishes a clear evidence hierarchy for pediatric allergy, distinguishing a few strong, actionable signals from a multitude of associations with limited or insufficient evidence. To advance the field, research resources should shift toward elucidating the mechanisms underlying the strong signals and conducting definitive trials on the most promising interventions, rather than perpetuating research on factors with minimal empirical support. Author Contributions Han Wang: Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing – original draft, Visualization, Project administration. Qiuling Hu: Methodology, Investigation, Data curation, Writing – review & editing. Jian Li: Investigation, Writing – review & editing. Kaining Chen: Formal analysis, Writing – review & editing. Xiaoxuan Qi: Investigation, Data curation, Writing – review & editing. Rongxin Zhang: Investigation, Writing – original draft, Writing – review & editing. Xi Wang: Investigation, Data curation, Writing – review & editing. Yongkun Wang: Formal analysis, Writing – review & editing. Yiwen Li: Conceptualization, Supervision, Writing – review & editing. All authors have read and approved the final version of the manuscript. The formal statistical analysis was supported by Xi Zhong (Department of Breast Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine), who is not listed as an author. The corresponding author (Han Wang) attests that all listed authors meet the authorship criteria and that no others meeting the criteria have been omitted. Acknowledgements We thank Doctor Xi Zhong from Department of Breast Surgery, The Second Affiliated Hospital of Zhejiang University School of Medicine for assistance in statistical analysis. Funding Information This research received no external funding. Conflict of Interest Statement The authors declare no conflict of interest. Ethical Considerations This study is an umbrella review synthesizing data from previously published systematic reviews and meta-analyses. No original data involving human participants or animals were collected. Therefore, ethical approval and informed consent were not required for this research. Data sharing Analyzed data are presented in Supplementary Material S1 and S2. References 1 Sasaki, M. et al. Prevalence of clinic-defined food allergy in early adolescence: The SchoolNuts study. 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Characteristics of the meta-analyses in the included systematic reviews based on binary data Li2022 Vitamin D Children Asthma the Risk of Asthma RR 11 577/1143 0.84(0.65-1.08) Luo2021 Vitamin D (Pregnancy or Infancy) Children Allergic Rhinitis the Risk of Allergic Rhinitis RR 3 689/1402 0.93(0.78-1.11) the Risk of LRTI RR 3 741/1452 0.97(0.85-1.11) You2024 Crisaborole Children Atopic Dermatitis ISGA Success OR 7 5076/7629 1.56(1.24-1.96) SPS OR 5 3656/5437 1.70(1.10-2.63) Yang2023 Montelukast Sodium Children Cough Variant Asthma Effective Rate RR 15 722/1436 1.23(1.18-1.29) Xu2021 Ipratropium Bromide and Salbutamol Children and Adolescents Asthma the Risk of Hospital Admission RR 15 1376/2754 0.79(0.66-0.95) Li2019 Hypertonic Saline Nasal Children Allergic Rhinitis Rescue Antihistamine Use Rates RR 3 119/298 0.68(0.48-0.95) Papamichael2018 Long Chain Omega-3 Fatty Acids Children Asthma Incidence of Asthma OR 3 3997/9366 0.75(0.60-0.95) Song2022 Acid Suppressants Children the Risk of Food Allergy HR 3 14114/964812 1.61(0.92-2.82) the Risk of Asthma HR 4 63021/145924 1.44(1.31-1.58) Fu2022 Pediatric Tuina Children Allergic Rhinitis Effective Rate RR 5 138/276 1.13(1.02-1.25) Guo2022 Chinese Herbal Bath Children Atopic Dermatitis Recurrence Rate RR 3 92/209 0.25(0.10-0.59) Xiao2024 Acupuncture Children Allergic Rhinitis Nasal Symptom Score RR 6 220/439 1.10(0.97-1.24) Relapse Rate RR 4 142/242 0.40(0.26-0.63) Zeng2024 Cang-Er-Zi-San Children Allergic Rhinitis Effective Rate RR 7 369/716 1.20(1.13-1.27) Recurrence Rate RR 6 277/554 0.22(0.12-0.42) Kuniyoshi2021 Neonatal Jaundice Children the Risk of Asthma OR 6 67524 + /2764834 1.37(1.22-1.54) the Risk of Allergic Rhinitis OR 3 3890 + /12213 1.46(1.24-1.72) Neonatal Phototherapy Children the Risk of Asthma OR 5 35597/2818940 1.24(1.11-1.38) Zhao2021 BCG Vaccination Children the Risk of Asthma OR 19 7918/80922 0.77(0.63-0.93) the Risk of Eczema OR 13 7504/72646 0.94(0.76-1.16) the Risk of Allergic Rhinitis OR 12 3765/69360 0.99(0.81-1.21) Li2024 PHF vs. CMF (Children aged2 y) the Risk of Allergic Rhinitis RR 4 849/1696 0.93(0.81-1.08) the Risk of Eczema 6 997/1993 0.82(0.65-1.02) the Risk of Asthma 3 835/1669 0.90(0.60-1.36) the Risk of Wheeze 3 162/324 0.56(0.27-1.18) Sensitization 3 667/1333 0.94(0.83-1.05) EHF vs. CMF (Children aged2 y) the Risk of Eczema RR 5 1879/3695 0.79(0.67-0.94) the Risk of Asthma 5 1879/3695 1.05(0.87-1.27) Sensitization 3 1234/2426 1.03(0.96-1.12) PHF vs. BM (Children aged<2 y) the Risk of Eczema RR 8 335/825 0.94(0.75-1.17) the Risk of Wheeze 4 216/625 1.61(1.11-2.31) the Risk of Food Allergy 3 195/467 1.53(0.95-2.46) Sensitization 3 168/453 1.00(0.74-1.35) EHF vs. BM (Children aged<2 y) the Risk of Cow’s Milk Allergy RR 3 1997/3312 0.71(0.42-1.20) the Risk of Eczema 6 432/1032 0.90(0.68-1.19) the Risk of Wheeze 4 363/920 1.64(1.26-2.14) the Risk of Food Allergy 3 264/768 1.02(0.64-1.62) Sensitization 6 2110/3498 0.91(0.71-1.18) Song2023 Milk and Dairy Consumption Children Asthma The Risk of Asthma OR 11 3644/63313 0.82(0.60-1.05) Keshavarz2024 Sugar-Sweetened Beverages Children Asthma the Risk of Asthma OR 12 17139/204026 1.28(1.15-1.42) Total Excess Free Fructose OR 3 1343 + /5147 2.73(1.30-5.73) 100% Fruit Juice OR 4 304 + /15286 1.43(0.91-2.23) Wei2019 Probiotic (Pregnancy or Infancy) Children the Risk of Asthma RR 13 2008/4021 0.94(0.82-1.09) the Risk of Wheeze RR 12 1258/2521 0.97(0.88-1.06) Luo2024 Probiotic (Pregnancy or Infancy) Children Allergic Rhinitis the Risk of Allergic Rhinitis OR 14 1800/3501 0.90(0.74-1.08) Jiang2024 Probiotic (Pregnancy or Infancy) Children the Risk of Food Allergy RR 5 708/1382 0.79(0.63-0.99) the Risk of Cow’s Milk Allergy RR 4 503/992 0.51(0.29-0.88) the Risk of Egg Allergy RR 3 443/883 0.57(0.39-0.84) Tolerance Towards Food RR 3 231/453 1.39(0.97-1.99) Probiotic (Infancy) the Risk of Food Allergy RR 9 1028/2080 1.08(0.94-1.25) the Risk of Cow’s Milk Allergy RR 5 422/836 0.69(0.49-0.96) the Risk of Egg Allergy RR 4 464/906 1.32(0.91-1.93) the Risk of Peanut Allergy RR 3 224/424 1.64(0.97-2.78) Sun2021 Probiotic (Pregnancy or Infancy) Children the Risk of Eczema OR 14 2014/4011 0.59(0.45-0.78) the Risk of Asthma OR 11 1599/3208 0.88(0.69-1.10) the Risk of Rhinitis OR 4 600/1214 0.83(0.55-1.24) the Risk of Wheeze OR 6 991/1922 0.82(0.67-1.01) Sensation OR 5 595/1174 0.99(0.75-1.30) Husein-ElAhmed2022 Probiotic (Infancy) Children Atopic Dermatitis Incidence of Atopic Dermatitis OR 17 1404/2844 0.78(0.64-0.94) Tan2021 Lactobacillus rhamnosus GG Children Oral Tolerance Rate RR 5 173/565 2.22(1.86-2.66) Lang2023 Omalizumab Children Allergic (IgE-Mediated) Asthma Effective Rate RR 4 686/1090 1.24(1.09-1.41) Azizpour2018 Overweight/ Obesity Children Children the Risk of Asthma OR 11 381/1490 1.64(1.13-2.38) 14 534/2413 1.92(1.39-2.65) Lambert2017 Residential Greenness Children and Adolescents the Risk of Asthma OR 3 8909/108381 1.01(0.93-1.09) Han2021 Traffic-related NO 2 Children the Risk of Asthma OR 4 2572/29442 1.21(1.12-1.31) Traffic-related TVOCs: the Risk of Asthma OR 2 190 + /30573 1.06(1.03-1.10) Lin2020 PM 2.5 Children Allergic Rhinitis the Prevalence of Allergic Rhinitis OR 9 11250 + /69705 1.09(1.01-1.17) PM 10 OR 15 21857/161141 1.06(1.02-1.11) Lau2023 Active Smoking (Pregnancy) Children the Risk of Eczema RR 17 19243/136083 0.92(0.84-1.00) Passive Smoking (Pregnancy) RR 5 1695/20641 1.04(0.85-1.28) Keleb2024 Pesticide Exposure Children the Risk of Asthma OR 28 8250 + /89532 1.24(1.14-1.35) the Risk of Wheeze OR 15 9045 + /41653 1.34(1.14-1.57) the Risk of Respiratory Tract Infection OR 9 1126/11618 1.79(1.45-2.21) Wang2022 Mercury Exposure Children Incidence of Asthma OR 4 1070/15622 1.13(0.87-1.45) Incidence of Atopic Dermatitis OR 3 455/1616 1.20(0.90-1.60) Incidence of Eczema OR 5 1512/8351 1.02(0.94-1.11) Incidence of Wheeze OR 6 1247 + /15219 1.01(0.93-1.10) Lead Exposure Incidence of Asthma OR 10 2392 + /30587 1.07(0.89-1.29) Incidence of Atopic Dermatitis OR 3 265/1485 1.58(0.79-3.18) Incidence of Eczema OR 4 1541/7359 1.04(0.94-1.14) Incidence of Wheeze OR 3 319 + /7221 1.00(0.93-1.07) Beckhaus2015 Vitamin E(Pregnancy) Children the Risk of Wheeze OR 5 559/4906 0.54(0.41-0.71) Zinc (Pregnancy) the Risk of Wheeze OR 3 194/2353 0.57(0.40-0.81) Zhu2016 Infection (Pregnancy) Children the Risk of Asthma OR 8 64977/1048473 1.55(1.24-1.92) the Risk of Eczema OR 3 1847/7388 1.36(1.13-1.64) Ai2024 Maternal Stress Children the Risk of Atopic Dermatitis OR 10 3974/72831 1.29(1.09-1.51) Maternal Distress OR 3 2786/20296 1.26(1.13-1.41) Maternal Anxiety (Pregnancy) OR 7 604/19553 1.40(1.24-1.59) Depression (Prenatal) OR 6 720/19311 1.21(1.09-1.33) Depression (Postnatal) OR 3 433/21222 1.07(0.86-1.33) Lai2018 Acid-Suppressive Drugs (Pregnancy) Children the Risk of Asthma RR 7 18932/1306247 1.31(1.15-1.59) Yan2020 PM 2.5 (Prenatal) Children the Risk of Asthma OR 9 156712/1096646 1.06(1.02-1.11) Conlan2020 Pre-Eclampsia Children the Risk of Asthma OR 7 1776/1991937 1.14(1.04-1.26) Hypertensive Disorders of Pregnancy (HDP) OR 4 770 + /256286 1.02(0.96-1.09) Huang2023 Gestational Diabetes Mellitus (GDM) Children the Risk of Asthma RR 7 62231/826891 1.22(1.07-1.39) Bärebring2022 Long Chain Omega-3 Fatty Acids (Pregnancy) Children the Risk of asthma RR 7 511/2966 0.62(0.34-0.91) the Risk of eczema RR 5 464/1610 0.86(0.50-1.22) the Risk of Food Allergy RR 4 64/1018 0.63(0.06-1.20) sensitization RR 4 396/1526 0.82(0.51-1.14) Malmir2021 Fish Consumption (Pregnancy) Children the Risk of Asthma RR 8 1618 + /42453 0.99(0.89-1.11) the Risk of wheeze RR 10 2929 + /45777 0.97(0.96-0.99) the Risk of eczema RR 11 2557 + /20781 0.93(0.84-1.03) the Risk of food allergy RR 5 459 + /13157 0.75(0.64-0.88) Cait2022 Antibiotic (Pregnancy) Children the Risk of Dermatitis RR 5 8608/27135 1.28(1.06-1.53) the Risk of Allergic Rhinitis RR 3 1155/25872 1.13(1.02-1.25) the Risk of Wheeze RR 9 9820 + /49986 1.51(1.17-1.94) the Risk of Asthma RR 20 137547 + /2773760 1.28(1.22-1.34) Li2022 Smoke Exposure (Prenatal) Children the Risk of Allergic Rhinitis OR 6 2243 + /22223 1.12(1.04-1.21) Smoke Exposure (Postnatal) the Risk of Allergic Rhinitis OR 7 20505 + /235582 1.19(1.03-1.39) Baranska2023 Paracetamol (Pregnancy) Children the Risk of Asthma OR 10 30 284/259057 1.34(1.22-1.48) the Risk of Wheeze OR 8 5198/21816 1.31(1.12-1.54) Jia2024 Depression (Postnatal) Children the Risk of Asthma RR 11 89645/852422 1.24(1.19-1.30) Pacheco-González2018 Vitamin D(Pregnancy) Children the Risk of Respiratory Tract Infections OR 13 2524 + /8685 0.64(0.47-0.87) the Risk of Wheeze OR 12 7666 + /53236 0.89(0.76-1.04) the Risk of Asthma OR 12 7870 + /62339 0.91(0.78-1.06) the Risk of Eczema OR 8 3947 + /12968 1.02(0.89-1.16) Sensitization OR 9 1509 + /11322 1.00(0.95-1.06) allergic rhinitis OR 5 1614/37955 0.99(0.84-1.16) Hoang2025 Elective Cesarean Delivery vs. Vaginal Delivery Children the Risk of Allergic Rhinitis OR 4 26003/1105795 1.15(1.04-1.26) Emergency Cesarean Delivery vs. Vaginal Delivery OR 4 24905/1103142 1.13(1.07-1.19) Non-Microbiota-Exposed Delivery vs. Microbiota-Exposed Delivery OR 3 5356/49281 1.25(0.88-1.77) Mebrahtu2015 Normal(≥2.5kg) vs. Low(<2.5kg) Birthweight Children the Risk of Wheeze OR 20 145421/810852 1.60(1.39-1.85) Normal (2.5-4.0kg) vs. Low(4 kg) Birthweight OR 10 44988/781928 1.02(0.99-1.04) Liu2023 Cesarean Section Children the Risk of Allergic Rhinitis OR 22 44724 + /1471374 1.19(1.12-1.27) Zhong2023 Cesarean Section Children the Risk of Asthma OR 35 138791 + /7053446 1.18(1.13-1.23) + Contain missing values. Abbreviations: CI=confidence interval; RR=Risk Ratio; OR=Odds Ratio; HR=Hazard Ratio; LRTI: Lower Respiratory Tract Infection; ISGA: Investigator Static Global Assessment; SPS: Severity of Pruritus Scale; BCG: Bacille Calmette Guerin; PHF: Partially Hydrolyzed Formula; CMF: Cow’s Milk Formula; EHF: Extensively Hydrolyzed Formula; BM: Breast Milk; TVOCs: Total Volatile Organic Pollutants; PM: Particulate Matter Table 2. Characteristics of the meta-analyses in the included systematic reviews (based on continuous data) Li2022 Vitamin D Children Atopic Dermatitis EASI or SCORAD SMD 8 242/483 -0.50(-0.87–0.12) Fedora2024 Vitamin D Children Asthma FEV1 SMD 4 156/318 -0.23(-0.46–0.01) Yang2023 Montelukast Sodium Children Cough Variant Asthma FEV1 SMD 16 751/1494 1.74(1.09-2.40) PEF SMD 15 703/1398 1.69(1.09-2.30) FVC SMD 9 459/900 1.67(0.94-2.39) FEV1/FVC SMD 6 327/646 1.84(0.41-3.28) TNF-α SMD 5 210/418 -2.38(-3.22–1.55) IL-4 SMD 7 310/620 -2.65(-3.26–2.04) IgE SMD 5 240/480 -2.98(-3.24–2.72) Zhou2021 Salmeterol/ Fluticasone Children and Adolescents Asthma PEF% pred MD 8 119/238 5.45(1.57-9.34) Li2019 Hypertonic Saline Nasal Children Allergic Rhinitis Nasal Symptom Scores MD 4 129/258 1.82(0.35-3.30) Fu2022 Pediatric Tuina Children Allergic Rhinitis Nasal Congestion Symptom MD 3 90/180 -0.46(-0.71–0.21) Nasal Itching Symptom MD 3 90/180 -0.32(-0.52–0.12) Runny Nose MD 3 90/180 -0.43(-0.62–0.23) Sneezing Symptom MD 3 90/180 -0.17(-0.38-0.03) Turbinate Swelling MD 3 90/180 -0.26(-0.48–0.04) Nasal Mucosal Swelling MD 3 90/180 -0.09(-0.30-0.13) Guo2022 Chinese Herbal Bath Children Atopic Dermatitis SCORAD SMD 5 290/570 -0.77(-0.99–0.55) Xiao2024 Acupuncture Children Allergic Rhinitis IgE MD 4 187/373 51.94(22.24-81.65) Luo2024 Probiotics (Pregnancy or Infancy) Children Allergic Rhinitis Nasal Symptom Scores SMD 6 438/750 -2.27(-3.26–1.29) Husein-ElAhmed2023 Lactobacillus rhamnosus Children Atopic Dermatitis SCORAD MD 11 351/677 -1.85(-4.61-0.90) Lactobacillus paracasei MD 4 175/354 -2.79(-4.74–0.84) Pan2021 Azithromycin Childhood Asthma FEV1/FVC MD 3 112/224 10.24(6.44-14.03) Penagos2013 SLIT Children 3 to 18 Years Asthma Asthma Symptom Scores SMD 9 232/441 -1.14(-2.1–0.18) Asthma Medication Score SMD 7 192/366 -1.63(-2.83–0.44) Yang2018 SLIT Children Allergic Conjunctivitis Ocular Symptom Scores SMD 13 573/1156 -0.21(-0.41–0.01) Chen2020 SLIT Children Perennial Rhinitis Nasal Symptoms Scores SMD 16 863/1736 -1.73(-2.62–0.84) Nasal Medication scores SMD 11 664/1336 -1.21(-1.75–0.68) Yang2023 SLIT vs SCIT Children Allergic Rhinitis Nasal Symptoms Scores SMD 3 125/332 0.41(-0.46-1.28) Zheng2023 SCIT Asthmatic Children with Allergy to House Dust Mite Asthma Symptom Scores SMD 12 368/737 -1.19(-1.87–0.50) Asthma Medication Scores SMD 12 349/673 -1.04(-1.54–0.54) PEF MD 10 361/728 2.99(0.09-5.90) MMEF MD 4 96/191 4.67(-2.03-11.37) Nonspecific Bronchial Provocation Test SMD 5 151/301 0.21(-0.02-0.44) Allergen-Specific Bronchial Provocation Test SMD 3 50/75 0.90(0.36-1.44) Chang2016 Synbiotics Children Atopic Dermatitis SCORAD WMD 6 166/344 -6.56 (-11.43–1.68) Chen2022 Probiotics Children and Adolescents Allergic Airway Diseases PRQLQs SMD 4 142/243 -2.57(-4.66–0.48) Ocular Symptom Score MD 3 189/339 -1.75(-1.88–1.62) IgE SMD 4 172/345 0.03(-0.19-0.24) Eosinophils SMD 3 97/189 0.10(-0.29-0.49) Fijan2023 Single-Strain Probiotic Lactobacilli Children Atopic Dermatitis SCORAD MD 14 574/1124 -4.50(-7.50–1.49) Wang2022 Copper Exposure Children Incidence of Asthma SMD 4 NA/301 1.50(0.13-2.86) Incidence of Atopic Dermatitis SMD 3 NA/423 -0.22(-1.00-0.55) Mercury Exposure Incidence of Atopic Dermatitis SMD 3 NA/813 0.45(-0.23-1.13) Lead Exposure Incidence of Asthma SMD 5 NA/2956 0.35(-0.76-1.47) Incidence of Atopic Dermatitis SMD 3 NA/706 1.96(-0.44-4.36) Pacheco-González2018 Vitamin D(Pregnancy) Children FEV z-scores weighted beta coefficients 4 259 + /5518 0.07(-0.01-0.15) FVC z-scores 4 259 + /5518 0.05(-0.03-0.13) + Contain missing values; NA: Not Available. Abbreviations: CI=confidence interval; MD=mean difference; WMD=weighted mean difference; SMD=standardized mean difference; EASI: Eczema Area and Severity Index; SCORAD: Scoring Atopic Dermatitis; FEV1: Forced Expiratory Volume in First Second; PEF: Peak Expiratory Flow; FVC: Forced Vital Capacity; TNF-α: Tumor Necrosis Factor-α; IL-4: Interleukin-4; SLIT: Sublingual Immunotherapy; SCIT: Subcutaneous Immunotherapy; MMEF: Maximum Mid-Expiratory Flow; PRQLQs: Pediatric Rhino-conjunctivitis Quality of Life Questionnaires. Table 3 Evidence grading results based on the results of all analyses of the included systematic reviews and meta-analyses based on binary data Associations supported by strong evidences (3) Kuniyoshi et al , 2021 Neonatal Jaundice and the Higher Risk of Asthma in Children +++ + + + - + + - Keleb et al , 2024 Pesticide Exposure and the Higher Risk of Respiratory Tract Infection in Children +++ + + + - + + - Jia et al , 2024 Depression (Postnatal) and the Higher Risk of Asthma in Children +++ + + + - + + - Associations supported by highly suggestive evidences (3) Song et al , 2022 Acid Suppressants and the Higher Risk of Asthma in Children +++ + + - - + + - Mebrahtu et al , 2015 Normal(≥2.5kg) vs. Low(<2.5kg) Birthweight and the Higher Risk of Wheeze in Children +++ + + - - + + - Liu et al , 2023 Cesarean Section and the Higher Risk of Allergic Rhinitis in Children +++ + + - + + + - Associations supported by suggestive evidences (8) Han et al , 2021 Traffic-related NO 2 and the Higher Risk of Asthma in Children +++ + + + + + + + Ai et al , 2024 Maternal Stress and the Higher Risk of Atopic Dermatitis +++ + + + - + - + Lai et al , 2018 Acid-Suppressive Drugs (Pregnancy) and the Higher Risk of Asthma in Children +++ + + - - + + - Conlan et al , 2020 Pre-Eclampsia and the Higher Risk of Asthma in Children +++ + + + - + + + Cait et al , 2022 Antibiotic (Pregnancy) and the Higher Risk of Wheeze in Children +++ + + - - + + - Cait et al , 2022 Antibiotic (Pregnancy) and the Higher Risk of Asthma in Children +++ + + - + + + - Baranska et al , 2023 Paracetamol (Pregnancy) and the Higher Risk of Wheeze in Children ++ + + - - + + - Hoang et al , 2025 Emergency Cesarean Delivery vs. Vaginal Delivery and the Higher Risk of Allergic Rhinitis in Children +++ + + + - + + - Associations supported by weak evidences (56) You et al , 2024 Crisaborole and the Higher ISGA Success in Children +++ + + - + + + + You et al , 2024 Crisaborole and the Higher SPS in Children + + + - - + + - Yang et al , 2023 Montelukast Sodium and the Higher Effective Rate in Children +++ - + + + + + - Xu et al , 2021 Ipratropium Bromide and Salbutamol and the Lower Risk of Hospital Admission in Children and Adolescents ++ - + + + + + - Li et al , 2019 Hypertonic Saline Nasal and the Lower Rescue Antihistamine Use Rates in Children + - - + - + + - Papamichael et al , 2018 Long Chain Omega-3 Fatty Acids and the Lower Incidence of Asthma in Children + + + + - - + + Fu et al , 2022 Pediatric Tuina and The Higher Effective Rate in Children + - + + - + - - Guo et al, 2022 Chinese Herbal Bath and The Lower Recurrence Rate in Children + - + + - + + - Xiao et al , 2024 Acupuncture and the Lower Relapse Rate in Children ++ - + + - + + - Xiao et al , 2024 Cang-Er-Zi-San and the Higher Effective Rate in Children +++ - + - - + + - Xiao et al , 2024 Cang-Er-Zi-San and the Lower Recurrence Rate in Children +++ - + + - + + - Kuniyoshi et al , 2021 Neonatal Phototherapy and the Higher Risk of Asthma in Children +++ + + + - + + - Zhao et al , 2021 BCG Vaccination and the Lower Risk of Asthma in Children + + + - + + + - Li et al , 2024 PHF vs. CMF (Children aged<2 y) and the Lower Risk of Eczema in Children ++ - + + + + + - Li et al , 2024 PHF vs. CMF (Children aged<2 y) and the Lower Risk of Wheeze in Children + - + + - + + - Li et al , 2024 EHF vs. CMF (Children aged2 y) and the Lower Risk of Eczema in Children ++ + + + - + + - Li et al , 2024 PHF vs. BM (Children aged<2 y) and the Higher Risk of Wheeze in Children + - + + + + + - Li et al , 2024 EHF vs. BM (Children aged<2 y) and the Higher Risk of Wheeze in Children + - + + - + + - Keshavarz et al , 2024 Sugar-Sweetened Beverages and the Higher Risk of Asthma in Children +++ + + - + + + + Keshavarz et al , 2024 Total Excess Free Fructose and the Higher Risk of Asthma in Children ++ + + - - - + - Jiang et al , 2024 Probiotic (Pregnancy or Infancy) and the Lower Risk of Food Allergy in Children + - + + - + - - Jiang et al , 2024 Probiotic (Pregnancy or Infancy) and the Lower Risk of Egg Allergy in Children + - + + - + - - Sun et al , 2021 Probiotic (Pregnancy or Infancy) and the Lower Risk of Eczema in Children ++ + + - - + + + Tan et al , 2021 Lactobacillus rhamnosus GG and the Higher Oral Tolerance Rate in Children +++ - + + - + + - Husein-ElAhmed et al, 2022 Probiotic (Infancy) and the Lower Incidence in Children + - + - + + - - Jiang et al, 2024 Probiotic (Infancy) and the Lower Risk of Cow’s Milk Allergy in Children + - + + - + - - Lang et al , 2023 Omalizumab and the Higher Effective Rate in Children +++ - + - + + + - Azizpour et al , 2018 Overweight and the Higher Risk of Asthma in Children ++ - + - + + - + Azizpour et al , 2018 Obesity and the Higher Risk of Asthma in Children ++ - + - + + + + Han et al , 2021 Traffic-related TVOCs and the Higher Risk of Asthma in Children ++ - + + + + - - Lin et al , 2020 PM 2.5 and the Higher Prevalence of Allergic Rhinitis in Children + + + - + + - + Lin et al , 2020 PM 10 and the Higher Prevalence of Allergic Rhinitis in Children + + + - + + - + Lau et al , 2023 Active Smoking (Pregnancy) and the Lower Risk of Eczema in Children + + + + - + - - Keleb et al , 2024 Pesticide Exposure and the Higher Risk of Asthma in Children ++ + + - + + + + Keleb et al , 2024 Pesticide Exposure and the Higher Risk of Wheeze in Children ++ + + - + + + + Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Lower Risk of Wheeze in Children + + + - + + - - Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Lower Risk of RTI in Children ++ + + - + + - + Beckhaus et al , 2015 Vitamin E(Pregnancy) and the Lower Risk of Wheeze in Children ++ - + + + + - - Beckhaus et al , 2015 Zinc (Pregnancy) and the Lower Risk of Wheeze in Children + - + + - - - - Zhu et al , 2016 Infection (Pregnancy) and the Higher Risk of Asthma in Children ++ + + - - + + - Zhu et al , 2016 Infection (Pregnancy) and the Higher Risk of Eczema in Children ++ + + + - + - - Ai et al , 2024 Maternal Stress and the Higher Risk of Atopic Dermatitis in Children ++ + + - - + - - Ai et al , 2024 Maternal Anxiety (Pregnancy) and the Higher Risk of Atopic Dermatitis in Children + - + + - + + - Ai et al , 2024 Depression (Prenatal) and the Higher Risk of Atopic Dermatitis in Children ++ - + + - + + - Yan et al , 2020 PM 2.5 (Prenatal) and the Higher Risk of Asthma in Children + + + - - + - + Huang et al , 2023 Gestational Diabetes Mellitus and the Higher Risk of Asthma in Children + + + - - + - - Bärebring et al , 2022 Long Chain n-3 Fatty Acids (Pregnancy) and the Lower Risk of asthma in Children + - + + - + - - Cait et al , 2022 Antibiotic (Pregnancy) and the Higher Risk of Dermatitis in Children ++ + + - + + + - Cait et al, 2022 Antibiotic (Pregnancy) and the Higher Risk of Allergic Rhinitis in Children + + - + + + + - Li et al , 2022 Smoke Exposure (Prenatal) and the Higher Risk of Allergic Rhinitis in Children + + - + + + - - Li et al , 2022 Smoke Exposure (Postnatal) and the Higher Risk of Allergic Rhinitis in Children + + - - + + - - Baranska et al , 2023 Paracetamol (Pregnancy) and the Higher Risk of Asthma in Children +++ + - - + + - - Hoang et al , 2025 Elective Cesarean Delivery vs. Vaginal Delivery and the Higher Risk of Allergic Rhinitis in Children ++ + - + + + + - Mebrahtu et al , 2015 Normal (2.5-4.0kg) vs. Low(<2.5kg) Birthweight and the Higher Risk of Wheeze in Children + + - - + + - - Zhong et al , 2023 Cesarean Section and the Higher Risk of Asthma in Children + + - - + + - - Associations supported by not suggestive evidences (58) Li et al , 2022 Vitamin D and the Lower Risk of Asthma in Children - - - - - + - - Luo et al , 2021 Vitamin D (Pregnancy or Infancy) and the Lower Risk of Allergic Rhinitis in Children - - - + - + - - Luo et al , 2021 Vitamin D (Pregnancy or Infancy) and the Lower Risk of LRTI in Children - - - + - + - - Song et al , 2022 Acid Suppressants and the Higher Risk of Food Allergy in Children - + - - + + - - Xiao et al , 2024 Acupuncture and the Higher Nasal Symptom Score in Children + - - + + + - - Kuniyoshi et al , 2021 Neonatal Jaundice and the Higher Risk of Allergic Rhinitis in Children + + - - - + - - Zhao et al , 2021 BCG Vaccination and the Lower Risk of Eczema in Children + + - - + + - - Zhao et al , 2021 BCG Vaccination and the Lower Risk of Allergic Rhinitis in Children + + - - - + - - Li et al , 2024 PHF vs. CMF (Children aged2 y) and the Lower Risk of Allergic Rhinitis in Children - - - + + + - - Li et al , 2024 PHF vs. CMF (Children aged>2 y) and the Lower Risk of Eczema in Children - - - + - + - - Li et al , 2024 PHF vs. CMF (Children aged>2 y) and the Lower Risk of Asthma in Children - - - - + + - - Li et al , 2024 PHF vs. CMF (Children aged>2 y) and the Lower Risk of Wheeze in Children - - - + - + - - Li et al ,2024 PHF vs. CMF (Children aged>2 y) and the Lower Sensitization in Children - - - + + + - - Li et al , 2024 EHF vs. CMF (Children aged<2 y) and the Lower Risk of Eczema in Children - - - - - + - - Li et al , 2024 EHF vs. CMF (Children aged2 y) and the Higher Risk of Asthma in Children - - - + - + - - Li et al , 2024 EHF vs. CMF (Children aged>2 y) and the Higher Sensitization in Children - + - + + + - - Li et al , 2024 PHF vs. BM (Children aged<2 y) and the Lower Risk of Eczema in Children - - - + - + - - Li et al , 2024 PHF vs. BM (Children aged<2 y) and the Higher Risk of Food Allergy in Children - - - + + + - - Li et al , 2024 PHF vs. BM (Children aged<2 y) and the Higher Sensitization in Children - - - + - + - - Li et al , 2024 EHF vs. BM (Children aged<2 y) and the Lower Risk of Cow’s Milk Allergy in Children - - - + + + - - Li et al , 2024 EHF vs. BM (Children aged<2 y) the Lower Risk of Eczema in Children - - - + - + - - Li et al , 2024 EHF vs. BM (Children aged<2 y) and the Higher Risk of Food Allergy in Children - - - + - + - - Li et al , 2024 EHF vs. BM (Children aged<2 y) and the Lower Sensitization in Children - + - + - + - - Song et al , 2023 Milk and Dairy Consumption and the Lower Risk of Asthma in Children - + - - + + - - Keshavarz et al , 2024 100% Fruit Juice and the Higher Risk of Asthma in Children - - - - - + - - Jiang et al , 2024 Probiotic (Pregnancy or Infancy) and the Lower Risk of Cow’s Milk Allergy in Children - - - + + + - - Jiang et al , 2024 Probiotic (Pregnancy or Infancy) and the Higher Tolerance Towards Food in Children - - - - - + - - Wei et al , 2019 Probiotic (Pregnancy or Infancy) and the Lower Risk of Asthma in Children - + - + - + - - Luo et al , 2024 Probiotic (Pregnancy or Infancy) and the Lower Risk of Allergic Rhinitis in Children - - - + + + - - Wei et al , 2019 Probiotic (Pregnancy or Infancy) and the Lower Risk of Wheeze in Children - + - + - + - - Sun et al , 2021 Probiotic (Pregnancy or Infancy) and the Lower Sensation in Children - - - + - + - - Jiang et al , 2024 Probiotic (Infancy) and the Higher Risk of Food Allergy in Children - - - + - + - - Jiang et al , 2024 Probiotic (Infancy) and the Higher Risk of Egg Allergy in Children - - - + - + - - Jiang et al , 2024 Probiotic (Infancy) and the Higher Risk of Peanut Allergy in Children - - - + - - - - Lambert et al , 2017 Residential Greenness and the Higher Risk of Asthma in Children - + - - - + - - Lau et al , 2023 Passive Smoking (Pregnancy) and the Higher Risk of Eczema in Children - + - - - + - - Wang et al , 2022 Mercury Exposure and the Higher Incidence in Children - + - - - + - - Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Lower Risk of Asthma in Children - + - + - + - - Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Lower Risk of Eczema in Children - + - + - + - - Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Higher Sensitization in Children - + - + - + - - Ai et al , 2024 Depression (Postnatal) and the Higher Risk of Atopic Dermatitis in Children - - - - - + - - Conlan et al , 2020 Hypertensive Disorders of and Pregnancy the Higher Risk of Asthma in Children - - - + - + - - Bärebring et al , 2022 Long Chain n-3 Fatty Acids (Pregnancy) and the Higher Risk of eczema in Children - - - - - + - - Bärebring et al , 2022 Long Chain n-3 Fatty Acids (Pregnancy) and the Lower Risk of Food Allergy in Children - - - + - + - - Bärebring et al , 2022 Long Chain n-3 Fatty Acids (Pregnancy) and the Lower Sensitization in Children - - - + - + - - Malmir et al , 2021 Fish Consumption (Pregnancy) and the Higher Risk of Asthma in Children - + - - - + - - Malmir et al , 2021 Fish Consumption (Pregnancy) and the Lower Risk of wheeze in Children - + - + - + - - Malmir et al , 2021 Fish Consumption (Pregnancy) and the Lower Risk of eczema in Children - + - + - + - - Malmir et al , 2021 Fish Consumption (Pregnancy) and the Lower Risk of food allergy in Children - - - - - + - - Wang et al , 2022 Lead Exposure and the Higher Incidence in Children - + - + - + - - Hoang et al , 2025 Non-Microbiota-Exposed Delivery vs. Microbiota-Exposed Delivery and the Higher Risk of Allergic Rhinitis in Children - + - - - + - - Mebrahtu et al , 2015 Normal (2.5-4.0kg) vs. High (>4 kg) Birthweight and the Higher Risk of Wheeze in Children - + - + - + - - Sun et al , 2021 Probiotic (Pregnancy or Infancy) and the Lower Risk of Asthma in Children - - - + - + - - Sun et al , 2021 Probiotic (Pregnancy or Infancy) and the Lower Risk of Rhinitis in Children - - - + - + - - Sun et al , 2021 Probiotic (Pregnancy or Infancy) and the Lower Risk of Wheeze in Children - - - + - + - - Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Lower incidence of allergic rhinitis in Children - + - + - + - - * P value calculated using random effects model: +++, P<10 -6 ; ++, P<10 -3 ; +, P0.05. For other items, += yes, -= no. Abbreviations: CI=confidence interval; RR=Risk Ratio; OR=Odds Ratio; HR=Hazard Ratio; LRTI: Lower Respiratory Tract Infection: ISGA: Investigator Static Global Assessment; SPS: Severity of Pruritus Scale; BCG: Bacille Calmette Guerin; PHF: Partially Hydrolyzed Formula; CMF: Cow’s Milk Formula; EHF: Extensively Hydrolyzed Formula; BM: Breast Milk; TVOCs: Total Volatile Organic Pollutants; PM: Particulate Matter. Table 4 Evidence grading results based on the results of all analyses of the included systematic reviews and meta-analyses based on continuous data Associations supported by weak evidences (33) Li et al , 2022 Vitamin D and the Lower EASI or SCORAD in Children ++ - - - - - - - Yang et al , 2023 Montelukast Sodium and the Higher FEV1 in Children +++ - - - + - + + Yang et al , 2023 Montelukast Sodium and the Higher PEF in Children +++ - - - + - + + Yang et al , 2023 Montelukast Sodium and the Higher FVC in Children +++ - - - + - + + Yang et al , 2023 Montelukast Sodium and the Higher FEV1/FVC in Children + - - - - - - + Yang et al , 2023 Montelukast Sodium and the Lower TNF-α in Children +++ - + - - - + - Yang et al , 2023 Montelukast Sodium and the Lower IL-4 in Children +++ - + - + + + - Yang et al , 2023 Montelukast Sodium and the Lower IgE in Children +++ - + + - + + - Zhou et al , 2021 Salmeterol/ Fluticasone and the Higher PEF% pred in Children and Adolescents ++ - + - - - - - Li et al , 2019 Hypertonic Saline Nasal and the Higher Nasal Symptom Scores in Children + - + - - - + - Pan et al , 2021 Azithromycin and the Higher FEV1/FVC in Childhood +++ - + + - - - - Yang et al , 2018 SLIT and the Lower Ocular Symptom Scores in Children + - + - - - - - Chen et al , 2020 SLIT and the Lower Nasal Symptoms Scores in Children +++ - + - - - - - Penagos et al , 2013 SLIT and the Lower Asthma Medication Score in Children ++ - - - + - - + Penagos et al , 2013 SLIT and the Lower Asthma Symptom Scores in Children + - + - - - - - Chen et al , 2020 SLIT and the Lower Nasal Medication scores in Children +++ - + - + - + - Zheng et al , 2023 SCIT and the Higher PEF in Children + - + - - - - - Zheng et al , 2023 SCIT and the Lower Asthma Symptom Scores in Children +++ - - - - - + + Zheng et al , 2023 SCIT and the Lower Asthma Medication Scores in Children +++ - - - - - - + Zheng et al , 2023 SCIT and the Higher Allergen-Specific Bronchial Provocation Test in Children ++ - - + - - + - Fu et al , 2022 Pediatric Tuina and the Higher Nasal Congestion Symptom in Children +++ - - + - - + - Fu et al , 2022 Pediatric Tuina and the Lower Nasal Itching Symptom in Children ++ - - + - - + - Fu et al , 2022 Pediatric Tuina and the Lower Runny Nose in Children +++ - + + - - + - Fu et al , 2022 Pediatric Tuina and the Lower Turbinate Swelling in Children + - - + - - - - Guo et al , 2022 Chinese Herbal Bath and the Lower SCORAD in Children +++ - + + - + + - Xiao et al , 2024 Acupuncture and the Higher IgE in Children +++ - - - - - - - Chang et al , 2016 Synbiotics and the Lower SCORAD in Children ++ - + - - - - - Luo et al , 2024 Probiotics (Pregnancy or Infancy) and the Lower Nasal Symptom Scores in Children +++ - + - - - - - Fijan et al , 2023 Single-Strain Probiotic Lactobacilli and the Lower SCORAD in Children ++ - + - + - - - Husein-ElAhmed et al , 2023 Lactobacillus paracasei and the Lower SCORAD in Children ++ - + - - - - - Wang et al , 2022 Copper Exposure and the Higher Incidence of Asthma in Children + - + - - - - - Chen et al , 2022 Probiotics and the Lower Ocular Symptom Score in Children and Adolescents ++ - + - - - + - Chen et al , 2022 Probiotics and the Lower PRQLQs in Children and Adolescents + - - - - - - + Associations supported by not suggestive evidences (15) Fedora et al , 2024 Vitamin D and the Lower FEV1 in Children - - - + - - - - Yang et al , 2023 SLIT vs SCIT and the Higher Nasal Symptoms Scores in Children - - + - - - - - Zheng et al , 2023 SCIT and the Higher MMEF in Children - - - + - - - - Zheng et al , 2023 SCIT and the Higher Nonspecific Bronchial Provocation Test in Children - - - + - - - - Fu et al , 2022 Pediatric Tuina and the Lower Sneezing Symptom in Children - - - + - - - - Fu et al , 2022 Pediatric Tuina and the Lower Nasal Mucosal Swelling in Children - - - - - - - + Husein-ElAhmed et al , 2023 Lactobacillus rhamnosus and the Lower SCORAD in Children - - - - - - - + Wang et al , 2022 Copper Exposure and the Lower Incidence of Atopic Dermatitis in Children - - - - - - - + Wang et al , 2022 Mercury Exposure and the Higher Incidence of Atopic Dermatitis in Children - - - - - - - + Wang et al , 2022 Lead Exposure and the Higher Incidence of Asthma in Children - - + - - - - - Wang et al , 2022 Lead Exposure and the Higher Incidence of Atopic Dermatitis in Children - - - - - - - + Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Higher FEV z-scores in Children - - - + - - - - Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Higher FVC z-scores in Children - - - + - - - - Chen et al , 2022 Probiotics and the Lower IgE in Children and Adolescents - - - - - - - + Chen et al , 2022 Probiotics and the Higher Eosinophils in Children and Adolescents - - - + - - - - * P value calculated using random effects model: +++, P<10 -6 ; ++, P<10 -3 ; +, P0.05. For other items, += yes, -= no. Abbreviations: CI=confidence interval; MD=mean difference; WMD=weighted mean difference; SMD=standardized mean difference; EASI: Eczema Area and Severity Index; SCORAD: Scoring Atopic Dermatitis; FEV1: Forced Expiratory Volume in First Second; PEF: Peak Expiratory Flow; FVC: Forced Vital Capacity; TNF-α: Tumor Necrosis Factor-α; IL-4: Interleukin-4; SLIT: Sublingual Immunotherapy; SCIT: Subcutaneous Immunotherapy; MMEF: Maximum Mid-Expiratory Flow; PRQLQs: Pediatric Rhino-conjunctivitis Quality of Life Questionnaires. Table 5 Evidence grading for continuous outcomes using an adjusted (pragmatic) sample size criterion (n ≥ 420.5) Associations supported by highly suggestive evidences (3) Yang et al , 2023 Montelukast Sodium and the Lower IL-4 in Children +++ + + - + + + - Yang et al , 2023 Montelukast Sodium and the Lower IgE in Children +++ + + + + + + - Guo et al , 2022 Chinese Herbal Bath and the Lower SCORAD in Children +++ + + + + + + - Associations supported by weak evidences (30) Li et al , 2022 Vitamin D and the Lower EASI or SCORAD in Children + + - - - - - - Yang et al , 2023 Montelukast Sodium and the Higher FEV1 in Children +++ + - - + - + + Yang et al , 2023 Montelukast Sodium and the Higher PEF in Children +++ + - - + - + + Yang et al , 2023 Montelukast Sodium and the Higher FVC in Children +++ + - - + - + + Yang et al , 2023 Montelukast Sodium and the Higher FEV1/FVC in Children + + - - + - - + Yang et al , 2023 Montelukast Sodium and the Lower TNF-α in Children +++ - + - + - + - Zhou et al , 2021 Salmeterol/ Fluticasone and the Higher PEF% pred in Children and Adolescents ++ - + - - - - - Li et al , 2019 Hypertonic Saline Nasal and the Higher Nasal Symptom Scores in Children + - + - - - + - Pan et al , 2021 Azithromycin and the Higher FEV1/FVC in Childhood +++ - + + - - - - Yang et al , 2018 SLIT and the Lower Ocular Symptom Scores in Children + + + - - - - - Chen et al , 2020 SLIT and the Lower Nasal Symptoms Scores in Children ++ + + - - - - - Penagos et al , 2013 SLIT and the Lower Asthma Medication Score in Children ++ - - - + - - + Penagos et al , 2013 SLIT and the Lower Asthma Symptom Scores in Children + + + - - - - - Chen et al , 2020 SLIT and the Lower Nasal Medication scores in Children +++ + + - + - + - Zheng et al , 2023 SCIT and the Higher PEF in Children + + + - + - - - Zheng et al , 2023 SCIT and the Lower Asthma Medication Scores in Children ++ + - - - - + + Zheng et al , 2023 SCIT and the Lower Asthma Symptom Scores in Children +++ + - - - - - + Zheng et al , 2023 SCIT and the Higher Allergen-Specific Bronchial Provocation Test in Children ++ - - + + - + + Fu et al , 2022 Pediatric Tuina and the Higher Nasal Congestion Symptom in Children ++ - + + - - + - Fu et al , 2022 Pediatric Tuina and the Lower Nasal Itching Symptom in Children ++ - - + - - + - Fu et al , 2022 Pediatric Tuina and the Lower Runny Nose in Children +++ - + + - - + - Fu et al , 2022 Pediatric Tuina and the Lower Turbinate Swelling in Children + - - + - - - - Xiao et al , 2024 Acupuncture and the Higher IgE in Children +++ - + - - - - - Chang et al , 2016 Synbiotics and the Lower SCORAD in Children ++ - + - - - - - Luo et al , 2024 Probiotics (Pregnancy or Infancy) and the Lower Nasal Symptom Scores in Children +++ + + - - - - - Fijan et al , 2023 Single-Strain Probiotic Lactobacilli and the Lower SCORAD in Children ++ + + - + - - - Husein-ElAhmed et al , 2023 Lactobacillus paracasei and the Lower SCORAD in Children ++ - + - - - - - Wang et al , 2022 Copper Exposure and the Higher Incidence of Asthma in Children + - + - - - - - Chen et al , 2022 Probiotics and the Lower Ocular Symptom Score in Children and Adolescents ++ - + - - - + - Chen et al , 2022 Probiotics and the Lower PRQLQs in Children and Adolescents + - - - + - - + Associations supported by not suggestive evidences (15) Fedora et al , 2024 Vitamin D and the Lower FEV1 in Children - - - + - - - - Yang et al , 2023 SLIT vs SCIT and the Higher Nasal Symptoms Scores in Children - - + - - - - - Zheng et al , 2023 SCIT and the Higher MMEF in Children - - - + - - - - Zheng et al , 2023 SCIT and the Higher Nonspecific Brochial Provocation Test in Children - - - + - - - - Fu et al , 2022 Pediatric Tuina and the Lower Sneezing Symptom in Children - - - + - - - - Fu et al , 2022 Pediatric Tuina and the Lower Nasal Mucosal Swelling in Children - - - - - - - + Husein-ElAhmed et al , 2023 Lactobacillus rhamnosus and the Lower SCORAD in Children - + - - - - - + Wang et al , 2022 Copper Exposure and the Lower Incidence of Atopic Dermatitis in Children - + - - - - - + Wang et al , 2022 Mercury Exposure and the Higher Incidence of Atopic Dermatitis in Children - + - - - - - + Wang et al , 2022 Lead Exposure and the Higher Incidence of Asthma in Children - + + - - - - - Wang et al , 2022 Lead Exposure and the Higher Incidence of Atopic Dermatitis in Children - + - - - - - + Pacheco-González et al , 2018 Vitamin D(Pregnancy) and the Higher FEV z-scores in Children - + - + - - - - Pacheco-González et al , 2018 Vitamin D (Pregnancy) and the Higher FVC z-scores in Children - + - + - - - - Chen et al , 2022 Probiotics and the Lower IgE in Children and Adolescents - - - - - - - + Chen et al , 2022 Probiotics and the Higher Eosinophils in Children and Adolescents - - - + - - - - *This table presents the evidence grading when the sample size criterion for continuous outcomes is relaxed from >20,000 to the median observed sample size (n ≥ 420.5), as an alternate, more pragmatic analysis. * P value calculated using random effects model: +++, P<10 -6 ; ++, P<10 -3 ; +, P0.05. For other items, += yes, -= no. Abbreviations: CI=confidence interval; MD=mean difference; WMD=weighted mean difference; SMD=standardized mean difference; EASI : Eczema Area and Severity Index; SCORAD: Scoring Atopic Dermatitis; FEV1: Forced Expiratory Volume in First Second; PEF: Peak Expiratory Flow; FVC: Forced Vital Capacity; TNF-α: Tumor Necrosis Factor-α; IL-4: Interleukin-4; SLIT: Sublingual Immunotherapy; SCIT: Subcutaneous Immunotherapy; MMEF: Maximum Mid-Expiratory Flow; PRQLQs: Pediatric Rhino-conjunctivitis Quality of Life Questionnaires. Information & Authors Information Version history V1 Version 1 05 January 2026 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Han Wang 0009-0009-6021-539X [email protected] The Second Hospital of Dalian Medical University View all articles by this author Qiuling Hu The Second Hospital of Dalian Medical University View all articles by this author Jian Li Shengjing Hospital of China Medical University View all articles by this author Kaining Chen The Second Hospital of Dalian Medical University View all articles by this author Xiaoxuan Qi The Second Hospital of Dalian Medical University View all articles by this author Rongxin Zhang The Second Hospital of Dalian Medical University View all articles by this author Xi Wang The Second Hospital of Dalian Medical University View all articles by this author Yongkun Wang The Second Hospital of Dalian Medical University View all articles by this author Yiwen Li Liaoyu Hospital of Dalian View all articles by this author Metrics & Citations Metrics Article Usage 147 views 108 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Han Wang, Qiuling Hu, Jian Li, et al. 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