About 20% of children and 10% of adults worldwide suffer from AD, a multifactorial inflammatory skin condition that lowers the quality of life and has a non-negligible economic impact [2, 8]. AD is prevalent in children and often precedes a cascade of allergic conditions, including food allergies, allergic rhinitis, and asthma [31]. A recent study reported a 12.0% prevalence of AD in preschool-aged children in Urumqi [32]. Apart from causing discomfort and itching, AD can significantly impact children's self-esteem and future social engagement[3, 4]. Therefore, it is crucial to investigate early infancy risk factors for AD to facilitate timely prevention and treatment. This case-control study revealed that a history of parental atopic disease, maternal exposure to newly renovated dwellings during pregnancy, exclusive breastfeeding for 4 months or more, and three or more antibiotic treatments before the age of 1 were positively associated with the development of AD in children aged 2–8 years. Conversely, the presence of older siblings and low birth weight (< 2.5 kg) were found to be negatively associated with AD development.
One significant risk factor for atopic disease in children is the history of atopic disease in either or both parents. For example, prospective studies have revealed that a high FLG mutation risk score (OR = 1.8; 95% CI: 1.1–2.9), parental asthma (OR = 3.7; 95% CI: 1.2–11.5), and parental AD (OR = 6.2; 95% CI: 1.2–23.2) are substantial genetic risks for persistent AD in children [11]. A significant prospective cohort study conducted at the beginning of the century discovered that children whose parents had atopic disease had an increased risk of AD by the time the children were 4 years old; the risk of AD in children with a parental atopic history was nearly twice as high as that in children without a parental atopic history [33]; this effect was even more pronounced when parental AD was taken into account. The present research discovered that atopic disease of the parents, such as eczema, asthma, and allergic rhinitis, all exacerbated the risk of AD in preschoolers, particularly in mothers. This is also evidenced by the assessment of the factors' importance by predictive models.
Multivariate regression analysis identified a positive association between new indoor renovations during the mother's pregnancy and the prevalence of AD in children, compared to the period before the mother's pregnancy and the child's age of 0–1 year. The release of chemicals such as formaldehyde, organic volatiles, surfactants, and environmental endocrine disruptors (EDCs) during the renovation process has been linked to adverse health effects, particularly in young children and infants [34]. Additionally, immunological research suggests a higher prevalence of the type 2 helper cell phenotype in AD patients, characterized by elevated serum IgE and interleukin (IL)-4 levels. Furthermore, decorative and furniture materials containing volatile organic compounds (VOCs) can impact the fetal immune system and compromise the skin barrier, intensifying the sensitization process to indoor dust mites and molds[35–37]. This is particularly significant during the seventh to seventeenth month of gestation, a crucial period for fetal epidermal differentiation and susceptibility to exogenous hazardous substances such as PM2.5 [37]. Overall, the negative impacts of new renovations during the mother's pregnancy are significantly associated with the subsequent development of AD in children, compared to both new renovations before and after pregnancy.
The association between antibiotic use and childhood AD has been extensively studied, yielding varying conclusions due to differences in study design, periods of interest, and antibiotic types and doses, which have impacted the credibility of meta-analyses [38–39]. A multicenter cross-sectional study revealed a correlation (OR = 1.20, 95%CI: 1.11–1.30) between childhood AD and antibiotic use in children aged 0–1 years [40]. Similarly, a retrospective cohort study found that prenatal antibiotic exposure increased the incidence of AD in 11-year-old children (aHR = 1.19, 95%CI: 1.09–1.31) [41]. However, most studies have not shown an adverse impact or a statistically significant link between antibiotic usage in neonates and childhood AD[22, 42]. For example, a retrospective study based on a prospective cohort found decreased odds ratios for developing AD in children using antibiotics during the ages of 0–1 year and 1–4 years, with OR of 0.61 and 0.11, respectively; as well as a lower risk of atopic sensitization, with OR of 0.38 and 0.15, respectively [22]. Moreover, the quantity and frequency of antibiotic use have not been thoroughly examined in many studies positively associated with AD [43]. Our current study observed a significant association between antibiotic usage during the 0–1 age range and AD in preschool-aged children, with a frequency-enhanced effect (P for trend < 0.001) after controlling for antibiotic use frequency. Additionally, multivariable analysis revealed that the administration of three or more antibiotic doses between the ages of 0 and 1 was associated with a 92% higher risk of AD, independent of the child's mode of birth or the parents' history of atopic disorder. These findings offer valuable insights for further research on antibiotic use.
Preliminary research suggests a potential preventive effect of breastfeeding against childhood AD. A meta-analysis of prospective studies published before 2000 indicated that exclusive breastfeeding for at least three months reduced the risk of AD, particularly when considering parental atopic disorder separately (OR = 0.58; 95% CI: 0.41–0.92) [44]. However, recent research has failed to provide sufficient evidence to support the protective role of exclusive breastfeeding against AD [45]. In contrast, a 2014 Japanese birth cohort study revealed an increased risk of AD associated with exclusive breastfeeding compared to formula feeding alone (OR = 1.26, 95%CI: 1.12–1.41), showing a dose-response relationship (P for trend < 001) [46]. Various factors, including recall reporting bias, study design, and understanding of exclusive breastfeeding, may contribute to this discrepancy. Furthermore, recent advances in infant formula supplements may have partially mitigated the benefits of breastfeeding. The hygiene hypothesis suggests that prolonged exclusive breastfeeding reduces an infant's exposure to pathogenic stimuli, favoring type 2 helper cells over type 1 cells and increasing the risk of allergy development [13]. It also posits that breast milk contains antimicrobial and anti-inflammatory bioactive substances that aid in infant resistance to infections[47]. Introducing a variety of complementary foods between 6 and 12 months of age helps establish and maintain intestinal flora homeostasis, reducing the incidence of AD between 1–2 years of age [48]. Our study found a 1.59 times higher risk of AD in children exclusively breastfed for four months or longer compared to those who were not. Further stratified analyses revealed that this effect was primarily observed in children without a parental history of atopic disease, particularly when the mother did not have an atopic disease. A recent matched case-control study also indicated a significantly lower risk of AD in children under two years old when weaned or introduced to a diverse solid complementary diet as early as 4 months of age, with OR of 0.41 (95% CI: 0.20–0.87) and 0.30 (95% CI: 0.11–0.81), respectively [49]. However, this effect disappeared when stratifying by the child's mode of birth, suggesting that the mode of birth may be a significant confounding factor in the extended exclusive breastfeeding effect on AD, warranting further rigorous study designs for confirmation in the future.
The hygiene hypothesis, proposed in 1989, has undergone significant revisions and modifications. Strachan initially suggested that the exchange of early childhood infections between siblings could protect against immune-related diseases [26]. Building on this concept, Rook introduced the "Old-Friends-Hypothesis," which emphasizes the coexistence of infectious diseases and human evolution over time, suggesting that appropriate early-life exposure to microbial communities can help prevent immune-related diseases and allergic conditions [50]. Subsequent Alpine farm studies provided strong evidence for this hypothesis, broadening our understanding of the relationship between health and early-life microbial exposure [51]. In the field of immunology, the Microbiota Hypothesis, developed by Noverr and Hufnagle, has been refined through the study of microbial communities and their interactions with host mucosal surfaces, highlighting their metabolic and immunological effects[52]. Simultaneously, phylogenetic evidence indicates a lower variety and richness of microbial communities in invertebrates compared to vertebrates[53]. Combining concepts from biological evolution, immunology, and microbiology, the hygiene hypothesis is considered a historically relevant model explaining how modern lifestyles impact human health. It emphasizes the long-evolved balance between pathogen stimuli and immune responses from a human-nature perspective, suggesting a potential link to the rising prevalence of allergy-related diseases in industrialized nations [54–55]. Notably, this study found that children with older siblings had a 24% lower risk of AD, independent of parental atopic disease. However, no correlation was found between having a dog at home and AD in children aged 0–1 years. According to the hygiene hypothesis, close contact with older siblings, whether in caregiving roles or otherwise, may increase a child's exposure to pathogenic stimuli after birth, potentially lowering the risk of AD by promoting normal immune system maturation. A recent study on early-life illnesses and the development of AD in children suggests that older siblings may act as "microbe contact carriers" when interacting with the child [56]. By contrast, children under one year old are less likely to often interact with a dog, and the influence of this relationship is also not significant.
This study suggests that children born with low birth weight have a significantly lower risk of developing AD later in life. This unexpected finding aligns with the notion that babies with low birth weights require more personalized attention. Notably, low birth weight children are less likely than those with normal birth weight to experience exclusive breastfeeding (Table S3), indirectly supporting this observation. Further logistic analyses indicated that low birth weight children were 1.46 times more likely than those with normal birth weight to experience discontinuous exclusive breastfeeding (Table S4). According to the hygiene hypothesis, it is presumed that low birth weight babies may have a reduced risk of AD due to less exclusive breastfeeding and increased nursing care. However, it is evident that multiple factors, particularly the quality of postnatal nursing care, contribute to this effect, necessitating careful consideration of the role and significance of the hygiene hypothesis in this context.
Artificial intelligence (AI) technologies based on machine learning are poised to revolutionize AD management, paving the way for data-driven, personalized precision treatment. Beyond its role in clinical diagnosis and prognosis, machine learning has increasingly extended to population studies in recent years. For example, by developing various machine learning models, a recent large-scale case-control study based on machine learning algorithms was able to extract and mine new information about breast cancer risk factors from the standpoint of illness prediction [57]. In this study, father's asthma was the worst predictor of AD among all variables, according to both SHAP value and MeanDecreaseGini. However, logistics regression showed that father's asthma was second only to mother's AD in terms of OR for child's AD (Table S1). This is because the traditional OR is based on ratio of the odds of exposure among cases to the odds of exposure among controls, ignoring the magnitude of the contribution of the exposure itself to the outcome; whereas the machine learning algorithm emphasizes the degree to which the exposure contributes to the outcome compared to all factors. Both machine learning algorithms showed that parental AD or AR contributed more to child AD outcomes; followed by exclusive breastfeeding duration and antibiotic use frequency. Notably, exclusive breastfeeding duration and antibiotic use frequency demonstrated the highest feature importance in the random forest model, which may be related to the fact that these two variables belonged to the multicategorical ordered information, and the different categories had a cumulative effect on the prediction of AD, which can be corroborated by the SHAP value of the XGBoost model. Overall, the machine learning feature evaluation technique suggests that children of parents with AD or AR are a key population of concern for future AD preventive health care, and parents with atopic disease should raise health awareness to prevent the occurrence of AD in their children; secondly, reducing the overuse of antibiotics is also important for childhood AD; and lastly, high-quality epidemiologic and mechanistic studies are needed to further elucidate the effect of duration of exclusive breastfeeding on AD and its mechanisms, so as to provide a scientific basis for maternal and child health care practices.
Through a large case-control study, we analyzed the effects of indoor environmental factors in early life, frequency of antibiotic use in 0–1 year olds, duration of exclusive breastfeeding in 0–1 year olds, and sibling status on AD in preschool children. While our strength lies in the comprehensive analysis and machine learning model development, this study also presents certain limitations. It is important to note that this is a single-center study conducted in Urumqi city and therefore may not fully represent the national situation. Additionally, being a retrospective study, there is potential for recall bias, which may compromise the credibility of the results. Moreover, the outcome indicators were obtained through questionnaires, introducing potential reporting bias.