Healthy Lifestyles Can Offset Respiratory/Psych-behavioral Comorbidities Due to Gestational Diabetes Mellitus or Prenatal Smoking Exposure in Children Aged 2-16 Years

Healthy Lifestyles Can Offset Respiratory/Psych-behavioral Comorbidities Due to Gestational Diabetes Mellitus or Prenatal Smoking Exposure in Children Aged 2-16 Years | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Healthy Lifestyles Can Offset Respiratory/Psych-behavioral Comorbidities Due to Gestational Diabetes Mellitus or Prenatal Smoking Exposure in Children Aged 2-16 Years Mei Xue, Kening Chen, Xiaoqian Zhang, Wenquan Niu, Zhixin Zhang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5738489/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Aim The aim of this study was to test whether healthy lifestyles can offset the increased risk of childhood respiratory and psycho-behavioral comorbidities attributed to gestational diabetes mellitus (GDM) or prenatal smoking exposure. Methods From April to May 2024, we conducted a cross-sectional cluster sampling of children aged 2–16 years in Beijing. Fetal and neonatal related factors, family-related factors, and lifestyle-related information were collected through an electronic questionnaire. A weighted healthy lifestyle score was calculated by aggregating diet, physical activity, sleep time, and screen time; it was categorized into healthy, intermediate and unhealthy lifestyles. Logistic regression was used to estimate odds ratio (OR) and 95% confidence interval (95% CI) for the association of GDM or smoking during pregnancy with respiratory and psych-behavioral comorbidities. Interaction terms were used to explore the offsetting effect of lifestyle factors. Results The prevalence of respiratory and psych-behavioral comorbidities among Chinese children aged 2–16 years was 15.18%. GDM and smoking during pregnancy were associated with an increased risk of childhood comorbidities (multi-adjusted OR, 95% CI: 1.40, 1.07–1.82 and 1.71, 1.22–2.40). Children with unhealthy lifestyles faced a significantly higher risk of developing comorbidities compared to their peers with healthy lifestyles (1.91; 1.48–2.45). Adhering to healthy lifestyles can offset the increased risk of childhood comorbidities due to GDM (1.42, 0.81–2.48) or smoking during pregnancy (1.29, 0.50–3.31). Conclusions Our findings indicated that adherence to healthy lifestyles might offset the increased risk of childhood respiratory and psycho-behavioral comorbidities that were attributed to prenatal GDM or smoking during pregnancy. Healthy lifestyle Respiratory and psycho-behavioral comorbidities Gestational diabetes mellitus Smoking during pregnancy Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Respiratory and psych-behavioral comorbidities are common in children worldwide, and they pose a major burden in pediatric healthcare. Global Burden of Disease Study 2021 estimated that lower respiratory infection, a substantial cause of deaths, is responsible for 0.76 million deaths among children under 5 around the global. There is evidence that 8% of children and 15% of adolescents worldwide are living with mental disorders, 1 and this number tends to rise in recent decades. Exhaustive endeavors have been devoted to curb the occurrence and progression of childhood respiratory and psych-behavioral comorbidities, such as vaccination, yet the effect is far from satisfactory. Therefore, the identification of factors that can offset the adverse outcomes of these comorbidities are still subject to ongoing exploration, improvement, and renewal. The development of respiratory and psych-behavioral comorbidities is complex and involve a variety of factors, such as gestational diabetes mellitus (GDM) and smoking during pregnancy. On one hand, GDM is a prevalent metabolic disorder during pregnancy marked by hyperglycemia during the second or third trimester. 2 Research shows that hyperglycemia exposure can affect fetal lung development, causing post-birth respiratory difficulties. 3 Besides, Chen et al 4 in a population-based study found that GDM diagnosed between the 27th and 30th week of pregnancy was associated with a higher likelihood of attention deficit hyperactivity disorder (ADHD) in childhood. Meta-analytical evidence 5 also consolidates the close link between GDM and prevalent autism spectrum disorder (ASD) in offspring. On the other hand, smoking during pregnancy is prevailing, 6 and prenatal exposure to nicotine has received growing concerns because it can readily cross placental barriers. Studies have shown that nicotine levels in umbilical veins are comparable to those in maternal veins, and nicotine levels in fetal lungs are similar to those in fetal blood. 7 , 8 There is evidence for an increasing rate of respiratory diseases and psycho-behavioral disorders in children exposed to prenatal maternal smoking. 9 – 14 In a pooled analysis of eight European birth cohorts, exposing maternal smoking during pregnancy rather than after birth was found to precipitate the risk of having wheezing and asthma in children aged 4–6 years, 15 as supported by a national study in Japan, 16 showing a close correlation of maternal smoking before and during pregnancy with incident wheezing in offspring up to three years. Meanwhile, the risk of having ADHD was increased by 60% for children whose mothers smoked during pregnancy. 17 GDM and smoking during pregnancy are prenatal adverse events for children, and it is of interest to know whether postnatal healthy lifestyles can offset these events. Nowadays, healthy lifestyles such as eating well-balanced foods, being physically active, lowing screen-seeing time, and having restorative sleep are being advocated in whole society as the upstream drivers and lifestyle medicine to prevent and reverse diseases facing children and adults around the world. Many studies have interrogated the individual contribution of these lifestyle factors to the prevention of asthma 18 and mental health 19 in children, while overlooking their potential combined roles in pulmonary and mental health. Thus far, no study has examined the counterbalancing effect of healthy lifestyles on respiratory and psych-behavioral comorbidities conferred by GDM and smoking during pregnancy. To fill this gap in knowledge, we explored the individual and joint association of GDM, smoking during pregnancy and healthy lifestyles with respiratory and psycho-behavioral comorbidities in children, with the goal of testing the hypothesis that healthy lifestyles can offset the increased risk of these comorbidities attributed to GDM and prenatal smoking exposure. METHODS Study design and children This cross-sectional study was conducted in the Pinggu District of Beijing, China, during the period between April and May in 2024. Data were collected using self-designed questionnaires. Total 4,419 valid questionnaires were collected from children aged 2 to 16 years recruited through a combination of stratified random and whole cluster random sampling methods. Children who did not meet age criteria (n = 21) and lacked comprehensive medical information (n = 353) were excluded, leaving 4,045 children in the final analysis (Fig. 1 ). The study was conducted in compliance with local legal and institutional guidelines, with data anonymized using unique identifiers. Parental or guardian consents were obtained electronically, with the option for children to opt-outs, as detailed in the consent form. Data collection procedure Data on demographic factors, fetal and neonatal factors (mode of delivery, birth body length, birthweight, pregnancy order, and delivery order), family-related factors (maternal and paternal body mass index [BMI], maternal and paternal childbearing age, maternal and paternal education, family income, gestational diabetes mellitus, smoking during pregnancy, vitamin D supplement during pregnancy, and duration of breastfeeding), and lifestyle factors (diet, physical activity, sleep, and screen time) were collected using standardized questionnaires and procedures. Physical assessments included standardized measurements of height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg) performed by health practitioners in kindergartens and schools. Details of questions and definitions of each item in our questionnaire are provided in Supplementary materials . Quality control The quality of our survey data was strictly controlled. Specifically, school health physicians and head teachers were trained to understand the elaborate procedures of this survey and each item in the questionnaire. They were in charge of assisting the parents or guardians of the participating children to fill in the questionnaire. When the survey was completed, data were downloaded from the “Wenjuanxing” platform and each item was strictly checked. In the case of missing values or apparent outliers, teachers and school healthcare physicians in charge were tasked with reaching out to the parents or guardians of children to obtain or verify necessary information. Definition of Comorbidities In this research study, comorbidities are defined as the comorbidities of respiratory and psycho-behavioral problems. Guardians are asked to report the children’s annual frequency of upper respiratory infection (URI), which encompass common cold, tonsillitis, pharyngitis, laryngitis, sinusitis, and otitis media, as well as lower respiratory tract infection, including tracheobronchitis and pneumonia, with symptom onset intervals exceeding 7 days. Additionally, guardians must confirm if their child has been definitively diagnosed with asthma. Respiratory problems are identified if a child experiences recurrent URI or a definitive asthma diagnosis. To quantify recurrent respiratory infections, the following criteria are applied: for children aged 2–5 years, more than 6 URI episodes per year or more than 2 lower respiratory infections per year; for children over 5 years, more than 5 URI episodes per year or more than 2 lower respiratory infection per year, with symptom onset intervals exceeding 7 days. Respiratory problems are characterized by either recurrent infections or a definitive asthma diagnosis. For psycho-behavioral assessment, guardians completed the Conners Parent Symptom Questionnaire (PSQ), a 48-item scale with six subscales, including conduct problems, learning difficulties, psychosomatic disorders, impulsivity/hyperactivity, anxiety, and a hyperactivity index. Responses are recorded on a 4-point frequency scale from never to frequently, with higher scores indicating more severe symptoms. Furthermore, guardians are queried about potential definitive diagnoses of autism, ADHD, and tic disorders. GDM and smoking during pregnancy GDM (“Does the mother have gestational diabetes?” The answer is yes or no) and smoking during pregnancy (“Did the child’s mother smoke actively or passively during pregnancy?” (Active smoking is defined as mothers who smoke more than 10 cigarettes a day. Passive smoking is defined as more than 1 day a week in the inhalation of smokers exhaled smoke time > 15min/ day). The answer is yes or no) were reported by their parents. Healthy lifestyle score A composite healthy lifestyle score was established for children, incorporating four key behaviors - diet, physical activity, screen time, and sleep duration. These behaviors were categorized as healthy or unhealthy based on established guidelines. Participants received one point for each healthy behavior, resulting in a score range of 0 to 4, with higher scores indicating healthier habits. The criteria for regular physical activity and healthy screen time were adapted from the WHO Guidelines on Physical Activity and Sedentary Behavior, 20 recommending that children engage in at least 60 minutes of moderate to vigorous-intensity physical activity daily, spread across the week. Screen time, defined as the sum of recreational time spent watching television, and using tablets or smartphones, should be limited to less than 2 hours per day according to these guidelines. 21 Sleep duration guidelines vary by ages and were referenced from the recommendations of the American Academy of Sleep Medicine. 22 Healthy diet was formulated in alignment with the Dietary Guidelines for Chinese Residents (2016), encompassing 14 food items. Intakes of rice, pasta, fruits, vegetables, soy, eggs, dairy, meat, poultry, aquatic products, and nuts were deemed healthy, while that of desserts, fried foods, preserved foods, and sugary beverages unhealthy. These dietary components have been correlated with childhood respiratory or psycho-behavioral problems. Lifestyle score was further stratified into unfavorable (0 or 1 healthy factor), moderate (2 healthy factors), and favorable (3 or 4 healthy factors) categories based on population distribution. Although this simple additive approach has been widely used, 23 , 24 the underlying assumption is that the association between different lifestyle factors and outcomes is identical, which may not be the case in practice. Consequently, a weighted lifestyle score was developed. This score was calculated by multiplying each binary lifestyle variable by its corresponding β coefficient from a Logistic regression model after adjusting for age and sex, summing these products, dividing by the total of the β coefficients, and then multiplying by 100. 24 , 25 Weighted standardized scores were then categorized into favorable, moderate, and unfavorable groups based on their distributions. Statistical analyses Continuous variables are presented as mean (standard deviation [SD]) or median (interquartile range); categorical variables as percentages. The t-test or rank-sum test was used for continuous variables, while the χ 2 test was for categorical variables. Logistic regression was applied to compute odds ratio (OR) for comorbidities in children, with those without comorbidities serving as the control group. Three models were constructed: model 1 was unadjusted; model 2 included adjustment for age and sex; model 3 included further adjustment for maternal obesity, maternal education level, mode of delivery, maternal age at childbearing, vitamin D supplementation during pregnancy, duration of breastfeeding, smoking during pregnancy (or GDM), and weighted healthy lifestyle score. The selection of covariates was based on expert knowledge regarding clinically significant risk factors for respiratory and psycho-behavioral disorders in children, as well as literature identifying suspected or established factors associated with exposure or outcomes. Data were grouped by combining GDM or smoking during pregnancy with lifestyle factors (all six categories, with the absence of GDM and a healthy lifestyle or non-smoking during pregnancy and a healthy lifestyle as the reference group) to investigate the association between adverse prenatal factors and postnatal lifestyle factors with the risk of respiratory and psycho-behavioral comorbidities in children aged 2–16 years. The joint correlation Logistic regression model was fully adjusted. To ensure the robustness of the regression model, a sensitivity analysis using unweighted lifestyle scores was done. All reported P values were two-tailed, with a threshold of less than 0.05 being statistically significant. Data were analyzed within November, 2024 using STATA software (version 16.0, Stata Corp, College Station, Texas, USA) and R coding platform (version 4.3.3). RESULTS Baseline characteristics After excluding invalid or incomplete or unqualified questionnaires (Fig. 1 ), data from 4045 children were analyzed in this study, comprising 1964 girls and 2081 boys; the response rate was 92%. The baseline characteristics of all eligible children are detailed in Table 1 . Of all children, 614 were identified with comorbid respiratory and psycho-behavioral conditions, with a prevalence rate of 15.18% in this population. Overall, healthy lifestyles were adopted by 29.57% of all children. During pregnancy, GDM was present in 402 mothers (9.94%), and 221 mothers (5.46%) smoked while pregnant. Generally, children with comorbidities tended to be younger and more likely to have an intermediate or unhealthy lifestyle. Table 1 Basic Characteristics of Study Children Characteristics Absence of Comorbidities (n = 3431) Presence of Comorbidities (n = 614) P Age (years) 12.16 [6.95, 13.79] 6.01 [4.76, 10.47] < 0.001 Sex 0.03 Boys 1740 (50.71) 341 (55.34) Girls 1691 (49.29) 273 (44.46) Height (cm) 156 [127, 167] 120 [110, 150] < 0.001 Weight (kg) 46 [27, 60] 24.6 [19, 44] < 0.001 BMI 18.94 [16.09, 23.04] 16.67 [15.01, 20.96] < 0.001 Siblings 0.14 Yes 1775 (51.73) 298 (48.53) No 1656 (48.27) 316 (51.47) Respiratory problems 304 (8.86) 614 (100.00) < 0.001 Psycho-behavioral problems 1398 (40.75) 614 (100.00) < 0.001 Fetal and neonatal factors Delivery mode 0.13 Vaginal delivery 1506 (43.89) 291 (47.39) Cesarean section 1758 (51.24) 285 (46.42) Transferred from vaginal delivery 155 (4.52) 35 (5.70) Forceps delivery 12 (0.35) 3 (0.49) Birth body length 50 [50, 52] 50 [50, 52] 0.52 Birth weight 3400 [3000, 3650] 3300 [3000, 3600] 0.03 Pregnancy order < 0.001 1 2586 (75.37) 874 (70.14) ≥ 2 845 (24.63) 372 (29.86) Delivery order < 0.001 1 2107 (61.41) 306 (49.84) ≥ 2 1324 (38.59) 308 (50.16) Family-related factors Maternal BMI 23.23 [21.10, 25.86] 23.72 [21.23, 26.45] 0.03 Paternal BMI 25.83 [23.59, 27.78] 25.83 [23.88, 28.41] 0.14 Maternal childbearing age 28 [25, 30] 29 [26, 32] < 0.001 Paternal childbearing age 29 [26, 32] 30 [28, 33] < 0.001 Maternal education (%) < 0.001 High school degree or below 1172 (34.16) 156 (25.41) Bachelor’s degree 2185 (63.68) 440 (71.66) Master’s degree or above 74 (2.16) 18 (2.93) Paternal education (%) < 0.001 High school degree or below 1439 (41.94) 227 (36.97) Bachelor’s degree 1907 (55.58) 382 (62.21) Master’s degree or above 85 (2.48) 5 (0.81) Family income (RMB per year) (%) 0.48 < 100,000 1003 (39.80) 193 (42.70) 100,000–300,000 1278 (50.71) 216 (47.79) ≥ 300,000 239 (9.48) 43 (9.51) Gestational diabetes mellitus < 0.001 Yes 305 (8.89) 97 (15.80) No 3126 (91.11) 517 (84.20) Smoking during pregnancy < 0.001 Yes 165 (4.81) 56 (9.12) No 3266 (95.19) 558 (90.88) Vitamin D supplement during pregnancy < 0.001 ≥ 3 months strictly following doctor’s advice 2265 (66.02) 363 (59.12) < 3 months strictly following doctor’s advice 321 (9.36) 74 (12.05) Not strictly following doctor’s advice 344 (10.03) 92 (14.98) Never supplemented 501 (14.60) 85 (13.84) Duration of breastfeeding (months) 12 [8, 15] 12 [8, 17] 0.24 Lifestyle-related information Healthy Lifestyle factors Healthy diet 1848 (53.86) 282 (45.93) < 0.001 Regular physical activity 175 (5.11) 13 (2.13) < 0.001 Healthy screen time 2826 (82.92) 485 (79.64) 0.05 Adequate sleep 2124 (61.91) 339 (55.21) 0.002 No. of healthy lifestyle factors < 0.001 0 144 (4.20) 32 (5.21) 1 739 (21.54) 181 (29.48) 2 1481 (43.17) 272 (44.30) 3 996 (29.03) 122 (19.87) 4 71 (2.07) 7 (1.14) Weighted healthy lifestyle score 35.79 [24.90, 56.42] 31.52 [20.62, 45.53] < 0.001 Healthy lifestyle category < 0.001 Healthy lifestyle 1067 (31.10) 129 (21.01) Intermediate lifestyle 1481 (43.17) 272 (44.30) Unhealthy lifestyle 883 (25.74) 213 (34.69) Maternal factors and childhood comorbidity Table 2 delineates the association between maternal factors and respiratory and psycho-behavioral comorbidities in children. After multiple adjustment for potential confounders including age, sex, maternal obesity, maternal educational level, mode of delivery, maternal age at childbearing, vitamin D supplementation during gestation, duration of breastfeeding, smoking status during pregnancy (or GDM), and weighted healthy lifestyle score, the risk of respiratory and psycho-behavioral comorbidities was significantly higher in children whose mothers had a history of GDM than children whose mothers had no GDM (OR = 1.40; 95% CI: 1.07–1.82). Likewise, children whose mothers smoked during pregnancy were 1.71 times more likely to have these comorbidities than children whose mothers did not smoke during pregnancy (OR = 1.71; 95% CI: 1.22–2.40). Table 2 Gestational diabetes mellitus or Smoking during Pregnancy and Comorbidity Risk in Children Subgroups No. of children with comorbidities/No. of total children OR (95% CI) Model 1 a Model 2 b Model 3 c Gestational diabetes mellitus (GDM) Without GDM 517 / 3643 1 [Ref] 1 [Ref] 1 [Ref] With GDM 97 / 402 1.92 (1.50, 2.46) *** 1.47 (1.14, 1.90) ** 1.40 (1.07, 1.82) * Smoking during pregnancy Non-exposed 558 / 3824 1 [Ref] 1 [Ref] 1 [Ref] Exposed 56 / 221 1.98 (1.45, 2.73) *** 1.87 (1.35, 2.60) *** 1.71 (1.22, 2.40) ** Lifestyle categories and childhood comorbidities Table 3 elucidates the association between adherence to healthy lifestyles and the risk of respiratory and psycho-behavioral comorbidities in children. Adjusting for age and sex revealed that comorbidity risk was increased with the increasing number of unhealthy lifestyle factors. Specifically, children who had unhealthy lifestyle practices were nearly twice as likely to experience these comorbidities compared to children with healthy lifestyle habits (OR = 1.98; 95% CI: 1.54–2.53). Fully-adjusted OR was reinforced for this association (OR = 1.91; 95% CI: 1.48–2.45). Table 3 Lifestyle Categories and Comorbidity Risk in Children Subgroups No. of children with comorbidities/No. of total children OR (95% CI) Model 1 a Model 2 b Model 3 c Healthy lifestyle categories Health lifestyle 129 / 1196 1 [Ref] 1 [Ref] 1 [Ref] Intermediate lifestyle 272 / 1753 1.55 (1.24, 1.94) *** 1.54 (1.22, 1.94) *** 1.54 (1.22, 1.95) *** Unhealthy lifestyle 213 / 1096 2.01 (1.58, 2.54) *** 1.98 (1.54, 2.53) *** 1.91 (1.48, 2.45) *** P for trend < 0.001 < 0.001 < 0.001 Combined maternal and lifestyle factors with childhood comorbidities When GDM or smoking during pregnancy were combined with various lifestyle categories, the consistent association with childhood comorbidities was observed. Figure 2 provides the fully-adjusted ORs for the combined effect of maternal factors and lifestyle categories on respiratory and psycho-behavioral comorbidities in children. Notably, the co-occurrence of both GDM and unhealthy lifestyle was associated with a markedly increased risk of comorbidities compared to children whose mothers had no GDM and who had unhealthy lifestyle practices (OR = 2.08; 95% CI: 1.23–3.49). Similarly, the combination of maternal smoking during pregnancy and unhealthy lifestyle significantly amplified the risk of comorbidities in childhood relative to children whose mothers did not smoke during pregnancy and who adhered to healthy lifestyle (OR = 3.72; 95% CI: 2.11–6.56). However, adherence to healthy lifestyle appeared to offset the heightened risk conferred by GDM (OR = 1.42; 95% CI: 0.81–2.48) and smoking during pregnancy (OR = 1.29; 95% CI: 0.50–3.31). Subgroup analyses by age and sex showed no statistical significance for comorbidity risk in children who had healthy lifestyles and whose mothers had GDM or smoked during pregnancy compared with children who adhered to healthy lifestyles and whose mothers neither had GDM nor smoked during pregnancy (Table 4 ). Consistent trends were observed when utilizing unweighted healthy lifestyle score, as depicted in Fig. 3 , further emphasizing the protective role of healthy lifestyle against the development of respiratory and psycho-behavioral comorbidities in children. Table 4 Subgroup Analyses on Healthy Lifestyle and Comorbidity Risk Conferred by Gestational Diabetes Mellitus (GDM) or Smoking during Pregnancy Subgroups Health Lifestyle with Gestational Diabetes Mellitus (GDM) Health Lifestyle with Smoking during Pregnancy n OR 95% CI n OR 95% CI Age (years) 2–6 28 1.73 0.70, 4.29 9 1.53 0.36, 6.57 6–10 51 1.19 0.52, 2.70 13 0.71 0.14, 3.46 > 10 40 0.79 0.11, 6.17 16 1.65 0.19, 4.10 Sex Boys 65 1.23 0.53, 2.87 26 1.58 0.54, 4.61 Girls 54 1.47 0.68, 3.16 12 0.48 0.05, 4.19 DISCUSSION Via a comprehensive analysis of survey data from 4045 children currently living in Beijing, our findings supported the hypothesis that healthy lifestyle can offset the increased risk of respiratory and psycho-behavioral comorbidities in children that were attributed to prenatal GDM and smoking during pregnancy, indicating that advocating healthy lifestyles in children can be proposed as a method for primary prevention of respiratory and psycho-behavioral comorbidities, especially in children whose mothers have exposed to GDM or smoking during pregnancy. To our knowledge, this is thus far the first study that has investigated the synergistic effect of healthy lifestyle and adverse prenatal exposure on following childhood respiratory and psycho-behavioral comorbidities. Mounting evidence suggests that respiratory disorders and mental problems are common in children and profoundly affect children’s healthy growth and development. 26 – 32 From a prospective viewpoint, maternal health status during pregnancy is pivotal for fetal growth and future health of offspring. Currently, a variety of prenatal factors have been established to significantly influence the development of respiratory and psycho-behavioral problems in children, practically GDM and smoking during pregnancy. 2 , 6 Consistent with the findings of prior studies, 33 – 37 we found that children whose mothers had a history of GDM or smoked during pregnancy had a significantly higher risk of experiencing respiratory and psycho-behavioral comorbidities than those without these adverse exposure, even after taking a wide panel of confounders into consideration, indicating the robustness of our findings. In practice, respiratory disorders and mental problems are interlinked, as respiratory disorders such as asthma often lead to breathing difficulties, which in return may trigger the development of anxiety and depression due to consistent physical discomfort. Moreover, children with respiratory disorders are often physically inactive and not good at social interaction, which could precipitate the occurrence of loneliness and depression. 38 From a biological aspect, respiratory disorders are featured by inflammation, which may contribute to cognitive dysfunction and indirectly influence mood and behavior by affecting circulating neurotransmitters and neuronal health. 39 Prior studies have assessed childhood respiratory disorders and mental problems individually, overlooking their co-occurring roles and overlapped underlying causes. To shed more light on this issue, we in a general children population from Pinggu district of Beijing attempted to seek potential avenues that can prevent the occurrence of respiratory and psycho-behavioral comorbidities attributed to GDM or smoking during pregnancy. Lifestyle practices are modifiable and represent largely untapped opportunity to mitigate the adverse outcomes of children under the exposure of prenatal GDM and smoking during pregnancy. Lifestyle factors are multifaceted, mainly including diet, physical activity, screen time, and sleep; they hold significant potentials for health and well-being. For instance, diet can significantly influence allergic diseases, including asthma, by modulating airway inflammation through antioxidant-rich foods like fruits, vegetables, and whole grains. 40 , 41 A well-balanced diet might potentially alleviate both systemic and airway inflammation in children with asthma. 42 Additionally, research has shown that balanced diet is beneficial for better mental health and better cognition, as evidenced by a large-scale study involving 180,000 participants. 43 Likewise, physical activity also plays a crucial role in asthma prevention and management; moderate-to-vigorous exercise can reduce asthma risk and improving airway responsiveness. 44 Clinically, physical activity has an immediate positive influence on the airway smooth muscle, leading to a reduction in airway responsiveness. 45 Exercise is also linked to better mental health outcomes in children, as shown in a meta-analysis of 13 studies involving 115,540 children. 46 Children who engaged in physical activity were reported to have mental well-being for both genders. 47 Above lines of evidence collectively highlight the significant roles of healthy lifestyles in the prevention of adverse respiratory and psycho-behavioral conditions in children. 23 , 24 , 48 – 51 Most prior studies merely focused on one or few lifestyle factors, and frequently neglected the their joint contribution to childhood respiratory and psycho-behavioral comorbidities. Extending the findings of prior studies, we generated a weighted healthy lifestyle score by comprehensively assessing various lifestyle related factors (diet, sleep, physical activity, and screen time), and provided the first-ever evidence that children with unhealthy lifestyles faced a significantly higher risk of developing respiratory and psycho-behavioral comorbidities compared to their peers with healthy lifestyles, and importantly adhering to healthy lifestyles might offset the increased risk of these comorbidities resulting from GDM or smoking during pregnancy. Strengths of this study include an extensive sampling of children from Beijing, a high response rate, and a comprehensive analysis of the combined effect of recommended lifestyle changes on respiratory and psycho-behavioral problems in children. However, some limitations should be acknowledged when interpreting our findings. Firstly, due to the cross-sectional design of this survey, causality cannot be established. Secondly, our study was based on data from children 2–16 years of age living in a district of Beijing, and extrapolation of our findings to other regions or races should be made with caution. Thirdly, in this survey, data were collected via parents-reported electronic questionnaires, leaving recall or reporting bias an open question, although we had implemented strict quality control. Our findings presented here are preliminary, and further investigations are urgently needed to elucidate and substantiate our results by incorporating more data in other independent groups. Taken together, our findings indicated that adherence to healthy lifestyles might offset the increased risk of childhood respiratory and psycho-behavioral comorbidities that were attributed to prenatal GDM or smoking during pregnancy. For practical reasons, through unraveling the potential protective roles of healthy lifestyles, we can inform public health initiatives and clinical advice to assist families in fostering the health and well-being of their children, especially those with adverse prenatal exposure. To achieve this goal, further research is necessary to clarify and affirm our findings. Declarations Ethics approval and consent to participate: This study was approved by the Ethics Committee of the China-Japan Friendship Hospital (2024-KY-086), and all participants and their parents provided informed consents voluntarily. Consent for publication: Not applicable. Availability of data and material: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request. Competing interests: The authors declare no conflict of interest and no financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article. Funding: This work was supported by the Public Service Development and Reform Pilot Project of Beijing Medical Research Institute (W. Niu), the Capital’s Funds for Health Improvement and Research (Grant Number: 2024-2-1133), and the National Natural Science Foundation of China (Grant Number: 81970042). Authors' contributions: Z.Z. and W.N. designed the study. X.Z. and Z.Z. obtained ethics approvals and contributed to data acquisition. M.X. and K.C. performed the statistical analysis and wrote the first draft. Z.Z. and W.N. are the study guarantors. All authors contributed to the article and approved the submitted version. Acknowledgements: We are grateful to all participating children and their parents or grandparents for their cooperation and willingness. 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Combined impact of healthy lifestyle factors on risk of asthma, rhinoconjunctivitis and eczema in school children: ISAAC phase III. Thorax Jun. 2019;74(6):531–8. 10.1136/thoraxjnl-2018-212668 . Fismen AS, Aarأߜ LE, Thorsteinsson E, et al. Associations between eating habits and mental health among adolescents in five nordic countries: a cross-sectional survey. BMC Public Health Sep. 2024;27(1):2640. 10.1186/s12889-024-20084-w . WHO Guidelines Approved by the Guidelines Review Committee. WHO Guidelines on Physical Activity and Sedentary Behaviour. World Health Organization © World Health Organization 2020.; 2020. QuickStats. Percentage* of Children and Adolescents Aged 5–17 Years Who Reported Being Tired Most Days or Every Day,(†) by Age Group and Hours of Screen Time(§) - National Health Interview Survey, United States, 2020(¶). MMWR Morb Mortal Wkly Rep Feb. 2022;11(6):224. 10.15585/mmwr.mm7106a5 . Paruthi S, Brooks LJ, D'Ambrosio C, et al. Recommended Amount of Sleep for Pediatric Populations: A Consensus Statement of the American Academy of Sleep Medicine. J Clin Sleep Med Jun. 2016;15(6):785–6. 10.5664/jcsm.5866 . Khera AV, Emdin CA, Drake I, et al. Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. N Engl J Med Dec. 2016;15(24):2349–58. 10.1056/NEJMoa1605086 . Zhang YB, Pan XF, Chen J, et al. Combined lifestyle factors, incident cancer, and cancer mortality: a systematic review and meta-analysis of prospective cohort studies. Br J Cancer Mar. 2020;122(7):1085–93. 10.1038/s41416-020-0741-x . Jiao L, Mitrou PN, Reedy J, et al. A combined healthy lifestyle score and risk of pancreatic cancer in a large cohort study. Arch Intern Med Apr. 2009;27(8):764–70. 10.1001/archinternmed.2009.46 . Bai S, Qin L, Zhang P, et al. Development and validation of asthma diagnostic scale for children. Pediatr Res Sep. 2024;26. 10.1038/s41390-024-03584-8 . Maciag MC, Phipatanakul W. Prevention of Asthma: Targets for Intervention. Chest Sep. 2020;158(3):913–22. 10.1016/j.chest.2020.04.011 . Narciso AR, Dookie R, Nannapaneni P, Normark S, Henriques-Normark B. Streptococcus pneumoniae epidemiology, pathogenesis and control. Nat Rev Microbiol Nov. 2024;6. 10.1038/s41579-024-01116-z . Stern J, Pier J, Litonjua AA. Asthma epidemiology and risk factors. Semin Immunopathol Feb. 2020;42(1):5–15. 10.1007/s00281-020-00785-1 . Leone M, Kuja-Halkola R, Leval A, et al. Association of Youth Depression With Subsequent Somatic Diseases and Premature Death. JAMA Psychiatry Mar. 2021;1(3):302–10. 10.1001/jamapsychiatry.2020.3786 . Momen NC, Plana-Ripoll O, Agerbo E, et al. Association between Mental Disorders and Subsequent Medical Conditions. N Engl J Med Apr. 2020;30(18):1721–31. 10.1056/NEJMoa1915784 . Posner J, Polanczyk GV, Sonuga-Barke E. Attention-deficit hyperactivity disorder. Lancet (London, England) . Feb. 2020;8(10222):450–62. 10.1016/s0140-6736(19)33004-1 . Budu-Aggrey A, Joyce S, Davies NM, et al. Investigating the causal relationship between allergic disease and mental health. Clin Exp Allergy Nov. 2021;51(11):1449–58. 10.1111/cea.14010 . Jiang M, Qin P, Yang X. Comorbidity between depression and asthma via immune-inflammatory pathways: a meta-analysis. J Affect Disord Sep. 2014;166:22–9. 10.1016/j.jad.2014.04.027 . Liu WZ, Zhang WH, Zheng ZH, et al. Identification of a prefrontal cortex-to-amygdala pathway for chronic stress-induced anxiety. Nat Commun May. 2020;6(1):2221. 10.1038/s41467-020-15920-7 . Yan Z, Chen J, Guo L, et al. Genetic analyses of the bidirectional associations between common mental disorders and asthma. Front Psychiatry. 2024;15:1372842. 10.3389/fpsyt.2024.1372842 . Zhu Z, Zhu X, Liu CL, et al. Shared genetics of asthma and mental health disorders: a large-scale genome-wide cross-trait analysis. Eur Respir J Dec. 2019;54(6). 10.1183/13993003.01507-2019 . Leander M, Lampa E, Rask-Andersen A, et al. Impact of anxiety and depression on respiratory symptoms. Respir Med Nov. 2014;108(11):1594–600. 10.1016/j.rmed.2014.09.007 . Cortese S, Sun S, Zhang J, et al. Association between attention deficit hyperactivity disorder and asthma: a systematic review and meta-analysis and a Swedish population-based study. Lancet Psychiatry Sep. 2018;5(9):717–26. 10.1016/s2215-0366(18)30224-4 . Julia V, Macia L, Dombrowicz D. The impact of diet on asthma and allergic diseases. Nat Rev Immunol May. 2015;15(5):308–22. 10.1038/nri3830 . Crespo A, Giner J, Torrejأߗn M, et al. Clinical and inflammatory features of asthma with dissociation between fractional exhaled nitric oxide and eosinophils in induced sputum. J Asthma Jun. 2016;53(5):459–64. 10.3109/02770903.2015.1116086 . Alwarith J, Kahleova H, Crosby L, et al. The role of nutrition in asthma prevention and treatment. Nutr Rev Nov. 2020;1(11):928–38. 10.1093/nutrit/nuaa005 . Zhang RH, Zhang B, Shen C. Associations of dietary patterns with brain health from behavioral, neuroimaging, biochemical and genetic analyses. Nat Mental Health April. 2024;1(2):535–52. org/10.1038/s44220-024-00226-0 . Lu K, Sidell M, Li X, et al. Self-Reported Physical Activity and Asthma Risk in Children. J Allergy Clin Immunol Pract Jan. 2022;10(1):231–e2393. 10.1016/j.jaip.2021.08.040 . Lee B, Kim Y, Kim YM, et al. Anti-oxidant and Anti-inflammatory Effects of Aquatic Exercise in Allergic Airway Inflammation in Mice. Front Physiol. 2019;10:1227. 10.3389/fphys.2019.01227 . Sampasa-Kanyinga H, Colman I, Goldfield GS, et al. Combinations of physical activity, sedentary time, and sleep duration and their associations with depressive symptoms and other mental health problems in children and adolescents: a systematic review. Int J Behav Nutr Phys Act Jun. 2020;5(1):72. 10.1186/s12966-020-00976-x . Alshallal AD, Alliott O, Brage S, et al. Total and temporal patterning of physical activity in adolescents and associations with mental wellbeing. Int J Behav Nutr Phys Act Jan. 2024;8(1):5. 10.1186/s12966-023-01553-8 . Deng Q, Zhang Y, Guan X, Wang C, Guo H. Association of healthy lifestyles with risk of all-cause and cause-specific mortality among individuals with metabolic dysfunction-associated steatotic liver disease: results from the DFTJ cohort. Ann Med Dec. 2024;56(1):2398724. 10.1080/07853890.2024.2398724 . Marino P, Mininni M, Deiana G, et al. Healthy Lifestyle and Cancer Risk: Modifiable Risk Factors to Prevent Cancer. Nutrients Mar. 2024;11(6). 10.3390/nu16060800 . Meyer U, Schindler C, Bloesch T, et al. Combined impact of negative lifestyle factors on cardiovascular risk in children: a randomized prospective study. J Adolesc Health Dec. 2014;55(6):790–5. 10.1016/j.jadohealth.2014.07.007 . Zhang YB, Chen C, Pan XF, et al. Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies. Bmj Apr. 2021;14:373:n604. 10.1136/bmj.n604 . Supplementary Files SupplementaryMaterials.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 15 Feb, 2025 Reviewers agreed at journal 07 Jan, 2025 Reviewers invited by journal 07 Jan, 2025 Editor assigned by journal 03 Jan, 2025 First submitted to journal 30 Dec, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5738489","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":398759742,"identity":"da87924d-fd87-47af-a03e-32358b5d0832","order_by":0,"name":"Mei Xue","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Xue","suffix":""},{"id":398759743,"identity":"499ae888-3a39-4ce3-93a5-9ee9b492691d","order_by":1,"name":"Kening Chen","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences \u0026 Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Kening","middleName":"","lastName":"Chen","suffix":""},{"id":398759744,"identity":"8e347640-52e9-45de-9ff0-34e5b225a8d8","order_by":2,"name":"Xiaoqian Zhang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoqian","middleName":"","lastName":"Zhang","suffix":""},{"id":398759745,"identity":"9631ec8c-56e5-4a84-8a12-c9e5a29820a3","order_by":3,"name":"Wenquan Niu","email":"","orcid":"","institution":"Capital Institute of Pediatrics","correspondingAuthor":false,"prefix":"","firstName":"Wenquan","middleName":"","lastName":"Niu","suffix":""},{"id":398759746,"identity":"8fb70f94-4b7a-4f15-adb9-f96c42da53bf","order_by":4,"name":"Zhixin Zhang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+klEQVRIie2QsWoCQRCG91i4ai7bznIHvsIE4UQQfZWFgDZXpJKUCwd5hgv6HNZ7LGgj+gCmCYL1HYRgIaJ3XQpXy0D2K34Y+D+GGcY8nr8ItmmAccbK6m0AQujHlWCP63EiC/OY0gSn6N0OSCu30Znlh6/v02dCq2iJGG6BmAmqOrutBPNlr5vAAWT+NMZX2EGPay4/FrcVjiqNES0IDiki7qCvTcgjhxLi5CdGshA2CtAGyCi3ApilslLtli6BMvcVxGwaM2Ovt8DzHs0LyKLMnbd0islCHk92RNs1lfV5OBIiL6vaobQvgN9zoN39pnK8W/F4PJ5/zQUKPkszxVTsVgAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-4914-1969","institution":"China-Japan Friendship Hospital","correspondingAuthor":true,"prefix":"","firstName":"Zhixin","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-12-31 02:22:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5738489/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5738489/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":73516195,"identity":"03e5adec-061b-4a39-9059-4715113bfdc4","added_by":"auto","created_at":"2025-01-10 17:46:41","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":106067,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Selecting Eligible Children in This Study.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5738489/v1/b740c70139734200e4582d84.jpg"},{"id":73517452,"identity":"0a3c6024-26af-4732-b404-e825b10125a9","added_by":"auto","created_at":"2025-01-10 17:54:41","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":109514,"visible":true,"origin":"","legend":"\u003cp\u003eGestational Diabetes Mellitus (A) or Smoking during Pregnancy (B) and Lifestyle with Comorbidity Risk in Children.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5738489/v1/e965e7757133b5314887fb11.jpg"},{"id":73516194,"identity":"42a17bff-3554-4585-8332-cc2d18a353b6","added_by":"auto","created_at":"2025-01-10 17:46:41","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":110583,"visible":true,"origin":"","legend":"\u003cp\u003eSensitivity Analyses on Gestational Diabetes Mellitus (A) or Smoking during Pregnancy (B) and Lifestyle with Comorbidity Risk in Children Using Unweighted Healthy Lifestyle Score.\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5738489/v1/1c37fc4c888193b42ac835a7.jpg"},{"id":73519697,"identity":"d91f309b-53ec-459d-b64b-d51b7ebc1ea3","added_by":"auto","created_at":"2025-01-10 18:10:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1751612,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5738489/v1/b4bfe0b5-41f4-4f7a-b223-7778e3516804.pdf"},{"id":73516204,"identity":"202635c3-cb48-4412-a659-12541bc982ae","added_by":"auto","created_at":"2025-01-10 17:46:42","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":31156,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryMaterials.docx","url":"https://assets-eu.researchsquare.com/files/rs-5738489/v1/ff138ac153931ee05967cbd7.docx"}],"financialInterests":"","formattedTitle":"Healthy Lifestyles Can Offset Respiratory/Psych-behavioral Comorbidities Due to Gestational Diabetes Mellitus or Prenatal Smoking Exposure in Children Aged 2-16 Years","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRespiratory and psych-behavioral comorbidities are common in children worldwide, and they pose a major burden in pediatric healthcare. Global Burden of Disease Study 2021 estimated that lower respiratory infection, a substantial cause of deaths, is responsible for 0.76\u0026nbsp;million deaths among children under 5 around the global. There is evidence that 8% of children and 15% of adolescents worldwide are living with mental disorders,\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e and this number tends to rise in recent decades. Exhaustive endeavors have been devoted to curb the occurrence and progression of childhood respiratory and psych-behavioral comorbidities, such as vaccination, yet the effect is far from satisfactory. Therefore, the identification of factors that can offset the adverse outcomes of these comorbidities are still subject to ongoing exploration, improvement, and renewal.\u003c/p\u003e \u003cp\u003eThe development of respiratory and psych-behavioral comorbidities is complex and involve a variety of factors, such as gestational diabetes mellitus (GDM) and smoking during pregnancy. On one hand, GDM is a prevalent metabolic disorder during pregnancy marked by hyperglycemia during the second or third trimester.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Research shows that hyperglycemia exposure can affect fetal lung development, causing post-birth respiratory difficulties.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Besides, Chen et al\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e in a population-based study found that GDM diagnosed between the 27th and 30th week of pregnancy was associated with a higher likelihood of attention deficit hyperactivity disorder (ADHD) in childhood. Meta-analytical evidence\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e also consolidates the close link between GDM and prevalent autism spectrum disorder (ASD) in offspring. On the other hand, smoking during pregnancy is prevailing,\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e and prenatal exposure to nicotine has received growing concerns because it can readily cross placental barriers. Studies have shown that nicotine levels in umbilical veins are comparable to those in maternal veins, and nicotine levels in fetal lungs are similar to those in fetal blood.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e There is evidence for an increasing rate of respiratory diseases and psycho-behavioral disorders in children exposed to prenatal maternal smoking.\u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11 CR12 CR13\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e In a pooled analysis of eight European birth cohorts, exposing maternal smoking during pregnancy rather than after birth was found to precipitate the risk of having wheezing and asthma in children aged 4\u0026ndash;6 years,\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e as supported by a national study in Japan,\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e showing a close correlation of maternal smoking before and during pregnancy with incident wheezing in offspring up to three years. Meanwhile, the risk of having ADHD was increased by 60% for children whose mothers smoked during pregnancy.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e GDM and smoking during pregnancy are prenatal adverse events for children, and it is of interest to know whether postnatal healthy lifestyles can offset these events.\u003c/p\u003e \u003cp\u003eNowadays, healthy lifestyles such as eating well-balanced foods, being physically active, lowing screen-seeing time, and having restorative sleep are being advocated in whole society as the upstream drivers and lifestyle medicine to prevent and reverse diseases facing children and adults around the world. Many studies have interrogated the individual contribution of these lifestyle factors to the prevention of asthma\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e and mental health\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e in children, while overlooking their potential combined roles in pulmonary and mental health. Thus far, no study has examined the counterbalancing effect of healthy lifestyles on respiratory and psych-behavioral comorbidities conferred by GDM and smoking during pregnancy.\u003c/p\u003e \u003cp\u003eTo fill this gap in knowledge, we explored the individual and joint association of GDM, smoking during pregnancy and healthy lifestyles with respiratory and psycho-behavioral comorbidities in children, with the goal of testing the hypothesis that healthy lifestyles can offset the increased risk of these comorbidities attributed to GDM and prenatal smoking exposure.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and children\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted in the Pinggu District of Beijing, China, during the period between April and May in 2024. Data were collected using self-designed questionnaires. Total 4,419 valid questionnaires were collected from children aged 2 to 16 years recruited through a combination of stratified random and whole cluster random sampling methods. Children who did not meet age criteria (n\u0026thinsp;=\u0026thinsp;21) and lacked comprehensive medical information (n\u0026thinsp;=\u0026thinsp;353) were excluded, leaving 4,045 children in the final analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The study was conducted in compliance with local legal and institutional guidelines, with data anonymized using unique identifiers. Parental or guardian consents were obtained electronically, with the option for children to opt-outs, as detailed in the consent form.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData collection procedure\u003c/h3\u003e\n\u003cp\u003eData on demographic factors, fetal and neonatal factors (mode of delivery, birth body length, birthweight, pregnancy order, and delivery order), family-related factors (maternal and paternal body mass index [BMI], maternal and paternal childbearing age, maternal and paternal education, family income, gestational diabetes mellitus, smoking during pregnancy, vitamin D supplement during pregnancy, and duration of breastfeeding), and lifestyle factors (diet, physical activity, sleep, and screen time) were collected using standardized questionnaires and procedures. Physical assessments included standardized measurements of height (to the nearest 0.1 cm) and weight (to the nearest 0.1 kg) performed by health practitioners in kindergartens and schools. Details of questions and definitions of each item in our questionnaire are provided in \u003cb\u003eSupplementary materials\u003c/b\u003e.\u003c/p\u003e\n\u003ch3\u003eQuality control\u003c/h3\u003e\n\u003cp\u003eThe quality of our survey data was strictly controlled. Specifically, school health physicians and head teachers were trained to understand the elaborate procedures of this survey and each item in the questionnaire. They were in charge of assisting the parents or guardians of the participating children to fill in the questionnaire. When the survey was completed, data were downloaded from the \u0026ldquo;Wenjuanxing\u0026rdquo; platform and each item was strictly checked. In the case of missing values or apparent outliers, teachers and school healthcare physicians in charge were tasked with reaching out to the parents or guardians of children to obtain or verify necessary information.\u003c/p\u003e\n\u003ch3\u003eDefinition of Comorbidities\u003c/h3\u003e\n\u003cp\u003eIn this research study, comorbidities are defined as the comorbidities of respiratory and psycho-behavioral problems. Guardians are asked to report the children\u0026rsquo;s annual frequency of upper respiratory infection (URI), which encompass common cold, tonsillitis, pharyngitis, laryngitis, sinusitis, and otitis media, as well as lower respiratory tract infection, including tracheobronchitis and pneumonia, with symptom onset intervals exceeding 7 days. Additionally, guardians must confirm if their child has been definitively diagnosed with asthma. Respiratory problems are identified if a child experiences recurrent URI or a definitive asthma diagnosis. To quantify recurrent respiratory infections, the following criteria are applied: for children aged 2\u0026ndash;5 years, more than 6 URI episodes per year or more than 2 lower respiratory infections per year; for children over 5 years, more than 5 URI episodes per year or more than 2 lower respiratory infection per year, with symptom onset intervals exceeding 7 days. Respiratory problems are characterized by either recurrent infections or a definitive asthma diagnosis.\u003c/p\u003e \u003cp\u003eFor psycho-behavioral assessment, guardians completed the Conners Parent Symptom Questionnaire (PSQ), a 48-item scale with six subscales, including conduct problems, learning difficulties, psychosomatic disorders, impulsivity/hyperactivity, anxiety, and a hyperactivity index. Responses are recorded on a 4-point frequency scale from never to frequently, with higher scores indicating more severe symptoms. Furthermore, guardians are queried about potential definitive diagnoses of autism, ADHD, and tic disorders.\u003c/p\u003e\n\u003ch3\u003eGDM and smoking during pregnancy\u003c/h3\u003e\n\u003cp\u003eGDM (\u0026ldquo;Does the mother have gestational diabetes?\u0026rdquo; The answer is yes or no) and smoking during pregnancy (\u0026ldquo;Did the child\u0026rsquo;s mother smoke actively or passively during pregnancy?\u0026rdquo; (Active smoking is defined as mothers who smoke more than 10 cigarettes a day. Passive smoking is defined as more than 1 day a week in the inhalation of smokers exhaled smoke time\u0026thinsp;\u0026gt;\u0026thinsp;15min/ day). The answer is yes or no) were reported by their parents.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eHealthy lifestyle score\u003c/h2\u003e \u003cp\u003eA composite healthy lifestyle score was established for children, incorporating four key behaviors - diet, physical activity, screen time, and sleep duration. These behaviors were categorized as healthy or unhealthy based on established guidelines. Participants received one point for each healthy behavior, resulting in a score range of 0 to 4, with higher scores indicating healthier habits. The criteria for regular physical activity and healthy screen time were adapted from the WHO Guidelines on Physical Activity and Sedentary Behavior,\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e recommending that children engage in at least 60 minutes of moderate to vigorous-intensity physical activity daily, spread across the week. Screen time, defined as the sum of recreational time spent watching television, and using tablets or smartphones, should be limited to less than 2 hours per day according to these guidelines.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e Sleep duration guidelines vary by ages and were referenced from the recommendations of the American Academy of Sleep Medicine.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Healthy diet was formulated in alignment with the Dietary Guidelines for Chinese Residents (2016), encompassing 14 food items. Intakes of rice, pasta, fruits, vegetables, soy, eggs, dairy, meat, poultry, aquatic products, and nuts were deemed healthy, while that of desserts, fried foods, preserved foods, and sugary beverages unhealthy. These dietary components have been correlated with childhood respiratory or psycho-behavioral problems. Lifestyle score was further stratified into unfavorable (0 or 1 healthy factor), moderate (2 healthy factors), and favorable (3 or 4 healthy factors) categories based on population distribution. Although this simple additive approach has been widely used,\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e the underlying assumption is that the association between different lifestyle factors and outcomes is identical, which may not be the case in practice. Consequently, a weighted lifestyle score was developed. This score was calculated by multiplying each binary lifestyle variable by its corresponding β coefficient from a Logistic regression model after adjusting for age and sex, summing these products, dividing by the total of the β coefficients, and then multiplying by 100.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e Weighted standardized scores were then categorized into favorable, moderate, and unfavorable groups based on their distributions.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical analyses\u003c/h3\u003e\n\u003cp\u003eContinuous variables are presented as mean (standard deviation [SD]) or median (interquartile range); categorical variables as percentages. The t-test or rank-sum test was used for continuous variables, while the χ\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e test was for categorical variables. Logistic regression was applied to compute odds ratio (OR) for comorbidities in children, with those without comorbidities serving as the control group. Three models were constructed: model 1 was unadjusted; model 2 included adjustment for age and sex; model 3 included further adjustment for maternal obesity, maternal education level, mode of delivery, maternal age at childbearing, vitamin D supplementation during pregnancy, duration of breastfeeding, smoking during pregnancy (or GDM), and weighted healthy lifestyle score. The selection of covariates was based on expert knowledge regarding clinically significant risk factors for respiratory and psycho-behavioral disorders in children, as well as literature identifying suspected or established factors associated with exposure or outcomes. Data were grouped by combining GDM or smoking during pregnancy with lifestyle factors (all six categories, with the absence of GDM and a healthy lifestyle or non-smoking during pregnancy and a healthy lifestyle as the reference group) to investigate the association between adverse prenatal factors and postnatal lifestyle factors with the risk of respiratory and psycho-behavioral comorbidities in children aged 2\u0026ndash;16 years. The joint correlation Logistic regression model was fully adjusted. To ensure the robustness of the regression model, a sensitivity analysis using unweighted lifestyle scores was done. All reported P values were two-tailed, with a threshold of less than 0.05 being statistically significant. Data were analyzed within November, 2024 using STATA software (version 16.0, Stata Corp, College Station, Texas, USA) and R coding platform (version 4.3.3).\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eAfter excluding invalid or incomplete or unqualified questionnaires (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), data from 4045 children were analyzed in this study, comprising 1964 girls and 2081 boys; the response rate was 92%. The baseline characteristics of all eligible children are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Of all children, 614 were identified with comorbid respiratory and psycho-behavioral conditions, with a prevalence rate of 15.18% in this population. Overall, healthy lifestyles were adopted by 29.57% of all children. During pregnancy, GDM was present in 402 mothers (9.94%), and 221 mothers (5.46%) smoked while pregnant. Generally, children with comorbidities tended to be younger and more likely to have an intermediate or unhealthy lifestyle.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBasic Characteristics of Study Children\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbsence of Comorbidities\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;3431)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePresence of Comorbidities\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;614)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.16 [6.95, 13.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.01 [4.76, 10.47]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1740 (50.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e341 (55.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1691 (49.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e273 (44.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e156 [127, 167]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120 [110, 150]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 [27, 60]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6 [19, 44]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.94 [16.09, 23.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.67 [15.01, 20.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSiblings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1775 (51.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e298 (48.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1656 (48.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e316 (51.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRespiratory problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e304 (8.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e614 (100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsycho-behavioral problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1398 (40.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e614 (100.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFetal and neonatal factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaginal delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1506 (43.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e291 (47.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCesarean section\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1758 (51.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e285 (46.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransferred from vaginal delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155 (4.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (5.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eForceps delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (0.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth body length\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 [50, 52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 [50, 52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3400 [3000, 3650]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3300 [3000, 3600]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePregnancy order\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2586 (75.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e874 (70.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e845 (24.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e372 (29.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery order\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2107 (61.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e306 (49.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1324 (38.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e308 (50.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily-related factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal BMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.23 [21.10, 25.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.72 [21.23, 26.45]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaternal BMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.83 [23.59, 27.78]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25.83 [23.88, 28.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal childbearing age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 [25, 30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29 [26, 32]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaternal childbearing age\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 [26, 32]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 [28, 33]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal education (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school degree or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1172 (34.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e156 (25.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2185 (63.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e440 (71.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster\u0026rsquo;s degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (2.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePaternal education (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school degree or below\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1439 (41.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227 (36.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor\u0026rsquo;s degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1907 (55.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e382 (62.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster\u0026rsquo;s degree or above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (2.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (0.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily income (RMB per year) (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1003 (39.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e193 (42.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100,000\u0026ndash;300,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1278 (50.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216 (47.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;300,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e239 (9.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43 (9.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGestational diabetes mellitus\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305 (8.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97 (15.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3126 (91.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e517 (84.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking during pregnancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e165 (4.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (9.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3266 (95.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e558 (90.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eVitamin D supplement during pregnancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;3 months strictly following doctor\u0026rsquo;s advice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2265 (66.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e363 (59.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;3 months strictly following doctor\u0026rsquo;s advice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e321 (9.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (12.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot strictly following doctor\u0026rsquo;s advice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e344 (10.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92 (14.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever supplemented\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e501 (14.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85 (13.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDuration of breastfeeding (months)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 [8, 15]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 [8, 17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLifestyle-related information\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealthy Lifestyle factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthy diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1848 (53.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282 (45.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegular physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e175 (5.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (2.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthy screen time\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2826 (82.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e485 (79.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdequate sleep\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2124 (61.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e339 (55.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo. of healthy lifestyle factors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (4.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32 (5.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e739 (21.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181 (29.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1481 (43.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e272 (44.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e996 (29.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122 (19.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71 (2.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (1.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWeighted healthy lifestyle score\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35.79 [24.90, 56.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.52 [20.62, 45.53]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealthy lifestyle category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealthy lifestyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1067 (31.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129 (21.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate lifestyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1481 (43.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e272 (44.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnhealthy lifestyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e883 (25.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213 (34.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMaternal factors and childhood comorbidity\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e delineates the association between maternal factors and respiratory and psycho-behavioral comorbidities in children. After multiple adjustment for potential confounders including age, sex, maternal obesity, maternal educational level, mode of delivery, maternal age at childbearing, vitamin D supplementation during gestation, duration of breastfeeding, smoking status during pregnancy (or GDM), and weighted healthy lifestyle score, the risk of respiratory and psycho-behavioral comorbidities was significantly higher in children whose mothers had a history of GDM than children whose mothers had no GDM (OR\u0026thinsp;=\u0026thinsp;1.40; 95% CI: 1.07\u0026ndash;1.82). Likewise, children whose mothers smoked during pregnancy were 1.71 times more likely to have these comorbidities than children whose mothers did not smoke during pregnancy (OR\u0026thinsp;=\u0026thinsp;1.71; 95% CI: 1.22\u0026ndash;2.40).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGestational diabetes mellitus or Smoking during Pregnancy and Comorbidity Risk in Children\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSubgroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo. of children with comorbidities/No. of total children\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGestational diabetes mellitus (GDM)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWithout GDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e517 / 3643\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWith GDM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e97 / 402\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.92 (1.50, 2.46)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.47 (1.14, 1.90)\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.40 (1.07, 1.82)\u003c/b\u003e\u003csup\u003e\u003cb\u003e*\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSmoking during pregnancy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-exposed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e558 / 3824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 / 221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.98 (1.45, 2.73)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.87 (1.35, 2.60)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.71 (1.22, 2.40)\u003c/b\u003e\u003csup\u003e\u003cb\u003e**\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLifestyle categories and childhood comorbidities\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e elucidates the association between adherence to healthy lifestyles and the risk of respiratory and psycho-behavioral comorbidities in children. Adjusting for age and sex revealed that comorbidity risk was increased with the increasing number of unhealthy lifestyle factors. Specifically, children who had unhealthy lifestyle practices were nearly twice as likely to experience these comorbidities compared to children with healthy lifestyle habits (OR\u0026thinsp;=\u0026thinsp;1.98; 95% CI: 1.54\u0026ndash;2.53). Fully-adjusted OR was reinforced for this association (OR\u0026thinsp;=\u0026thinsp;1.91; 95% CI: 1.48\u0026ndash;2.45).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLifestyle Categories and Comorbidity Risk in Children\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSubgroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo. of children with comorbidities/No. of total children\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eModel 1\u003c/b\u003e \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eModel 2\u003c/b\u003e \u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eModel 3\u003c/b\u003e \u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHealthy lifestyle categories\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth lifestyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e129 / 1196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 [Ref]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntermediate lifestyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e272 / 1753\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1.55 (1.24, 1.94)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.54 (1.22, 1.94)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.54 (1.22, 1.95)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnhealthy lifestyle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e213 / 1096\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.01 (1.58, 2.54)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.98 (1.54, 2.53)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e1.91 (1.48, 2.45)\u003c/b\u003e\u003csup\u003e\u003cb\u003e***\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e \u003cb\u003efor trend\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCombined maternal and lifestyle factors with childhood comorbidities\u003c/h2\u003e \u003cp\u003eWhen GDM or smoking during pregnancy were combined with various lifestyle categories, the consistent association with childhood comorbidities was observed. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e provides the fully-adjusted ORs for the combined effect of maternal factors and lifestyle categories on respiratory and psycho-behavioral comorbidities in children. Notably, the co-occurrence of both GDM and unhealthy lifestyle was associated with a markedly increased risk of comorbidities compared to children whose mothers had no GDM and who had unhealthy lifestyle practices (OR\u0026thinsp;=\u0026thinsp;2.08; 95% CI: 1.23\u0026ndash;3.49). Similarly, the combination of maternal smoking during pregnancy and unhealthy lifestyle significantly amplified the risk of comorbidities in childhood relative to children whose mothers did not smoke during pregnancy and who adhered to healthy lifestyle (OR\u0026thinsp;=\u0026thinsp;3.72; 95% CI: 2.11\u0026ndash;6.56). However, adherence to healthy lifestyle appeared to offset the heightened risk conferred by GDM (OR\u0026thinsp;=\u0026thinsp;1.42; 95% CI: 0.81\u0026ndash;2.48) and smoking during pregnancy (OR\u0026thinsp;=\u0026thinsp;1.29; 95% CI: 0.50\u0026ndash;3.31).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSubgroup analyses by age and sex showed no statistical significance for comorbidity risk in children who had healthy lifestyles and whose mothers had GDM or smoked during pregnancy compared with children who adhered to healthy lifestyles and whose mothers neither had GDM nor smoked during pregnancy (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Consistent trends were observed when utilizing unweighted healthy lifestyle score, as depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, further emphasizing the protective role of healthy lifestyle against the development of respiratory and psycho-behavioral comorbidities in children.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSubgroup Analyses on Healthy Lifestyle and Comorbidity Risk Conferred by Gestational Diabetes Mellitus (GDM) or Smoking during Pregnancy\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSubgroups\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eHealth Lifestyle with Gestational Diabetes Mellitus (GDM)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eHealth Lifestyle with Smoking during Pregnancy\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u0026ndash;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.70, 4.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.36, 6.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.52, 2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.14, 3.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.11, 6.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.19, 4.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoys\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53, 2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.54, 4.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGirls\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68, 3.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.05, 4.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eVia a comprehensive analysis of survey data from 4045 children currently living in Beijing, our findings supported the hypothesis that healthy lifestyle can offset the increased risk of respiratory and psycho-behavioral comorbidities in children that were attributed to prenatal GDM and smoking during pregnancy, indicating that advocating healthy lifestyles in children can be proposed as a method for primary prevention of respiratory and psycho-behavioral comorbidities, especially in children whose mothers have exposed to GDM or smoking during pregnancy. To our knowledge, this is thus far the first study that has investigated the synergistic effect of healthy lifestyle and adverse prenatal exposure on following childhood respiratory and psycho-behavioral comorbidities.\u003c/p\u003e \u003cp\u003eMounting evidence suggests that respiratory disorders and mental problems are common in children and profoundly affect children\u0026rsquo;s healthy growth and development.\u003csup\u003e\u003cspan additionalcitationids=\"CR27 CR28 CR29 CR30 CR31\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e From a prospective viewpoint, maternal health status during pregnancy is pivotal for fetal growth and future health of offspring. Currently, a variety of prenatal factors have been established to significantly influence the development of respiratory and psycho-behavioral problems in children, practically GDM and smoking during pregnancy.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e Consistent with the findings of prior studies,\u003csup\u003e\u003cspan additionalcitationids=\"CR34 CR35 CR36\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e we found that children whose mothers had a history of GDM or smoked during pregnancy had a significantly higher risk of experiencing respiratory and psycho-behavioral comorbidities than those without these adverse exposure, even after taking a wide panel of confounders into consideration, indicating the robustness of our findings. In practice, respiratory disorders and mental problems are interlinked, as respiratory disorders such as asthma often lead to breathing difficulties, which in return may trigger the development of anxiety and depression due to consistent physical discomfort. Moreover, children with respiratory disorders are often physically inactive and not good at social interaction, which could precipitate the occurrence of loneliness and depression.\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e From a biological aspect, respiratory disorders are featured by inflammation, which may contribute to cognitive dysfunction and indirectly influence mood and behavior by affecting circulating neurotransmitters and neuronal health.\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e Prior studies have assessed childhood respiratory disorders and mental problems individually, overlooking their co-occurring roles and overlapped underlying causes. To shed more light on this issue, we in a general children population from Pinggu district of Beijing attempted to seek potential avenues that can prevent the occurrence of respiratory and psycho-behavioral comorbidities attributed to GDM or smoking during pregnancy.\u003c/p\u003e \u003cp\u003eLifestyle practices are modifiable and represent largely untapped opportunity to mitigate the adverse outcomes of children under the exposure of prenatal GDM and smoking during pregnancy. Lifestyle factors are multifaceted, mainly including diet, physical activity, screen time, and sleep; they hold significant potentials for health and well-being. For instance, diet can significantly influence allergic diseases, including asthma, by modulating airway inflammation through antioxidant-rich foods like fruits, vegetables, and whole grains.\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e A well-balanced diet might potentially alleviate both systemic and airway inflammation in children with asthma.\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e Additionally, research has shown that balanced diet is beneficial for better mental health and better cognition, as evidenced by a large-scale study involving 180,000 participants.\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e Likewise, physical activity also plays a crucial role in asthma prevention and management; moderate-to-vigorous exercise can reduce asthma risk and improving airway responsiveness.\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e Clinically, physical activity has an immediate positive influence on the airway smooth muscle, leading to a reduction in airway responsiveness.\u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e Exercise is also linked to better mental health outcomes in children, as shown in a meta-analysis of 13 studies involving 115,540 children.\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e Children who engaged in physical activity were reported to have mental well-being for both genders.\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e Above lines of evidence collectively highlight the significant roles of healthy lifestyles in the prevention of adverse respiratory and psycho-behavioral conditions in children.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan additionalcitationids=\"CR49 CR50\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e Most prior studies merely focused on one or few lifestyle factors, and frequently neglected the their joint contribution to childhood respiratory and psycho-behavioral comorbidities. Extending the findings of prior studies, we generated a weighted healthy lifestyle score by comprehensively assessing various lifestyle related factors (diet, sleep, physical activity, and screen time), and provided the first-ever evidence that children with unhealthy lifestyles faced a significantly higher risk of developing respiratory and psycho-behavioral comorbidities compared to their peers with healthy lifestyles, and importantly adhering to healthy lifestyles might offset the increased risk of these comorbidities resulting from GDM or smoking during pregnancy.\u003c/p\u003e \u003cp\u003eStrengths of this study include an extensive sampling of children from Beijing, a high response rate, and a comprehensive analysis of the combined effect of recommended lifestyle changes on respiratory and psycho-behavioral problems in children. However, some limitations should be acknowledged when interpreting our findings. Firstly, due to the cross-sectional design of this survey, causality cannot be established. Secondly, our study was based on data from children 2\u0026ndash;16 years of age living in a district of Beijing, and extrapolation of our findings to other regions or races should be made with caution. Thirdly, in this survey, data were collected via parents-reported electronic questionnaires, leaving recall or reporting bias an open question, although we had implemented strict quality control. Our findings presented here are preliminary, and further investigations are urgently needed to elucidate and substantiate our results by incorporating more data in other independent groups.\u003c/p\u003e \u003cp\u003eTaken together, our findings indicated that adherence to healthy lifestyles might offset the increased risk of childhood respiratory and psycho-behavioral comorbidities that were attributed to prenatal GDM or smoking during pregnancy. For practical reasons, through unraveling the potential protective roles of healthy lifestyles, we can inform public health initiatives and clinical advice to assist families in fostering the health and well-being of their children, especially those with adverse prenatal exposure. To achieve this goal, further research is necessary to clarify and affirm our findings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e This study was approved by the Ethics Committee of the China-Japan Friendship Hospital (2024-KY-086), and all participants and their parents provided informed consents voluntarily.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material:\u0026nbsp;\u003c/strong\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest and no financial or non-financial benefits have been received or will be received from any party related directly or indirectly to the subject of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This work was supported by the Public Service Development and Reform Pilot Project of Beijing Medical Research Institute (W. Niu), the Capital\u0026rsquo;s Funds for Health Improvement and Research (Grant Number: 2024-2-1133), and the National Natural Science Foundation of China (Grant Number: 81970042).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u003c/strong\u003e Z.Z. and W.N. designed the study. X.Z. and Z.Z. obtained ethics approvals and contributed to data acquisition. M.X. and K.C. performed the statistical analysis and wrote the first draft. Z.Z. and W.N. are the study guarantors. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003eWe are grateful to all participating children and their parents or grandparents for their cooperation and willingness.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. Improving the mental and brain health of children and adolescents. 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Associations of healthy lifestyle and socioeconomic status with mortality and incident cardiovascular disease: two prospective cohort studies. Bmj Apr. 2021;14:373:n604. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/bmj.n604\u003c/span\u003e\u003cspan address=\"10.1136/bmj.n604\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"italian-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"itjp","sideBox":"Learn more about [Italian Journal of Pediatrics](http://ijponline.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ITJP/default.aspx","title":"Italian Journal of Pediatrics","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Healthy lifestyle, Respiratory and psycho-behavioral comorbidities, Gestational diabetes mellitus, Smoking during pregnancy","lastPublishedDoi":"10.21203/rs.3.rs-5738489/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5738489/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eAim\u003c/h2\u003e \u003cp\u003eThe aim of this study was to test whether healthy lifestyles can offset the increased risk of childhood respiratory and psycho-behavioral comorbidities attributed to gestational diabetes mellitus (GDM) or prenatal smoking exposure.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFrom April to May 2024, we conducted a cross-sectional cluster sampling of children aged 2\u0026ndash;16 years in Beijing. Fetal and neonatal related factors, family-related factors, and lifestyle-related information were collected through an electronic questionnaire. A weighted healthy lifestyle score was calculated by aggregating diet, physical activity, sleep time, and screen time; it was categorized into healthy, intermediate and unhealthy lifestyles. Logistic regression was used to estimate odds ratio (OR) and 95% confidence interval (95% CI) for the association of GDM or smoking during pregnancy with respiratory and psych-behavioral comorbidities. Interaction terms were used to explore the offsetting effect of lifestyle factors.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of respiratory and psych-behavioral comorbidities among Chinese children aged 2\u0026ndash;16 years was 15.18%. GDM and smoking during pregnancy were associated with an increased risk of childhood comorbidities (multi-adjusted OR, 95% CI: 1.40, 1.07\u0026ndash;1.82 and 1.71, 1.22\u0026ndash;2.40). Children with unhealthy lifestyles faced a significantly higher risk of developing comorbidities compared to their peers with healthy lifestyles (1.91; 1.48\u0026ndash;2.45). Adhering to healthy lifestyles can offset the increased risk of childhood comorbidities due to GDM (1.42, 0.81\u0026ndash;2.48) or smoking during pregnancy (1.29, 0.50\u0026ndash;3.31).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eOur findings indicated that adherence to healthy lifestyles might offset the increased risk of childhood respiratory and psycho-behavioral comorbidities that were attributed to prenatal GDM or smoking during pregnancy.\u003c/p\u003e","manuscriptTitle":"Healthy Lifestyles Can Offset Respiratory/Psych-behavioral Comorbidities Due to Gestational Diabetes Mellitus or Prenatal Smoking Exposure in Children Aged 2-16 Years","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-01-10 17:46:37","doi":"10.21203/rs.3.rs-5738489/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2025-02-16T04:03:52+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-01-07T11:07:58+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-01-07T09:17:57+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-03T12:28:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Italian Journal of Pediatrics","date":"2024-12-30T21:19:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"italian-journal-of-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"itjp","sideBox":"Learn more about [Italian Journal of Pediatrics](http://ijponline.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ITJP/default.aspx","title":"Italian Journal of Pediatrics","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9b9aea3e-6dc0-4d80-8894-b86e7f60a430","owner":[],"postedDate":"January 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-03-05T10:02:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-01-10 17:46:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5738489","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5738489","identity":"rs-5738489","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}