Abstract
Objective
Adverse childhood experiences (ACEs) are associated with the development of asthma, but the link between the two remains controversial currently. This protocol describes a systematic review and meta-analysis to evaluate the association between different ACEs and asthma.
Methods
We will conduct a comprehensive search across PubMed, Embase, Cochrane Library, and Web of Science to identify research pertaining to the correlation between ACEs and asthma, spanning from the inception of these databases to April 30, 2025. The information primarily will encompass fundamental study attributes (such as lead author, publication year, geographical location, and study design) and essential demographic details (including sample size, gender distribution, and average age) of the study populations. The primary focus is on examining the relationship between ACEs and asthma, with the quality assessment of included case–control or cohort studies being conducted using the Newcastle–Ottawa Scale (NOS). The processes of literature screening, data extraction, and bias evaluation will be independently carried out in duplicate by two investigators. In instances where meta-analysis is not applicable, we will employ optimal methods for integrating evidence descriptively.
Discussion
This protocol will use meta-analysis to prove the relationship between different types of ACEs and asthma, hoping to improve the quality of life of children with ACEs and reduce the incidence of asthma.
Systematic review registration
PROSPERO CRD42024544950.
Supplementary Information
The online version contains supplementary material available at 10.1186/s13643-026-03079-z.
Keywords: Adverse childhood experiences, Asthma, Meta-analysis, Association
Introduction
Adverse childhood experiences (ACEs) will garner significant attention as a critical social issue that profoundly impacts the physical and mental well-being of adolescents [1, 2]. Children, as a vulnerable demographic, will be particularly prone to suffering from abuse, neglect, and adverse circumstances such as poverty, parental divorce, and various forms of family dysfunction originating from societal, educational, and familial sources [3, 4]. The prevalence of child abuse will be notably higher among adolescents compared to younger children, yet the incidence of reporting these cases will be substantially lower [5]. The Fourth National Survey of Child Abuse and Neglect Prevalence, conducted in the USA in 2019 by the US Department of Health and Human Services, reports that 21 out of every 1000 adolescents aged 12 to 14 will experience abuse, in contrast to 8.5 per 1000 among children aged 0 to 2. The survey, which includes children and adolescents from diverse socioeconomic and demographic backgrounds, tracks incidents of physical, emotional, and sexual abuse, as well as neglect. However, only about 8 out of every 1000 adolescents in this age bracket will be reported to Child Protective Services (CPS) for maltreatment. CPS is a nationwide system in the USA responsible for investigating reports of child abuse and neglect, and it categorizes maltreatment into physical abuse, emotional abuse, sexual abuse, and neglect [6–8]. This underreporting will stem from the perception that maltreatment is less detrimental to adolescents than to younger children.
ACEs will be linked to a range of adverse outcomes in adolescents, including depressed mood, anxiety, PTSD symptoms, risk-taking behaviors, early pregnancies, eating disorders, weight issues, substance use, treatment for sexually transmitted diseases, suicide attempts, and the need for mental health services [9–12]. Experiencing severe ACEs, such as abuse, bereavement, or neglect, during childhood is correlated with heightened morbidity and mortality [13]. Although the biological mechanisms connecting ACEs to health outcomes in later life will be complex, recent research suggests that immune system dysregulation may play a crucial role as an underlying biological pathway [14]. Several studies will investigate the impact of ACEs on the subsequent development of asthma [15, 16], but the relationship between ACEs and asthma remains contentious [17]. Therefore, we propose the first systematic review and meta-analysis protocol specifically based on case–control and cohort studies to explore the association between various ACEs and the incidence of asthma.
Materials and methods
The program will construct in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) guidelines [18] (Supplementary Material 1). This study will schedule end on April 30, 2025. This study is pre-registered with the International Prospective Register of Systematic Reviews (PROSPERO) under the registration number (Supplementary Material 2): CRD42024544950.
Inclusion/exclusion criteria
Inclusion criteria:
We will include studies involving children aged 0–18 years who were free of asthma at baseline. Eligible populations had to undergo assessment for ACEs using validated tools, such as the ACES Questionnaire or the World Health Organization (WHO) framework [19, 20]. Only studies that clearly defined the target population and confirmed the absence of asthma at baseline were included.
Exposure: The exposure group consisted of children with a documented history of ACEs. ACEs were defined using validated measurement tools and included physical, emotional, or sexual abuse; physical or emotional neglect; and household dysfunction such as domestic violence, parental substance abuse, parental mental illness, or incarceration of a household member. ACEs exposure occurring from birth to 18 years of age was considered, with particular emphasis on exposures during the first five years of life. Exposure had to be clearly measured and reported using reliable methods, including medical records, caregiver reports, or standardized questionnaires.
Control: The comparator group comprised children with no history of ACEs, defined as the absence of abuse, neglect, or household dysfunction according to the same validated tools used for exposure assessment. These children served as the reference group for evaluating the association between ACEs exposure and subsequent asthma development.
Outcome: The primary outcome is the diagnosis of asthma, confirmed by clinical criteria (physician diagnosis, spirometry, or ICD codes). Studies should provide data on the timing of asthma diagnosis relative to ACEs exposure. Asthma outcomes must be assessed at least 6 months after ACEs exposure to allow for meaningful assessment of the long-term impact of ACEs on asthma development. We will accept studies with varying follow-up durations, but study follow-up duration must be clearly specified, and the relationship between the timing of ACEs exposure and asthma outcome will be assessed in the analysis.
Study design: Case–control or cohort studies (prospective/retrospective).
Exclusion criteria:
Studies without a control group.
Case reports.
Non-primary research (reviews, editorials).
Studies focusing on adult populations (> 18 years).
Non-English publications or studies with inaccessible full text.
Studies where ACEs or asthma are self-reported without clinical validation.
Studies conflating ACEs with non-childhood adversities (adult trauma).
Literature retrieval
We will search PubMed, Embase, Cochrane Library, and Web of Science databases to identify research pertaining to the correlation between ACEs and asthma in case–control or cohort studies. The search will be conducted from database creation to April 30, 2025. The search will be performed using MeSH terms combined with free terms: adverse childhood experiences; asthma, and the specific search strategy is described in Supplementary Material 3.
Data collection and analysis
Study collection
Two authors (Liqiong Wang and Yungai Cheng) will independently screen the retrieved studies, excluding duplicates and those that do not meet inclusion criteria by reading titles and abstracts. They will review the full text of each study to select those that qualify. Any disagreements will be resolved through discussion with a third reviewer (Yuqi Wang). The entire study selection process will be illustrated in Fig. 1.
Fig. 1.
PRISMA 2020 flow diagram for new systematic reviews which included searches of databases and registers only. ∗Consider, if feasible to do so, reporting the number of records identified from each database or register searched (rather than the total number across all databases/registers). ∗∗If automation tools were used, indicate how many records were excluded by a human and how many were excluded by automation tools.
Data extraction
Data extraction from the included studies will be carried out independently by two reviewers (Liqiong Wang and Yungai Cheng) using a predefined data acquisition list. This list will capture basic information (author, title, journal, year, and country of publication), study design (including study size), and any conflicts of interest. If necessary, a third reviewer will double-check the data for consistency. If data is missing or incomplete, we will contact the study authors to obtain it. Studies without available data will be excluded.
Assessment of risk of bias
The risk of bias in the included studies will be evaluated independently by two investigators (Liqiong Wang and Yungai Cheng), and the results will be cross-checked. For cohort and case–control studies, the Newcastle Ottawa Scale (NOS) [21] will be used to assess quality. The NOS evaluates studies based on three dimensions: population selection, comparability, and exposure or outcome, with eight items totaling nine points. Scores range from 0 to 4 (low quality), 5 to 6 (moderate quality), and 7 to 9 (high quality). Studies scoring 0 to 4 will be excluded.
Measures of association
Statistical analyses will be performed using Stata 15.0. The first step will involve data standardization and transformation where necessary to ensure consistency in the measurement of outcomes across studies. A random effects model will be applied to estimate the pooled odds ratio (OR) and corresponding 95% confidence interval (CI) for the association between ACEs and asthma. This model is chosen due to anticipated heterogeneity in the included studies, which may arise from differences in study design, populations, and follow-up times.
Assessment of heterogeneity
Heterogeneity will be assessed using Cochrane’s Q test and the I2 statistic (with p > 0.05 for the Q statistic and I2 < 50% indicating statistical homogeneity). Due to potential variations in follow-up times among studies, meta-analyses will be conducted using a random effects model. Subgroup analyses will be performed to explore possible causes of heterogeneity. If heterogeneity exceeds 75%, a meta-analysis will not be performed, and a narrative, qualitative summary will be provided instead.
Quality of evidence
The revised evidence quality assessment will adopt the GRADE framework, specifically the methodology for prognostic studies proposed by Iorio et al. [22]. According to this framework, observational studies examining overall prognosis, including cohort and case–control studies, initially begin as high-quality evidence. The evidence quality may then be downgraded due to study limitations, inconsistency, indirectness, imprecision, or risk of bias. Conversely, it may be upgraded if studies demonstrate large or very large effects, a clear dose–response gradient, or plausible confounding that would reduce the observed effect. In this study, which investigates the association between adverse childhood experiences (ACEs) and asthma development, we will assign evidence quality grades to all included studies based on these criteria. Detailed justifications for any upgrading or downgrading decisions will be provided in the analysis.
Assessment of publication biases
For studies with more than ten included studies, publication bias will be assessed using funnel plots and Egger’s test. Asymmetry in the funnel plot indicates a higher likelihood of publication bias, which will be further evaluated using Egger’s test. A P value < 0.05 indicates the presence of publication bias, while a P value > 0.05 suggests otherwise. Further confirmation may be done using the trim-and-fill method.
Subgroup analysis
If data allows, subgroup analyses will be conducted to assess heterogeneity based on the following criteria:
Publication year: Studies will be categorized by their publication year (e.g., studies published before 2010 vs. those published after 2010) to assess temporal trends in the findings.
Country: Studies will be grouped by geographical region or country (North America, Europe, Asia) to examine potential regional variations in the results.
Study type: Subgroup analyses will consider different study designs, including cohort studies and case–control studies, to assess the robustness of the results across different methodologies.
Age: The analysis will be stratified by age groups (children, adults, elderly) to determine whether age influences the outcomes.
Gender: Data will be analyzed separately for males and females to explore any gender differences in the findings.
Types of ACEs: Given the study’s objective of evaluating associations between different types of ACEs and asthma, separate analyses will be conducted for each type of ACEs. This includes physical abuse; emotional abuse; neglect (physical and emotional); household dysfunction (parental mental illness, substance abuse, domestic violence, incarceration of household members).
- Asthma diagnosis method: Given that clinical diagnosis of asthma can vary in its accuracy and may be somewhat subjective, sensitivity analyses will be conducted based on different asthma outcome definitions:
- Physician diagnosis: Studies where asthma is diagnosed by a healthcare provider based on clinical evaluation.
- Spirometry-confirmed diagnosis: Studies that use spirometry (or other objective measures of lung function) to confirm the diagnosis of asthma.
- ICD code-based diagnosis: Studies where asthma is diagnosed using International Classification of Diseases (ICD) codes.
We will evaluate whether the type of asthma diagnosis influences the overall findings, as variations in diagnostic criteria may contribute to heterogeneity across studies.
These subgroup analyses will allow us to determine whether specific types of ACEs are more strongly associated with asthma outcomes, helping to refine our understanding of the unique impact of different childhood adversities.
Sensitivity analysis
Where possible, sensitivity analyses will be employed to determine how uncertain data assumptions affect the robustness of the combined results. High-risk studies will be included in the overall synthesis, but they will be excluded in sensitivity analyses to assess their impact on the robustness of the results. The specific impact of each article on the statistical analysis will be judged by sequentially excluding each study.
To ensure the reliability of the results, we will pre-specify the following sensitivity analyses:
Study risk and quality: Sensitivity analyses will also consider the inclusion of high-risk studies, which may have methodological limitations (poor study design, incomplete data). These high-risk studies will be included in the overall synthesis but excluded in sensitivity analyses to assess their potential impact on the robustness of the results.
Sensitivity analyses will also explore the impact of different study designs (case–control vs. cohort studies), as these may introduce varying degrees of bias or confounding. The results will be compared across these design types to assess the consistency of the findings.
These pre-specified sensitivity analyses will allow for a more thorough understanding of how different factors, such as asthma diagnosis method and study quality, may affect the overall conclusions of the meta-analysis.
Ethics and dissemination
This review does not require ethical approval as it does not infringe on individual rights. Results will be published in a peer-reviewed journal and disseminated through conferences.
Discussion
The current study will be the first to use meta-analysis to explore the effect of different ACEs on asthma. The results of this study will improve the quality of life of children with ACEs, improve prognosis, and can reduce the incidence of asthma in children with ACEs.
Some research indicates that traumatic stress during childhood substantially raises the likelihood of future asthma attacks. This finding differs from TIBOSCH et al. [23], which examined psychological traits of parents linked to asthma attacks and acute exacerbations but did not conclusively identify a heightened risk of asthma attacks. This discrepancy may be due to the wider array of ACEs considered in this review. Additionally, there is proof of interactions or “synergistic” effects between ACEs and physical environmental risk factors. When ACEs and environmental exposures are combined, there is a potential for increased sensitization and pro-inflammatory responses, which significantly heightens the risk of developing asthma. This phenomenon will be elucidated by the biological embedding of stress [24], the theory of nonstationary load [25], or body programming [26]. The observation that immune biomarkers consistently rise with parental stress, and that these elevated levels are strongly linked to asthma diagnoses, supports this suggestion. Research on prenatal stress exposure has yielded similar results, highlighting the relationship between maternal stress and disease susceptibility in offspring [27]. Wright [28] reviewed this “perinatal programming” effect, noting that chronic maternal stress induces placental secretion of corticotropin-releasing hormone. This triggers the release of adrenocorticotropin-releasing hormone (ARH), which activates the hypothalamic-pituitary-adrenocortical axis in the developing fetus, potentially leading to abnormal regulation or decreased glucocorticoid sensitivity. Empirical evidence links this process to atopic disorders such as asthma, eczema, and food allergies [29].
Recent findings bolster the expanding body of literature on biopsychosocial models of asthma development. Psychosocial stressors are recognized for activating the sympathetic nervous system and the hypothalamic-pituitary-adrenocortical axis, prompting the release of catecholamines and cortisol, which subsequently influence the expression and activity of various immune cells [27, 30]. While transient hormone increases offer protection, prolonged or excessive exposure may prove detrimental. Negative emotional states can disrupt the regulation of these axes, resulting in chronic under- or over-activity of this typically balanced system. It has been demonstrated that stress induces a shift in the immune response toward a T helper cell type 2 cytokine profile, leading to the recruitment of inflammatory cells, which can initiate or amplify the atopic inflammatory characteristics of asthma [31, 32]. Animal research has indicated that social stress can cause corticosteroid insensitivity and trigger mast cell degranulation, with these genes being implicated in many symptoms of atopic disorders like asthma. Multiple studies have demonstrated that stressful life events elevate the incidence of asthma [33, 34]. Maternal stress during prenatal and postnatal periods will be notably associated with childhood wheezing [35]. One study revealed that mothers who encountered stressful life events during pregnancy, such as divorce, bereavement, or job loss, were 1.71 times more likely to have children who developed asthma than those who did not [36]. Furthermore, a large population-based study of adults found that high-intensity life stress doubled the risk of developing asthma [37]. Besides exacerbating asthma, stress exposure also predicts a higher incidence of asthma in children.
Potential clinical and research implications
If a causal relationship between ACEs and asthma is confirmed, it would have significant implications for clinical practice. First, clinicians could identify high-risk children based on their ACE history and develop personalized prevention and treatment plans. This includes integrating mental health interventions, stress management techniques, and trauma-informed care into asthma treatment to help improve children’s immune function and mental health, thereby reducing asthma attack frequency. Additionally, clinical settings may introduce more interventions focused on alleviating psychological stress, thereby enhancing patients’ quality of life and prognosis.
In the research domain, confirming this causal relationship would drive deeper exploration of how ACEs influence asthma through immune responses and biological mechanisms. This would spur more interdisciplinary research, particularly in immunology, psychology, and public health, dedicated to uncovering the long-term effects of childhood trauma on the immune system. Future research may develop novel biomarkers for diagnosis and explore personalized treatment approaches based on ACEs’ histories. This could also prompt adjustments to public health policies, shifting greater emphasis toward social interventions that reduce childhood trauma, thereby decreasing asthma incidence and improving patient health outcomes.
Limitations of the study
Despite the strict inclusion criteria used in this study, these criteria may have led to selection bias, especially the exclusion of some studies with weak methodology or underreporting, which may affect the representation of the studies. Alternatively, reliance on published literature may lead to publication bias, especially for studies that do not publish negative or inconclusive results. Due to heterogeneity in the design, population characteristics, and follow-up time of different studies, the final statistical results may be affected. At the same time, although the New Castle–Ottawa scale was used for quality assessment, its subjectivity may affect the assessment results. Finally, this study only includes English literature, and the complete text of some literature cannot be obtained, which may lead to the lack of information, thus affecting the comprehensiveness of the study.
Supplementary Information
Acknowledgements
None.
Authors’ contributions
Liqiong Wang, Yungai Cheng, Yuqi Wang: manuscript preparation and data analysis; Yungai Cheng, Yuqi Wang: manuscript editing; Liqiong Wang: final approval.
Funding
The authors received no specific funding for this work.
Data availability
No datasets were generated or analyzed during the current study. All relevant data from this study will be made available upon study completion.
Declarations
Ethics approval and consent to participate
This meta-analysis does not involve human subjects. IRB review is not required.
Consent for publication
Not applicable.
Competing interests
None declared.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
References
- 1.Bhutta ZA, Bhavnani S, Betancourt TS, Tomlinson M, Patel V. Adverse childhood experiences and lifelong health. Nat Med. 2023;29(7):1639–48. [DOI] [PubMed] [Google Scholar]
- 2.Olsen EL, April-Sanders AK, Bird HR, Canino GJ, Duarte CS, Suglia SF. Adverse childhood experiences and sleep disturbances among Puerto Rican young adults. JAMA Netw Open. 2024;7(4):e247532. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Peterson C, Aslam MV, Niolon PH, Bacon S, Bellis MA, Mercy JA, et al. Economic burden of health conditions associated with adverse childhood experiences among US adults. JAMA Netw Open. 2023;6(12):e2346323. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Swedo EA, Aslam MV, Dahlberg LL, Niolon PH, Guinn AS, Simon TR, et al. Prevalence of adverse childhood experiences among U.S. adults - behavioral risk factor surveillance system, 2011-2020. MMWR Morb Mortal Wkly Rep. 2023;72(26):707–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Merrick MT, Ford DC, Ports KA, Guinn AS. Prevalence of adverse childhood experiences from the 2011-2014 behavioral risk factor surveillance system in 23 states. JAMA Pediatr. 2018;172(11):1038–44. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Briggs EC, Amaya-Jackson L, Putnam KT, Putnam FW. All adverse childhood experiences are not equal: the contribution of synergy to adverse childhood experience scores. Am Psychol. 2021;76(2):243–52. [DOI] [PubMed] [Google Scholar]
- 7.Lin L, Wang HH, Lu C, Chen W, Guo VY. Adverse childhood experiences and subsequent chronic diseases among middle-aged or older adults in China and associations with demographic and socioeconomic characteristics. JAMA Netw Open. 2021;4(10):e2130143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Satinsky EN, Kakuhikire B, Baguma C, Rasmussen JD, Ashaba S, Cooper-Vince CE, et al. Adverse childhood experiences, adult depression, and suicidal ideation in rural Uganda: a cross-sectional, population-based study. PLoS Med. 2021;18(5):e1003642. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Rehan ST, Fatima S, Imran L, Khan Z, Swed S, Nashwan AJ. Perinatal mental disorders associated with adverse childhood experiences in Asian countries; call to practice recommendations. Asian J Psychiatr. 2023;81:103410. [DOI] [PubMed] [Google Scholar]
- 10.Solberg MA, Blair LM, Schlegel EC, Kurzer J. Health disparities among sexual and gender minorities with adverse childhood experiences: insights from the 2021 behavioral risk factor surveillance system data. Am J Public Health. 2023;113(12):1343–51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Xiao W, Li S, Xu H, Zhang Y, Wei R, Tao F, et al. Population attributable fractions of adverse childhood experiences for emotional problems and self-harming behaviors among middle school students in China. Asian J Psychiatr. 2023;85:103621. [DOI] [PubMed] [Google Scholar]
- 12.Xiao W, Xu H, Yu W, Li S, Li R, Jin Z, et al. Comparison of adverse childhood experience analytic approaches and associations with emotional and behavioral problems: a nationwide study among Chinese middle school students. J Affect Disord. 2023;325:755–61. [DOI] [PubMed] [Google Scholar]
- 13.VanBronkhorst SB, Abraham E, Dambreville R, Ramos-Olazagasti MA, Wall M, Saunders DC, et al. Sociocultural risk and resilience in the context of adverse childhood experiences. JAMA Psychiat. 2024;81(4):406–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Zhang Z, Wang W, Yuan X, Wang X, Luo Y, Dou L, et al. Adverse childhood experiences and subsequent physical and mental health among young adults: results from six universities in China. Psychiatry Res. 2024;335:115832. [DOI] [PubMed] [Google Scholar]
- 15.Pape K, Cowell W, Sejbaek CS, Andersson NW, Svanes C, Kolstad HA, et al. Adverse childhood experiences and asthma: trajectories in a national cohort. Thorax. 2021;76(6):547–53. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Sun Q, Liu J, Yang Y, Chen Y, Liu D, Ye F, et al. Mediating role of depressive symptoms in the association between adverse childhood experiences and asthma. Child Abuse Negl. 2024;149:106662. [DOI] [PubMed] [Google Scholar]
- 17.Bochicchio L, Porsch L, Zollweg S, Matthews AK, Hughes TL. Health outcomes of sexual minority women who have experienced adverse childhood experiences: a scoping review. Trauma Violence Abuse. 2024;25(1):764–94. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. PLoS Med. 2009;6(7):e1000100. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Racine N, Killam T, Madigan S. Trauma-informed care as a universal precaution: beyond the adverse childhood experiences questionnaire. JAMA Pediatr. 2020;174(1):5–6. [DOI] [PubMed] [Google Scholar]
- 20.Romans S, Belaise C, Martin J, Morris E, Raffi A. Childhood abuse and later medical disorders in women. An epidemiological study. Psychother Psychosom. 2002;71(3):141–50. [DOI] [PubMed] [Google Scholar]
- 21.Stang A, Jonas S, Poole C. Case study in major quotation errors: a critical commentary on the Newcastle-Ottawa scale. Eur J Epidemiol. 2018;33(11):1025–31. [DOI] [PubMed] [Google Scholar]
- 22.Iorio A, Spencer FA, Falavigna M, Alba C, Lang E, Burnand B, et al. Use of GRADE for assessment of evidence about prognosis: rating confidence in estimates of event rates in broad categories of patients. BMJ. 2015;350:h870. [DOI] [PubMed] [Google Scholar]
- 23.Tibosch MM, Verhaak CM, Merkus PJ. Psychological characteristics associated with the onset and course of asthma in children and adolescents: a systematic review of longitudinal effects. Patient Educ Couns. 2011;82(1):11–9. [DOI] [PubMed] [Google Scholar]
- 24.Segerstrom SC, Miller GE. Psychological stress and the human immune system: a meta-analytic study of 30 years of inquiry. Psychol Bull. 2004;130(4):601–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Bahreinian S, Ball GD, Vander Leek TK, Colman I, McNeil BJ, Becker AB, et al. Allostatic load biomarkers and asthma in adolescents. Am J Respir Crit Care Med. 2013;187(2):144–52. [DOI] [PubMed] [Google Scholar]
- 26.Hyland ME, Jeffery AN, Wilkin TJ. A biological, latent variable model of health (EarlyBird 68). Brain Behav Immun. 2014;40:104–9. [DOI] [PubMed] [Google Scholar]
- 27.McBain RK, Levin JS, Matthews S, Qureshi N, Long D, Schickedanz AB, et al. The effect of adverse childhood experience training, screening, and response in primary care: a systematic review. EClinicalMedicine. 2023;65:102282. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Wright RJ. Stress and atopic disorders. J Allergy Clin Immunol. 2005;116(6):1301–6. [DOI] [PubMed] [Google Scholar]
- 29.Austin A, Herrick H, Proescholdbell S. Adverse childhood experiences related to poor adult health among lesbian, gay, and bisexual individuals. Am J Public Health. 2016;106(2):314–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Martinez A, Ye M, Hessler D, de la Rosa R, Benson M, Gilgoff R, et al. Adverse childhood experiences and related events are associated with asthma symptoms in children. Acad Pediatr. 2024;24(4):669–76. [DOI] [PubMed] [Google Scholar]
- 31.Ospina MB, Serrano-Lomelin JA, Amjad S, Hicks A, Giesbrecht GF. Latent factors of adverse childhood experiences and adult-onset asthma. J Dev Orig Health Dis. 2021;12(1):50–7. [DOI] [PubMed] [Google Scholar]
- 32.Panisch LS, Baiden P, Findley E, Jahan N, LaBrenz CA. Adverse childhood experiences and risk factors associated with asthma among children in the United States: the intersection of sex and race/ethnicity. J Asthma. 2022;59(6):1122–30. [DOI] [PubMed] [Google Scholar]
- 33.Saygideger Y, Özkan H, Baydar O, Yilmaz O. Adulthood asthma as a consequence of childhood adversity: a systematic review of epigenetically affected genes. J Dev Orig Health Dis. 2022;13(6):674–82. [DOI] [PubMed] [Google Scholar]
- 34.Shonkoff JP, Boyce WT, Levitt P, Martinez FD, McEwen B. Leveraging the Biology of Adversity and Resilience to Transform Pediatric Practice. Pediatrics. 2021;147(2):e20193845. [DOI] [PubMed]
- 35.Calthorpe LM, Pantell MS. Differences in the prevalence of childhood adversity by geography in the 2017-18 National Survey of Children’s Health. Child Abuse Negl. 2021;111:104804. [DOI] [PubMed] [Google Scholar]
- 36.de Marco R, Pesce G, Girardi P, Marchetti P, Rava M, Ricci P, et al. Foetal exposure to maternal stressful events increases the risk of having asthma and atopic diseases in childhood. Pediatr Allergy Immunol. 2012;23(8):724–9. [DOI] [PubMed] [Google Scholar]
- 37.Sandberg S, Paton JY, Ahola S, McCann DC, McGuinness D, Hillary CR, et al. The role of acute and chronic stress in asthma attacks in children. Lancet. 2000;356(9234):982–7. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
No datasets were generated or analyzed during the current study. All relevant data from this study will be made available upon study completion.