Factors Associated with Psycho-behavioral Problems among 100 Phenylketonuria Children Aged 6-18 Years

Factors Associated with Psycho-behavioral Problems among 100 Phenylketonuria Children Aged 6-18 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 Factors Associated with Psycho-behavioral Problems among 100 Phenylketonuria Children Aged 6-18 Years Mei Xue, Wenquan Niu, Ming Shen, Shunan Wang, Bo Pang, Xiaoqian Zhang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5298122/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Jun, 2025 Read the published version in Orphanet Journal of Rare Diseases → Version 1 posted 5 You are reading this latest preprint version Abstract Background Phenylketonuria (PKU) is a rare condition, and children diagnosed with PKU often face psycho-behavioral challenges, which can significantly impact their daily lives and social integration. Our objective was to evaluate the prevalence of psycho-behavioral difficulties and explore potential factors associated with their occurrence in PKU children aged 6–18 years. Methods From May 2022 to May 2024, we recruited 100 children with PKU using a questionnaire survey. Data were analyzed using STATA software and the R programming language. Results 25% of children aged 6–18 years with PKU exhibited psycho-behavioral problems. Following multivariable adjustment, significant factors associated with these psycho-behavioral problems in the children were body mass index (BMI) (odds ratio, 95% CI, P: 95% CI: 1.135, 1.010–1.276, 0.033), age (3.169, 1.024–9.804, 0.045), pregnancy order (0.143, 0.033–0.607, 0.008), delivery order (0.041, 0.004–0.373, 0.005), mode of disease diagnosis (5.730, 1.935–16.963, 0.002), and dietary therapy pressure (3.321, 1.083–10.181, 0.036). A nomogram was constructed based on above significant factors, with descent prediction capability and accuracy. Conclusions Six factors were identified to be closely associated with psycho-behavioral problems in PKU children. Our findings provide insights into the risk profiles behind psycho-behavioral issues in PKU, potentially enabling the development of preventive strategies. phenylketonuria rare disease children factors psycho-behavioral problems Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Phenylketonuria (PKU), a genetic metabolic disorder affecting approximately 1 in 10,000 to 1 in 15,000 individuals globally,(1) is characterized by a deficiency in the phenylalanine hydroxylase (PAH) enzyme, which is pivotal for the metabolism of the amino acid phenylalanine (Phe). The subsequent accumulation of Phe in the bloodstream and brain can lead to a spectrum of neurodevelopmental challenges if allowed to proceed untreated, including severe intellectual disability and psycho-behavioral complications.(2) , (3) Despite the advent of neonatal screening and dietary management, children with PKU may still face psycho-behavioral issues that can impact quality of life and social integration.(4) , (5) The importance of focusing psycho-behavioral problems in PKU cannot be overstated.(6) These issues, if left untreated, can lead to long-term social and emotional difficulties, affecting not only individuals but also their families and societies. The necessity of this research is further highlighted by the limitations in existing literature, which mainly focuses on metabolic aspects of PKU, overlooking the psychological and social implications.(7, 8) Prior studies have reported a range of psycho-behavioral challenges in PKU, including attention deficit, mood disorders, and social cognitive deficits, yet how many factors are responsible for these issues thus far remain poorly understood.(2, 9, 10) This study aimed to explore potential factors associated with psycho-behavioral problems in PKU children aged 6–18 years, with a particular focus on birth history, disease-related factors, metabolic control, and family-related factors. METHODS Study design We conducted a cross-sectional survey from May 2022 to May 2024. The Ethics Committee of China-Japan Friendship Hospital reviewed and approved the protocols of this survey, and this study was implemented according to the Declaration of Helsinki. Study participants The study participants consisted of PKU children from the pediatric clinic of China-Japan Friendship Hospital. The parents or guardians of participating students provided signature consent to the participation of this survey, with opt-out clauses in our consent form. Study participants were restricted to children aged 6 to 18 years, who have received a definitive diagnosis of PKU from a qualified clinician. Participants were excluded if they met any of the following criteria: (1) BH4 deficiency and DNAJC12 biallelic mutation; (2) guardians cannot provide reliable medical history; (3) prior diagnosis of familial or hereditary mental health disorders; (4) suffering from other chronic diseases that may precipitate psycho-behavioral problems. Data collection We collected data by self-designed questionnaires. To ensure the reliability of tour questionnaires, both questionnaires were distributed in small samples before formal circulation, and had a reliability coefficient (alpha) over 0.85. The questionnaire includes the following parts: (1) demographic information: age, sex, height, weight, body mass index (BMI), and region; (2) fetal and neonatal factors: birth length, birth weight, delivery mode, pregnancy order, and delivery order; (3) family-related factors: maternal education level, paternal education level, and family income. (4) disease-related information: disease diagnosis mode, age of initial treatment (month), highest Phe before treatment, recent Phe, average Phe per year, diet therapy pressure (no, yes), follow-up period, and control situation; (5) psycho-behavioral part: the Conners Parent Symptom Questionnaire (PSQ) and the Hospital Anxiety and Depression Scale (HADS) used to evaluate the psycho-behavioral status. Quality control The questionnaires were all recorded by two experienced doctors in toutpatient department, and they were responsible for assisting in parents or guardians of participating patients to understand and fill out questionnaire. The dissenting part was ruled by a doctor with higher seniority. All information was independently typed into an Excel sheet by two researchers (M.X. and B.P.). Disagreement was adjudicated by a third researcher (M.S.). Physicians would contact the parents or guardians of participants to resupply or confirm information which were missing or obviously abnormal in the questionnaires. Definitions of PKU and psycho-behavioral problems In this study, we adopted the clinical practice guidelines for PKU to define it.(11) The Parent Symptom Questionnaire (PSQ)(12) is a widely recognized assessment tool for children’s psychological and behavioral issues. It features 48 items completed by parents, with each scored on a scale of 0 to 3. The PSQ evaluates six key factors: conduct problems, learning problems, psychosomatic issues, impulsive-hyperactivity, anxiety, and a hyperactivity index. To determine the average score for each factor, individual scores were summed and divided by the number of items. A factor score above 1.5 (or two standard deviations from the norm) is deemed as abnormal. The Hospital Anxiety and Depression Scale (HADS)(13) is a prevalent screening tool for mental health issues in the context of physical illness. It consists of 14 items that measure anxiety and depression. Scores are categorized as follows: 0–7 for no symptoms, 8–10 for possible symptoms, and 11–21 for the presence of symptoms. If the score of each factor in the PSQ questionnaire is greater than 1.5 points, the value is 1, 0 otherwise. In the HADS questionnaire, 0–7 scores were assigned as 0, 8–10 scores were assigned as 1, 11–21 scores were assigned as 2. In this study, we defined psycho-behavioral problems as PSQ questionnaire score and/or HADS questionnaire score ≥ 2, and no psycho-behavioral problems otherwise. Definitions of other items Delivery modes included vaginal delivery and caesarean section. Gestational age was used to distinguish between term and preterm. Birth body length (to the nearest 0.1 cm) was reported by the parents or guardians of participant students. Pregnancy order and delivery order meant the times of pregnancy and bearing birth, respectively. Family education was the highest level of education of parents and was categorized as master's degree or above, bachelor's degree, and high school degree or below. Family income (RMB per year) was categorized as ≥ 100,000, 50,000-100,000, and < 50,000. Disease diagnosis mode includes neonatal screening and clinical diagnosis. The age of initial treatment was measured in months. Average Phe per year was categorized as 2–6 mg/dL, 6–10 mg/dL, and > 10 mg/dL. Follow-up period included 4 times a year and less than 4 times a year. The control situation was divided according to age and the standard blood value of the corresponding age. Statistical Analyses Data were analyze utilizing the STATA software (version 18.0) and R programming environment (version 4.3.3). The expression of continuous variables was mean (standard deviation) if no deviation from normal distribution tested by the skewness and kurtosis test, and median (interquartile range) otherwise. The expression of categorical variables was count (percent). Between-group comparisons (PKU children with versus without psycho-behavioral problems) of variables were conducted using appropriate statistical tests, including the t-test for parametric data, the χ 2 test for categorical data, and the rank-sum test for non-parametric data. To identify statistically significant risk factors for psycho-behavioral problems among PKU children, logistic regression analyses were done without considering any confounders and then adjusted for sex, region, family income, maternal education level, and paternal education level in multivariable adjustment models to examine their independence. Effect-size estimates are expressed as odds ratio (OR) and 95% confidence interval (95% CI). The enhancement in predictive accuracy achieved through the incorporation of significant factors into the basic model was comprehensively evaluated from both calibration and discrimination perspectives. On the calibration side, the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were leveraged to assess the degree of congruence between the predicted probabilities, incorporating these factors, and the actual observed risks. Furthermore, these criteria served to evaluate the overall suitability and goodness-of-fit of the refined risk model. From a discrimination standpoint, the Receiver Operating Characteristic (ROC) curve analysis for both the original and modified models was conducted. Finally, a predictive nomogram for risk assessment was developed, incorporating key influential factors to improve its utility in clinical settings and public health initiatives. This model was created using R version 4.3.3 for Windows. RESULTS Baseline characteristics After rigorous screening to eliminate unqualified questionnaires, data from 100 children diagnosed with PKU (detailed selection procedure is shown in Fig. 1 .), comprising 54 girls and 46 boys, were analyzed, with 25 children exhibiting psycho-behavioral problems, reflecting a prevalence rate of 25% for such issues among PKU children. The baseline characteristics of all participating children are presented in Table 1 according to the presence and absence of psycho-behavioral problems. Table 1 The baseline characteristics of study children. Characteristics Children without Psycho-behavioral problem Children with psycho-behavioral problem p (n = 75) (n = 25) Demographic information Age (years) 0.003 6–12 59 (78.7) 12 (48.0) 12–18 16 (21.3) 13 (52.0) Sex 0.247 Boys 32 (42.7) 14 (56.0) Girls 43 (57.3) 11 (44.0) Height (cm) 136 (128, 155) 138.5 (126, 155) 0.939 Weight (kg) 32 (25, 46) 39 (28, 55) 0.200 BMI (kg/m 2 ) 16.8 (15.2, 20.7) 19.5 (16.0, 22.2) 0.118 Region 0.006 City 58 (77.3) 12 (48.0) Country 17 (22.7) 13 (52.0) Fetal and neonatal factors Birth length (cm) 50 (50, 51) 50 (49, 50) 0.036 Birth weight (kg) 3200 (2900, 3500) 3000 (2650, 3400) 0.159 Delivery mode 0.096 Vaginal delivery 43 (57.3) 19 (76.0) Cesarean section 32 (42.7) 6 (24.0) Pregnancy order 1 (1, 2) 1 (1, 1) 0.034 Delivery order 1 (1, 2) 1 (1, 1) 0.005 Family-related factors Maternal education level 0.258 High school degree or below 37 (49.3) 16 (64.0) Bachelor’s degree 33 (44.0) 9 (36.0) Master’s degree or above 5 (6.7) 0 (0) Paternal education level 0.376 High school degree or below 39 (52.0) 17 (68.0) Bachelor’s degree 32 (42.7) 7 (28.0) Master’s degree or above 4 (5.3) 1 (4.0) Family income (RMB per year) 0.335 100, 000 26 (34.7) 5 (20.0) Disease-related information Disease diagnosis mode < 0.001 Neonatal screening 62 (82.7) 11 (44.0) Clinical diagnosis 13 (17.3) 14 (56.0) Age of initial treatment (month) 2 (1, 19) 1 (1, 17) 0.599 Highest Phe before treatment 20 (11, 31) 22 (19, 24) 0.454 Recent Phe 7.9 (5.85, 12) 6 (3.63, 12.75) 0.245 Average Phe per year (mg/dL) 0.339 2–6 32 (42.7) 11 (44.0) 6–10 28 (37.3) 6 (24.0) > 10 15 (20.0) 8 (32.0) Diet therapy pressure 0.007 No 64 (89.3) 15 (60.0) Yes 11 (14.7) 10 (40.0) Follow-up period 0.899 ≥ 4 times a year 53 (70.7) 18 (72.0) < 4 times a year 22 (29.3) 7 (28.0) Control situation 0.817 Well control 38 (50.7) 12 (48.0) Poor control 37 (49.3) 13 (52.0) Data are expressed as median (interquartile range) or count (percent). P value was calculated by the rank-sum test or the χ 2 test, where appropriate. Abbreviations: BMI, body mass index. Identification of contributing predictors Baseline variables shown in Table 1 were selected based on clinical relevance or with a P value < 0.05 on univariate analysis, and considered as candidate variables. After adjusting for sex, region, income, paternal education level, and maternal education level, six factors (BMI, age, pregnancy order, delivery order, disease diagnosis mode, and diet therapy pressure) were associated with the significant factors of PKU children with psycho-behavioral problems, as shown in Table 2 . For example, the significant odds of having psycho-behavioral problems was 1.135 (95% CI: 1.010–1.276, P = 0.033) for BMI, 3.169 (95% CI: 1.024–9.804, P = 0.045) for age, 0.143 (95% CI: 0.033–0.607, P = 0.008) for pregnancy order, 0.041 (95% CI: 0.004–0.373, P = 0.005) for delivery order, 5.730 (95% CI: 1.935–16.963, P = 0.002) for disease diagnosis mode, and 3.321 (95% CI: 1.083–10.181, P = 0.036) for diet therapy pressure. Table 2 Identification of potential factors responsible for PKU children with psycho-behavioral problem. Significant variables Unadjusted model Multivariable adjusted model OR 95% CI p OR 95% CI p BMI 0.950 0.927 to 0.972 < 0.001 1.135 1.010 to 1.276 0.033 Age 3.994 1.530 to 10.428 0.005 3.169 1.024 to 9.804 0.045 Pregnancy order 0.302 0.092 to 0.992 0.049 0.143 0.033 to 0.607 0.008 Delivery order 0.098 0.013 to 0.749 0.025 0.041 0.004 to 0.373 0.005 Highest Phe before treatment 0.961 0.942 to 0.979 < 0.001 0.993 0.956 to 1.031 0.726 Recent Phe 0.902 0.859 to 0.947 < 0.001 0.985 0.897 to 1.081 0.750 Age of initial treatment 0.971 0.948 to 0.995 0.018 0.986 0.964 to 1.007 0.199 Delivery mode 0.442 0.257 to 0.758 0.003 2.307 0.785 to 6.783 0.129 Disease diagnosis mode 6.069 2.254 to 16.343 < 0.001 5.730 1.935 to 16.963 0.002 Diet therapy pressure 0.504 0.355 to 0.716 < 0.001 3.321 1.083 to 10.181 0.036 Follow-up period 0.452 0.319 to 0.641 < 0.001 0.655 0.211 to 2.033 0.464 Average Phe per year 0.605 0.477 to 0.768 < 0.001 1.251 0.671 to 2.334 0.481 Control situation 0.351 0.186 to 0.660 0.001 1.342 0.498 to 3.609 0.560 Abbreviations: BMI, body mass index; OR, odds ratio; 95% CI, 95% confidence interval. Multivariable adjusted for sex, region, income, paternal education level, maternal education level. Prediction accuracy assessment We constructed two models to evaluate the predictive prowess of six pivotal factors: a basic model, which encompassed all variables minus the six significant ones, and a comprehensive full model, integrating all surveyed variables. To gauge the models' accuracy, we employed calibration and discrimination metrics and juxtaposed the performances of both models. Notably, the full model exhibited a marked enhancement in predictive accuracy over the basic model, as evidenced in Table 3 . Delving deeper, the Area under the Receiver Operating Characteristic Curve (AUROC) analysis underscored a statistically significant divergence in discrimination between the two models (P < 0.001), with the distinct outcomes vividly portrayed in the ROC curves presented in Fig. 2 . Table 3 Prediction accuracy gained by adding six significant factors identified for PKU children with psycho-behavioral problem. Statistics Basic model Full model Calibration AIC 115.1776 81.9296 BIC 130.8086 113.1916 Discrimination AUROC 0.715 0.927 P value for AUROC < 0.001 Abbreviations: AIC, Akaike information criterion; BIC, Bayesian information criterion; AUROC, area under the receiver operating characteristic. Basic model included all variables under study with the exception of six significant factors identified in Table 2 , and full model included all variables under study. Risk prediction nomogram model For practical reasons, we constructed a nomogram, shown in Fig. 3 , to help intuitively predict the overall risk of psycho-behavioral problems in children with PKU by modeling promising and important influencing factors under study. DISCUSSION In this study, we aimed to estimate the prevalence rate of psycho-behavioral problems among PKU children and explore potential factors associated with psycho-behavioral problems among 100 PKU children aged 6–18 years from the pediatric clinic of China-Japan Friendship Hospital. The key finding of this study was that BMI, age, pregnancy order, delivery order, disease diagnosis mode, and diet therapy pressure were significantly associated with psycho-behavioral problems among PKU children. To our knowledge, this is thus far the first study that has explored the influencing factors profiling psycho-behavioral problems among Chinese PKU children during childhood and post-childhood. In this study, approximately 25% of Chinese children aged 6–18 years with PKU exhibited psycho-behavioral challenges. In addition to establishing this prevalence rate, we endeavored to uncover potential contributing factors underlying the emergence of psycho-behavioral issues among PKU-affected children, leveraging the insights garnered from our survey data. BMI was a relevant factor associated with psycho-behavioral problems among Chinese PKU children in our analyses, consistent with the results of several studies.(14, 15) BMI was found to be a contributing factor, with an odds ratio of 1.135, indicating a modest yet statistically significant increase in the likelihood of psycho-behavioral problems. Age was another significant variable, with a notable odds ratio of 3.169, suggesting that age may play a pivotal role in shaping psycho-behavioral outcomes. This result revealed that adolescents are particularly prone to encountering such issues, echoing the findings of previous research.(16, 17) Notably, as adolescents progress in age, their adherence to prescribed dietary regimens tends to diminish, and sustaining metabolic balance post-childhood poses significant challenges. This scenario heightens the vulnerability to comorbidities, which can subsequently impact psychosocial well-being. In adolescent children with PKU, the cause of psycho-psychological and behavioral problems may be related to disease burden, elevated blood Phe level, and poor compliance, which may affect brain development and increase the incidence of mental diseases. Meanwhile, it's worth noting that, approximately half of children experiencing psycho-behavioral difficulties reported feelings of pressure surrounding their eating habits in our study. The pressure associated with diet therapy was found to be significantly associated, with an odds ratio of 3.321. Social settings often present challenges for these children, who may feel alienated or embarrassed due to dietary constraints. Prolonged adherence to these restrictions may foster emotional disturbances,(18) encompassing anxiety, depression, and diminished self-esteem, potentially fostering disinterest in the restrictive diet and, subsequently, impacting their overall compliance. Furthermore, the strict maintenance of a low-phenylalanine diet imposes stress on family members, particularly primary caregivers, potentially jeopardizing family well-being.(19) Consequently, offering psychological support and intervention tailored to PKU children is crucial in bolstering treatment adherence and enhancing the quality of life for both the children and their families.(3, 5) , (19) In addition, disease diagnosis mode is also crucial to the occurrence of psycho-behavioral problems, with an odds ratio of 5.730 (95% CI: 1.935–16.963, P = 0.002). Among PKU children exhibiting psycho-psychological and behavioral issues, the proportion of those diagnosed through neonatal screening is comparable to that of clinical detection (44% vs. 56%). However, among children without such problems, a striking 82.7% were identified through neonatal screening. Among the 73 children diagnosed via neonatal screening, a favorable trend emerges, with 62 (84.9%) exhibiting no psycho-behavioral difficulties, whereas among the 27 children detected clinically post-birth, only 14 (51.9%) were free from such issues. The research underscores the link between the prevalence and severity of psycho-behavioral problems and the timing and extent of exposure to elevated blood phenylalanine levels.(7, 20) Specifically, children with suboptimal metabolic control during the early, crucial stages are more vulnerable and may manifest more severe symptoms. While early-screened and treated PKU children may still encounter mental, psychological, and behavioral challenges, prompt diagnosis and intervention significantly enhance patient prognosis,(21, 22) emphasizing the paramount importance of early diagnosis and treatment. Interestingly, we found that the sequence of pregnancy and delivery were also identified as important, with a decreased odds ratio of 0.143, and 0.041, respectively, hinting at potential protective effects for subsequent pregnancies, possibly involving genetic risk, family management, and therapeutic interventions. Although the order of pregnancy and delivery themselves do not directly affect genetic risk, if there is already a child with PKU in a family, parents and doctors will pay more attention and may conduct more rigorous genetic counseling and prenatal diagnosis for subsequent children. This increased attention helps identify potential problems earlier and intervene accordingly. In order to further improve the applied value of our findings, we employed nomogram techniques. Fortunately, the overall accuracy of the nomogram prediction model we constructed for psycho-behavioral problems in children with PKU was excellent. Despite the apparent associations, the findings here should be considered preliminary, and we agree that validation in other independent, well-designed longitudinal studies are necessary to confirm or refute our conclusions. Limitations The current study boasts several notable strengths. Firstly, given the rarity of PKU, the inclusion of a substantial sample size and a multifaceted approach to exploration stands as a significant advantage. This comprehensive analysis offers valuable insights and serves as a reliable reference for clinicians in the diagnosis and management of PKU in children. Secondly, the utilization of tools such as the PSQ (Parent Symptom Questionnaire) and HADS (Hospital Anxiety and Depression Scale) underscores the study’s comprehensiveness. These instruments efficiently screen for a wide range of mental, psychological, and behavioral concerns in children, enabling prompt identification and targeted interventions. Some limitations should be acknowledged for this study. First, the questionnaire was mainly answered by parents according to children’s condition, which cannot avoid the impact of a recall bias. Secondly, the cross-sectional design of the study constrains our ability to establish definitive causal relationships between potential factors and psycho-behavioral problems. Conclusions In conclusion, our study highlights that roughly a quarter of Chinese PKU children aged 6–18 could be facing psycho-behavioral difficulties. We have also uncovered six factors that show a notable correlation with these problems in children affected by PKU. Our findings offer a window into the risk factors associated with psycho-behavioral issues in this patient population, potentially enabling the development of preventive measures to mitigate their occurrence. Declarations Ethics approval and consent to participate: The conduct of the surveys was reviewed and approved by the Ethics Committee of China-Japan Friendship Hospital (2024-KY-081). Written informed consent to participate in this study was provided by the participants' legal guardian. Consent for publication: All authors consent to publish. Availability of data and materials: Data are available upon reasonable requirements. 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 study had no specific funding. Authors' contributions: M.X., M.S. and WQ.N. designed the study. M.X., SN.W. and B.P. contributed to data acquisition. M.X. and WQ.N. performed the statistical analysis. M.X. and M.S. wrote the first draft. ZX.Z. and WQ.N. are the study guarantors. The final manuscript was contributed by all authors. Acknowledgments: We are grateful to all participating children and their parents or guardians for their cooperation and willingness. References van Spronsen FJ, Blau N, Harding C, Burlina A, Longo N, Bosch AM. Phenylketonuria. Nature reviews Disease primers. 2021;7(1):36. Didycz B, Bik-Multanowski M. Blood phenylalanine instability strongly correlates with anxiety in phenylketonuria. Molecular genetics and metabolism reports. 2018;14:80-2. Feillet F, MacDonald A, Hartung Perron D, Burton B. Outcomes beyond phenylalanine: an international perspective. Molecular genetics and metabolism. 2010;99 Suppl 1:S79-85. Moyle JJ, Fox AM, Arthur M, Bynevelt M, Burnett JR. Meta-analysis of neuropsychological symptoms of adolescents and adults with PKU. Neuropsychology review. 2007;17(2):91-101. Sharman R, Sullivan K, Young RM, McGill J. Depressive symptoms in adolescents with early and continuously treated phenylketonuria: associations with phenylalanine and tyrosine levels. Gene. 2012;504(2):288-91. Borghi L, Salvatici E, Riva E, Giovannini M, Vegni EA. Psychological and psychosocial implications for parenting a child with phenylketonuria: a systematic review. Minerva Pediatr. 2019;71(2):181-95. Elhawary NA, AlJahdali IA, Abumansour IS, Elhawary EN, Gaboon N, Dandini M, et al. Genetic etiology and clinical challenges of phenylketonuria. Hum Genomics. 2022;16(1):22. Zuñiga Vinueza AM. Recent Advances in Phenylketonuria: A Review. Cureus. 2023;15(6):e40459. Anderson PJ, Wood SJ, Francis DE, Coleman L, Anderson V, Boneh A. Are neuropsychological impairments in children with early-treated phenylketonuria (PKU) related to white matter abnormalities or elevated phenylalanine levels? Developmental neuropsychology. 2007;32(2):645-68. Clacy A, Sharman R, McGill J. Depression, anxiety, and stress in young adults with phenylketonuria: associations with biochemistry. Journal of developmental and behavioral pediatrics : JDBP. 2014;35(6):388-91. Writing Group For Practice Guidelines For D, Treatment Of Genetic Diseases Medical Genetics Branch Of Chinese Medical A, Huang S, Song F. [Clinical practice guidelines for phenylketonuria]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2020;37(3):226-34. Willard VW, Conklin HM, Huang L, Zhang H, Kahalley LS. Concordance of parent-, teacher- and self-report ratings on the Conners 3 in adolescent survivors of cancer. Psychol Assess. 2016;28(9):1110-8. Beekman E, Verhagen A. Clinimetrics: Hospital Anxiety and Depression Scale. J Physiother. 2018;64(3):198. Rocha JC, MacDonald A, Trefz F. Is overweight an issue in phenylketonuria? Molecular genetics and metabolism. 2013;110 Suppl:S18-24. Rocha JC, van Rijn M, van Dam E, Ahring K, Bélanger-Quintana A, Dokoupil K, et al. Weight Management in Phenylketonuria: What Should Be Monitored. Ann Nutr Metab. 2016;68(1):60-5. Manti F, Nardecchia F, Chiarotti F, Carducci C, Carducci C, Leuzzi V. Psychiatric disorders in adolescent and young adult patients with phenylketonuria. Molecular genetics and metabolism. 2016;117(1):12-8. Esgi M, Ergun H, Kaya NY, Atakay DY, Erucar E, Celik F. Phenylketonuria from the perspectives of patients in Türkiye. Orphanet journal of rare diseases. 2024;19(1):78. Rocha JC, van Spronsen FJ, Almeida MF, Soares G, Quelhas D, Ramos E, et al. Dietary treatment in phenylketonuria does not lead to increased risk of obesity or metabolic syndrome. Molecular genetics and metabolism. 2012;107(4):659-63. Ashe K, Kelso W, Farrand S, Panetta J, Fazio T, De Jong G, et al. Psychiatric and Cognitive Aspects of Phenylketonuria: The Limitations of Diet and Promise of New Treatments. Front Psychiatry. 2019;10:561. Anjema K, van Rijn M, Verkerk PH, Burgerhof JG, Heiner-Fokkema MR, van Spronsen FJ. PKU: high plasma phenylalanine concentrations are associated with increased prevalence of mood swings. Molecular genetics and metabolism. 2011;104(3):231-4. Loeber JG, Platis D, Zetterström RH, Almashanu S, Boemer F, Bonham JR, et al. Neonatal Screening in Europe Revisited: An ISNS Perspective on the Current State and Developments Since 2010. Int J Neonatal Screen. 2021;7(1). Spiekerkoetter U, Krude H. Target Diseases for Neonatal Screening in Germany. Dtsch Arztebl Int. 2022;119(17):306-16. Cite Share Download PDF Status: Published Journal Publication published 11 Jun, 2025 Read the published version in Orphanet Journal of Rare Diseases → Version 1 posted Editorial decision: Minor revision 18 Mar, 2025 Reviewers agreed at journal 10 Feb, 2025 Reviewers invited by journal 03 Nov, 2024 Editor assigned by journal 22 Oct, 2024 First submitted to journal 20 Oct, 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5298122","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":373425982,"identity":"c72c4524-f1aa-49ba-9254-53357c84b9d7","order_by":0,"name":"Mei Xue","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Mei","middleName":"","lastName":"Xue","suffix":""},{"id":373425983,"identity":"14af2dea-77fc-494e-b5b2-7c1cc1ebac43","order_by":1,"name":"Wenquan Niu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYDACZjS2HBt7+wHStBjz8ZxJIM3GxHkSDgZ4VZmz85hJfNxhndg/u4H5c0HNnfQ2CYYEhh8V23BqsWzmMZOceSY9ccadA2zSM449y22TbjzA2HPmNk4tBod5zG7zth1ObLiRwMbM23A4t03mQAIzYxsBLX+BWubfSGD+DNSSziaRYEBYCyNQy4YbCQzSQC0JRGhhK//Z25ZuvBHoMGmeY4cN24CBfBCvX84f3mzws81adh7IYTw1h+Xl29sPPvhRgVsLFIBihP8DnHuAkHoG1DQwCkbBKBgFowANAAAgGlcViUHdUAAAAABJRU5ErkJggg==","orcid":"","institution":"Capital Institute of Pediatrics","correspondingAuthor":true,"prefix":"","firstName":"Wenquan","middleName":"","lastName":"Niu","suffix":""},{"id":373425984,"identity":"9908959b-27ec-42ae-866b-96c4eea8e29d","order_by":2,"name":"Ming Shen","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ming","middleName":"","lastName":"Shen","suffix":""},{"id":373425985,"identity":"207e286c-310a-46ad-8a64-6b0dc4774b76","order_by":3,"name":"Shunan Wang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shunan","middleName":"","lastName":"Wang","suffix":""},{"id":373425986,"identity":"e9dd17ed-3a0b-48a4-9cc3-6cf576e7296c","order_by":4,"name":"Bo Pang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bo","middleName":"","lastName":"Pang","suffix":""},{"id":373425987,"identity":"247ab6c5-4776-471c-ab52-1a79ec728edd","order_by":5,"name":"Xiaoqian Zhang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoqian","middleName":"","lastName":"Zhang","suffix":""},{"id":373425988,"identity":"3a9a27ab-39eb-4100-ac25-e00db56a6d79","order_by":6,"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":373425989,"identity":"bf5ee456-07e9-4138-82df-d04e9f4f1d06","order_by":7,"name":"Zhixin Zhang","email":"","orcid":"","institution":"China-Japan Friendship Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zhixin","middleName":"","lastName":"Zhang","suffix":""}],"badges":[],"createdAt":"2024-10-20 11:30:00","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5298122/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5298122/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13023-025-03824-y","type":"published","date":"2025-06-11T15:57:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":70507046,"identity":"f336fc55-1361-4224-b08b-c6a35e1055fa","added_by":"auto","created_at":"2024-12-03 23:49:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":70207,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eParticipants selection process flow chart.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5298122/v1/af9e124a15f4dd6794dc7724.png"},{"id":70507785,"identity":"c077c6a6-35b7-45e7-b4ec-fec6945a8cb9","added_by":"auto","created_at":"2024-12-03 23:57:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":68336,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver operating characteristic (ROC) curve for basic model and full model.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbbreviations: AUC, area under curve.\u003c/p\u003e\n\u003cp\u003eThe blue solid line corresponds to basic model, and the red solod line corresponds to full model. Basic model included all variables under study with the exception of six significant factors identified in Table 2, and full model included all variables under study.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5298122/v1/f77b7893f983aabc7e56b8b2.png"},{"id":70507047,"identity":"521833be-a28b-4c65-b091-036d94a3a1a2","added_by":"auto","created_at":"2024-12-03 23:49:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":96342,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrediction nomograms for psycho-behavioral problem among PKU children.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5298122/v1/e1920fb7ff76fa65f566a99e.png"},{"id":84726461,"identity":"bcd17833-6768-4de3-824d-31466d0c13c9","added_by":"auto","created_at":"2025-06-16 16:04:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1338092,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5298122/v1/b927dbb9-626d-4808-9789-6e7ef9e4b9df.pdf"}],"financialInterests":"","formattedTitle":"Factors Associated with Psycho-behavioral Problems among 100 Phenylketonuria Children Aged 6-18 Years","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003ePhenylketonuria (PKU), a genetic metabolic disorder affecting approximately 1 in 10,000 to 1 in 15,000 individuals globally,(1) is characterized by a deficiency in the phenylalanine hydroxylase (PAH) enzyme, which is pivotal for the metabolism of the amino acid phenylalanine (Phe). The subsequent accumulation of Phe in the bloodstream and brain can lead to a spectrum of neurodevelopmental challenges if allowed to proceed untreated, including severe intellectual disability and psycho-behavioral complications.(2)\u003csup\u003e,\u003c/sup\u003e (3) Despite the advent of neonatal screening and dietary management, children with PKU may still face psycho-behavioral issues that can impact quality of life and social integration.(4)\u003csup\u003e,\u003c/sup\u003e (5)\u003c/p\u003e \u003cp\u003eThe importance of focusing psycho-behavioral problems in PKU cannot be overstated.(6) These issues, if left untreated, can lead to long-term social and emotional difficulties, affecting not only individuals but also their families and societies. The necessity of this research is further highlighted by the limitations in existing literature, which mainly focuses on metabolic aspects of PKU, overlooking the psychological and social implications.(7, 8) Prior studies have reported a range of psycho-behavioral challenges in PKU, including attention deficit, mood disorders, and social cognitive deficits, yet how many factors are responsible for these issues thus far remain poorly understood.(2, 9, 10)\u003c/p\u003e \u003cp\u003eThis study aimed to explore potential factors associated with psycho-behavioral problems in PKU children aged 6\u0026ndash;18 years, with a particular focus on birth history, disease-related factors, metabolic control, and family-related factors.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design\u003c/h2\u003e \u003cp\u003eWe conducted a cross-sectional survey from May 2022 to May 2024. The Ethics Committee of China-Japan Friendship Hospital reviewed and approved the protocols of this survey, and this study was implemented according to the Declaration of Helsinki.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy participants\u003c/h3\u003e\n\u003cp\u003eThe study participants consisted of PKU children from the pediatric clinic of China-Japan Friendship Hospital. The parents or guardians of participating students provided signature consent to the participation of this survey, with opt-out clauses in our consent form. Study participants were restricted to children aged 6 to 18 years, who have received a definitive diagnosis of PKU from a qualified clinician. Participants were excluded if they met any of the following criteria: (1) BH4 deficiency and DNAJC12 biallelic mutation; (2) guardians cannot provide reliable medical history; (3) prior diagnosis of familial or hereditary mental health disorders; (4) suffering from other chronic diseases that may precipitate psycho-behavioral problems.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eWe collected data by self-designed questionnaires. To ensure the reliability of tour questionnaires, both questionnaires were distributed in small samples before formal circulation, and had a reliability coefficient (alpha) over 0.85.\u003c/p\u003e \u003cp\u003eThe questionnaire includes the following parts: (1) demographic information: age, sex, height, weight, body mass index (BMI), and region; (2) fetal and neonatal factors: birth length, birth weight, delivery mode, pregnancy order, and delivery order; (3) family-related factors: maternal education level, paternal education level, and family income. (4) disease-related information: disease diagnosis mode, age of initial treatment (month), highest Phe before treatment, recent Phe, average Phe per year, diet therapy pressure (no, yes), follow-up period, and control situation; (5) psycho-behavioral part: the Conners Parent Symptom Questionnaire (PSQ) and the Hospital Anxiety and Depression Scale (HADS) used to evaluate the psycho-behavioral status.\u003c/p\u003e\n\u003ch3\u003eQuality control\u003c/h3\u003e\n\u003cp\u003eThe questionnaires were all recorded by two experienced doctors in toutpatient department, and they were responsible for assisting in parents or guardians of participating patients to understand and fill out questionnaire. The dissenting part was ruled by a doctor with higher seniority. All information was independently typed into an Excel sheet by two researchers (M.X. and B.P.). Disagreement was adjudicated by a third researcher (M.S.). Physicians would contact the parents or guardians of participants to resupply or confirm information which were missing or obviously abnormal in the questionnaires.\u003c/p\u003e\n\u003ch3\u003eDefinitions of PKU and psycho-behavioral problems\u003c/h3\u003e\n\u003cp\u003e In this study, we adopted the clinical practice guidelines for PKU to define it.(11) The Parent Symptom Questionnaire (PSQ)(12) is a widely recognized assessment tool for children\u0026rsquo;s psychological and behavioral issues. It features 48 items completed by parents, with each scored on a scale of 0 to 3. The PSQ evaluates six key factors: conduct problems, learning problems, psychosomatic issues, impulsive-hyperactivity, anxiety, and a hyperactivity index. To determine the average score for each factor, individual scores were summed and divided by the number of items. A factor score above 1.5 (or two standard deviations from the norm) is deemed as abnormal. The Hospital Anxiety and Depression Scale (HADS)(13) is a prevalent screening tool for mental health issues in the context of physical illness. It consists of 14 items that measure anxiety and depression. Scores are categorized as follows: 0\u0026ndash;7 for no symptoms, 8\u0026ndash;10 for possible symptoms, and 11\u0026ndash;21 for the presence of symptoms. If the score of each factor in the PSQ questionnaire is greater than 1.5 points, the value is 1, 0 otherwise. In the HADS questionnaire, 0\u0026ndash;7 scores were assigned as 0, 8\u0026ndash;10 scores were assigned as 1, 11\u0026ndash;21 scores were assigned as 2. In this study, we defined psycho-behavioral problems as PSQ questionnaire score and/or HADS questionnaire score\u0026thinsp;\u0026ge;\u0026thinsp;2, and no psycho-behavioral problems otherwise.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDefinitions of other items\u003c/h2\u003e \u003cp\u003eDelivery modes included vaginal delivery and caesarean section. Gestational age was used to distinguish between term and preterm. Birth body length (to the nearest 0.1 cm) was reported by the parents or guardians of participant students. Pregnancy order and delivery order meant the times of pregnancy and bearing birth, respectively. Family education was the highest level of education of parents and was categorized as master's degree or above, bachelor's degree, and high school degree or below. Family income (RMB per year) was categorized as \u0026ge;\u0026thinsp;100,000, 50,000-100,000, and \u0026lt;\u0026thinsp;50,000.\u003c/p\u003e \u003cp\u003eDisease diagnosis mode includes neonatal screening and clinical diagnosis. The age of initial treatment was measured in months. Average Phe per year was categorized as 2\u0026ndash;6 mg/dL, 6\u0026ndash;10 mg/dL, and \u0026gt;\u0026thinsp;10 mg/dL. Follow-up period included 4 times a year and less than 4 times a year. The control situation was divided according to age and the standard blood value of the corresponding age.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStatistical Analyses\u003c/h3\u003e\n\u003cp\u003eData were analyze utilizing the STATA software (version 18.0) and R programming environment (version 4.3.3). The expression of continuous variables was mean (standard deviation) if no deviation from normal distribution tested by the skewness and kurtosis test, and median (interquartile range) otherwise. The expression of categorical variables was count (percent). Between-group comparisons (PKU children with versus without psycho-behavioral problems) of variables were conducted using appropriate statistical tests, including the t-test for parametric data, the χ\u003csup\u003e2\u003c/sup\u003e test for categorical data, and the rank-sum test for non-parametric data.\u003c/p\u003e \u003cp\u003eTo identify statistically significant risk factors for psycho-behavioral problems among PKU children, logistic regression analyses were done without considering any confounders and then adjusted for sex, region, family income, maternal education level, and paternal education level in multivariable adjustment models to examine their independence. Effect-size estimates are expressed as odds ratio (OR) and 95% confidence interval (95% CI).\u003c/p\u003e \u003cp\u003eThe enhancement in predictive accuracy achieved through the incorporation of significant factors into the basic model was comprehensively evaluated from both calibration and discrimination perspectives. On the calibration side, the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) were leveraged to assess the degree of congruence between the predicted probabilities, incorporating these factors, and the actual observed risks. Furthermore, these criteria served to evaluate the overall suitability and goodness-of-fit of the refined risk model. From a discrimination standpoint, the Receiver Operating Characteristic (ROC) curve analysis for both the original and modified models was conducted.\u003c/p\u003e \u003cp\u003eFinally, a predictive nomogram for risk assessment was developed, incorporating key influential factors to improve its utility in clinical settings and public health initiatives. This model was created using R version 4.3.3 for Windows.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eAfter rigorous screening to eliminate unqualified questionnaires, data from 100 children diagnosed with PKU (detailed selection procedure is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.), comprising 54 girls and 46 boys, were analyzed, with 25 children exhibiting psycho-behavioral problems, reflecting a prevalence rate of 25% for such issues among PKU children. The baseline characteristics of all participating children are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e according to the presence and absence of psycho-behavioral problems.\u003c/p\u003e \u003cp\u003e \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\u003eThe baseline 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=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChildren without\u003c/p\u003e \u003cp\u003ePsycho-behavioral problem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChildren with\u003c/p\u003e \u003cp\u003epsycho-behavioral problem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;25)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographic information\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\u003eAge (years)\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u0026ndash;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59 (78.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (48.0)\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\u003e12\u0026ndash;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (52.0)\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\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.247\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\u003e32 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (56.0)\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\u003e43 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (44.0)\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\u003e136 (128, 155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138.5 (126, 155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.939\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\u003e32 (25, 46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (28, 55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.8 (15.2, 20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.5 (16.0, 22.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (77.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (48.0)\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\u003eCountry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (52.0)\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\u003eFetal and neonatal 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\u003eBirth length (cm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (50, 51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (49, 50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.036\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBirth weight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3200 (2900, 3500)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3000 (2650, 3400)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.159\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.096\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\u003e43 (57.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19 (76.0)\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\u003e32 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (24.0)\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\u003ePregnancy order\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \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 \u003cp\u003e1 (1, 2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1, 1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eFamily-related 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\u003eMaternal education level\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.258\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\u003e37 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (64.0)\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\u003e33 (44.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (36.0)\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\u003e5 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\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 level\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.376\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\u003e39 (52.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (68.0)\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\u003e32 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (28.0)\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\u003e4 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (4.0)\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.335\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;50, 000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23 (30.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (32.0)\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\u003e50, 000-100, 000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (48.0)\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\u0026gt;\u0026thinsp;100, 000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (20.0)\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\u003eDisease-related information\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\u003eDisease diagnosis 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=\"char\" char=\".\" 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\u003eNeonatal screening\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (82.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (44.0)\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\u003eClinical diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (56.0)\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\u003eAge of initial treatment (month)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (1, 19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1, 17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.599\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest Phe before treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (11, 31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (19, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.454\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecent Phe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.9 (5.85, 12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (3.63, 12.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Phe per year (mg/dL)\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\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\u003e32 (42.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (44.0)\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\u003e6\u0026ndash;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (24.0)\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\u0026gt;\u0026thinsp;10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (32.0)\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\u003eDiet therapy pressure\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \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\u003e64 (89.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (60.0)\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\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (14.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (40.0)\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\u003eFollow-up period\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.899\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;4 times a year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (70.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (72.0)\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;4 times a year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (29.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (28.0)\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\u003eControl situation\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=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.817\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWell control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38 (50.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (48.0)\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\u003ePoor control\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (52.0)\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 \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are expressed as median (interquartile range) or count (percent). P value was calculated by the rank-sum test or the χ\u003csup\u003e2\u003c/sup\u003e test, where appropriate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: BMI, body mass index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of contributing predictors\u003c/h2\u003e \u003cp\u003eBaseline variables shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e were selected based on clinical relevance or with a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 on univariate analysis, and considered as candidate variables. After adjusting for sex, region, income, paternal education level, and maternal education level, six factors (BMI, age, pregnancy order, delivery order, disease diagnosis mode, and diet therapy pressure) were associated with the significant factors of PKU children with psycho-behavioral problems, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. For example, the significant odds of having psycho-behavioral problems was 1.135 (95% CI: 1.010\u0026ndash;1.276, P\u0026thinsp;=\u0026thinsp;0.033) for BMI, 3.169 (95% CI: 1.024\u0026ndash;9.804, P\u0026thinsp;=\u0026thinsp;0.045) for age, 0.143 (95% CI: 0.033\u0026ndash;0.607, P\u0026thinsp;=\u0026thinsp;0.008) for pregnancy order, 0.041 (95% CI: 0.004\u0026ndash;0.373, P\u0026thinsp;=\u0026thinsp;0.005) for delivery order, 5.730 (95% CI: 1.935\u0026ndash;16.963, P\u0026thinsp;=\u0026thinsp;0.002) for disease diagnosis mode, and 3.321 (95% CI: 1.083\u0026ndash;10.181, P\u0026thinsp;=\u0026thinsp;0.036) for diet therapy pressure.\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\u003eIdentification of potential factors responsible for PKU children with psycho-behavioral problem.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSignificant variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eUnadjusted model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eMultivariable adjusted model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c11\" namest=\"c9\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.950\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.276\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.530\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e10.428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.024\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e9.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.045\u003c/b\u003e\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.992\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.607\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e0.373\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.005\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHighest Phe before treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.993\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.956\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.726\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecent Phe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.902\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.750\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of initial treatment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.971\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.948\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e1.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.199\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=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e2.307\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e6.783\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisease diagnosis mode\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e5.730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e16.963\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiet therapy pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e3.321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e10.181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e\u003cb\u003e0.036\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFollow-up period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.319\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.655\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.464\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage Phe per year\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.605\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.477\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.768\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.251\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.671\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e2.334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.481\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eControl situation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.351\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e1.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e0.498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c11\"\u003e \u003cp\u003e3.609\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c12\"\u003e \u003cp\u003e0.560\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003eAbbreviations: BMI, body mass index; OR, odds ratio; 95% CI, 95% confidence interval. Multivariable adjusted for sex, region, income, paternal education level, maternal education level.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePrediction accuracy assessment\u003c/h2\u003e \u003cp\u003eWe constructed two models to evaluate the predictive prowess of six pivotal factors: a basic model, which encompassed all variables minus the six significant ones, and a comprehensive full model, integrating all surveyed variables. To gauge the models' accuracy, we employed calibration and discrimination metrics and juxtaposed the performances of both models. Notably, the full model exhibited a marked enhancement in predictive accuracy over the basic model, as evidenced in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Delving deeper, the Area under the Receiver Operating Characteristic Curve (AUROC) analysis underscored a statistically significant divergence in discrimination between the two models (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with the distinct outcomes vividly portrayed in the ROC curves presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\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\u003ePrediction accuracy gained by adding six significant factors identified for PKU children with psycho-behavioral problem.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatistics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBasic model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFull model\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCalibration\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115.1776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.9296\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130.8086\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e113.1916\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiscrimination\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAUROC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.715\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.927\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP value for AUROC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eAbbreviations: AIC, Akaike information criterion; BIC, Bayesian information criterion; AUROC, area under the receiver operating characteristic. Basic model included all variables under study with the exception of six significant factors identified in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and full model included all variables under study.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eRisk prediction nomogram model\u003c/h2\u003e \u003cp\u003eFor practical reasons, we constructed a nomogram, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, to help intuitively predict the overall risk of psycho-behavioral problems in children with PKU by modeling promising and important influencing factors under study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, we aimed to estimate the prevalence rate of psycho-behavioral problems among PKU children and explore potential factors associated with psycho-behavioral problems among 100 PKU children aged 6\u0026ndash;18 years from the pediatric clinic of China-Japan Friendship Hospital. The key finding of this study was that BMI, age, pregnancy order, delivery order, disease diagnosis mode, and diet therapy pressure were significantly associated with psycho-behavioral problems among PKU children. To our knowledge, this is thus far the first study that has explored the influencing factors profiling psycho-behavioral problems among Chinese PKU children during childhood and post-childhood.\u003c/p\u003e \u003cp\u003eIn this study, approximately 25% of Chinese children aged 6\u0026ndash;18 years with PKU exhibited psycho-behavioral challenges. In addition to establishing this prevalence rate, we endeavored to uncover potential contributing factors underlying the emergence of psycho-behavioral issues among PKU-affected children, leveraging the insights garnered from our survey data.\u003c/p\u003e \u003cp\u003eBMI was a relevant factor associated with psycho-behavioral problems among Chinese PKU children in our analyses, consistent with the results of several studies.(14, 15) BMI was found to be a contributing factor, with an odds ratio of 1.135, indicating a modest yet statistically significant increase in the likelihood of psycho-behavioral problems.\u003c/p\u003e \u003cp\u003eAge was another significant variable, with a notable odds ratio of 3.169, suggesting that age may play a pivotal role in shaping psycho-behavioral outcomes. This result revealed that adolescents are particularly prone to encountering such issues, echoing the findings of previous research.(16, 17) Notably, as adolescents progress in age, their adherence to prescribed dietary regimens tends to diminish, and sustaining metabolic balance post-childhood poses significant challenges. This scenario heightens the vulnerability to comorbidities, which can subsequently impact psychosocial well-being. In adolescent children with PKU, the cause of psycho-psychological and behavioral problems may be related to disease burden, elevated blood Phe level, and poor compliance, which may affect brain development and increase the incidence of mental diseases. Meanwhile, it's worth noting that, approximately half of children experiencing psycho-behavioral difficulties reported feelings of pressure surrounding their eating habits in our study. The pressure associated with diet therapy was found to be significantly associated, with an odds ratio of 3.321. Social settings often present challenges for these children, who may feel alienated or embarrassed due to dietary constraints. Prolonged adherence to these restrictions may foster emotional disturbances,(18) encompassing anxiety, depression, and diminished self-esteem, potentially fostering disinterest in the restrictive diet and, subsequently, impacting their overall compliance. Furthermore, the strict maintenance of a low-phenylalanine diet imposes stress on family members, particularly primary caregivers, potentially jeopardizing family well-being.(19) Consequently, offering psychological support and intervention tailored to PKU children is crucial in bolstering treatment adherence and enhancing the quality of life for both the children and their families.(3, 5)\u003csup\u003e,\u003c/sup\u003e(19)\u003c/p\u003e \u003cp\u003eIn addition, disease diagnosis mode is also crucial to the occurrence of psycho-behavioral problems, with an odds ratio of 5.730 (95% CI: 1.935\u0026ndash;16.963, P\u0026thinsp;=\u0026thinsp;0.002). Among PKU children exhibiting psycho-psychological and behavioral issues, the proportion of those diagnosed through neonatal screening is comparable to that of clinical detection (44% vs. 56%). However, among children without such problems, a striking 82.7% were identified through neonatal screening. Among the 73 children diagnosed via neonatal screening, a favorable trend emerges, with 62 (84.9%) exhibiting no psycho-behavioral difficulties, whereas among the 27 children detected clinically post-birth, only 14 (51.9%) were free from such issues. The research underscores the link between the prevalence and severity of psycho-behavioral problems and the timing and extent of exposure to elevated blood phenylalanine levels.(7, 20) Specifically, children with suboptimal metabolic control during the early, crucial stages are more vulnerable and may manifest more severe symptoms. While early-screened and treated PKU children may still encounter mental, psychological, and behavioral challenges, prompt diagnosis and intervention significantly enhance patient prognosis,(21, 22) emphasizing the paramount importance of early diagnosis and treatment.\u003c/p\u003e \u003cp\u003eInterestingly, we found that the sequence of pregnancy and delivery were also identified as important, with a decreased odds ratio of 0.143, and 0.041, respectively, hinting at potential protective effects for subsequent pregnancies, possibly involving genetic risk, family management, and therapeutic interventions. Although the order of pregnancy and delivery themselves do not directly affect genetic risk, if there is already a child with PKU in a family, parents and doctors will pay more attention and may conduct more rigorous genetic counseling and prenatal diagnosis for subsequent children. This increased attention helps identify potential problems earlier and intervene accordingly.\u003c/p\u003e \u003cp\u003eIn order to further improve the applied value of our findings, we employed nomogram techniques. Fortunately, the overall accuracy of the nomogram prediction model we constructed for psycho-behavioral problems in children with PKU was excellent. Despite the apparent associations, the findings here should be considered preliminary, and we agree that validation in other independent, well-designed longitudinal studies are necessary to confirm or refute our conclusions.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThe current study boasts several notable strengths. Firstly, given the rarity of PKU, the inclusion of a substantial sample size and a multifaceted approach to exploration stands as a significant advantage. This comprehensive analysis offers valuable insights and serves as a reliable reference for clinicians in the diagnosis and management of PKU in children. Secondly, the utilization of tools such as the PSQ (Parent Symptom Questionnaire) and HADS (Hospital Anxiety and Depression Scale) underscores the study\u0026rsquo;s comprehensiveness. These instruments efficiently screen for a wide range of mental, psychological, and behavioral concerns in children, enabling prompt identification and targeted interventions.\u003c/p\u003e \u003cp\u003eSome limitations should be acknowledged for this study. First, the questionnaire was mainly answered by parents according to children\u0026rsquo;s condition, which cannot avoid the impact of a recall bias. Secondly, the cross-sectional design of the study constrains our ability to establish definitive causal relationships between potential factors and psycho-behavioral problems.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn conclusion, our study highlights that roughly a quarter of Chinese PKU children aged 6\u0026ndash;18 could be facing psycho-behavioral difficulties. We have also uncovered six factors that show a notable correlation with these problems in children affected by PKU. Our findings offer a window into the risk factors associated with psycho-behavioral issues in this patient population, potentially enabling the development of preventive measures to mitigate their occurrence.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u0026nbsp;\u003c/strong\u003eThe conduct of the surveys was reviewed and approved by the Ethics Committee of China-Japan Friendship Hospital (2024-KY-081). Written informed consent to participate in this study was provided by the participants\u0026apos; legal guardian.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eAll authors consent to publish.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eData are available upon reasonable requirements.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no conflict of interest and no financial or\u0026nbsp;\u003c/p\u003e\n\u003cp\u003enon-financial benefits have been received or will be received from any party related\u0026nbsp;\u003c/p\u003e\n\u003cp\u003edirectly or indirectly to the subject of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This study had no specific funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003eM.X., M.S. and WQ.N. designed the study. M.X., SN.W. and B.P. contributed to data acquisition. M.X. and WQ.N. performed the statistical analysis. M.X. and M.S. wrote the first draft. ZX.Z. and WQ.N. are the study guarantors. The final manuscript was contributed by all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eWe are grateful to all participating children and their parents or guardians for their cooperation and willingness.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003evan Spronsen FJ, Blau N, Harding C, Burlina A, Longo N, Bosch AM. Phenylketonuria. Nature reviews Disease primers. 2021;7(1):36.\u003c/li\u003e\n \u003cli\u003eDidycz B, Bik-Multanowski M. Blood phenylalanine instability strongly correlates with anxiety in phenylketonuria. Molecular genetics and metabolism reports. 2018;14:80-2.\u003c/li\u003e\n \u003cli\u003eFeillet F, MacDonald A, Hartung Perron D, Burton B. Outcomes beyond phenylalanine: an international perspective. Molecular genetics and metabolism. 2010;99 Suppl 1:S79-85.\u003c/li\u003e\n \u003cli\u003eMoyle JJ, Fox AM, Arthur M, Bynevelt M, Burnett JR. Meta-analysis of neuropsychological symptoms of adolescents and adults with PKU. Neuropsychology review. 2007;17(2):91-101.\u003c/li\u003e\n \u003cli\u003eSharman R, Sullivan K, Young RM, McGill J. Depressive symptoms in adolescents with early and continuously treated phenylketonuria: associations with phenylalanine and tyrosine levels. Gene. 2012;504(2):288-91.\u003c/li\u003e\n \u003cli\u003eBorghi L, Salvatici E, Riva E, Giovannini M, Vegni EA. Psychological and psychosocial implications for parenting a child with phenylketonuria: a systematic review. Minerva Pediatr. 2019;71(2):181-95.\u003c/li\u003e\n \u003cli\u003eElhawary NA, AlJahdali IA, Abumansour IS, Elhawary EN, Gaboon N, Dandini M, et al. Genetic etiology and clinical challenges of phenylketonuria. Hum Genomics. 2022;16(1):22.\u003c/li\u003e\n \u003cli\u003eZu\u0026ntilde;iga Vinueza AM. Recent Advances in Phenylketonuria: A Review. Cureus. 2023;15(6):e40459.\u003c/li\u003e\n \u003cli\u003eAnderson PJ, Wood SJ, Francis DE, Coleman L, Anderson V, Boneh A. Are neuropsychological impairments in children with early-treated phenylketonuria (PKU) related to white matter abnormalities or elevated phenylalanine levels? Developmental neuropsychology. 2007;32(2):645-68.\u003c/li\u003e\n \u003cli\u003eClacy A, Sharman R, McGill J. Depression, anxiety, and stress in young adults with phenylketonuria: associations with biochemistry. Journal of developmental and behavioral pediatrics : JDBP. 2014;35(6):388-91.\u003c/li\u003e\n \u003cli\u003eWriting Group For Practice Guidelines For D, Treatment Of Genetic Diseases Medical Genetics Branch Of Chinese Medical A, Huang S, Song F. [Clinical practice guidelines for phenylketonuria]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2020;37(3):226-34.\u003c/li\u003e\n \u003cli\u003eWillard VW, Conklin HM, Huang L, Zhang H, Kahalley LS. Concordance of parent-, teacher- and self-report ratings on the Conners 3 in adolescent survivors of cancer. Psychol Assess. 2016;28(9):1110-8.\u003c/li\u003e\n \u003cli\u003eBeekman E, Verhagen A. Clinimetrics: Hospital Anxiety and Depression Scale. J Physiother. 2018;64(3):198.\u003c/li\u003e\n \u003cli\u003eRocha JC, MacDonald A, Trefz F. Is overweight an issue in phenylketonuria? Molecular genetics and metabolism. 2013;110 Suppl:S18-24.\u003c/li\u003e\n \u003cli\u003eRocha JC, van Rijn M, van Dam E, Ahring K, B\u0026eacute;langer-Quintana A, Dokoupil K, et al. Weight Management in Phenylketonuria: What Should Be Monitored. Ann Nutr Metab. 2016;68(1):60-5.\u003c/li\u003e\n \u003cli\u003eManti F, Nardecchia F, Chiarotti F, Carducci C, Carducci C, Leuzzi V. Psychiatric disorders in adolescent and young adult patients with phenylketonuria. Molecular genetics and metabolism. 2016;117(1):12-8.\u003c/li\u003e\n \u003cli\u003eEsgi M, Ergun H, Kaya NY, Atakay DY, Erucar E, Celik F. Phenylketonuria from the perspectives of patients in T\u0026uuml;rkiye. Orphanet journal of rare diseases. 2024;19(1):78.\u003c/li\u003e\n \u003cli\u003eRocha JC, van Spronsen FJ, Almeida MF, Soares G, Quelhas D, Ramos E, et al. Dietary treatment in phenylketonuria does not lead to increased risk of obesity or metabolic syndrome. Molecular genetics and metabolism. 2012;107(4):659-63.\u003c/li\u003e\n \u003cli\u003eAshe K, Kelso W, Farrand S, Panetta J, Fazio T, De Jong G, et al. Psychiatric and Cognitive Aspects of Phenylketonuria: The Limitations of Diet and Promise of New Treatments. Front Psychiatry. 2019;10:561.\u003c/li\u003e\n \u003cli\u003eAnjema K, van Rijn M, Verkerk PH, Burgerhof JG, Heiner-Fokkema MR, van Spronsen FJ. PKU: high plasma phenylalanine concentrations are associated with increased prevalence of mood swings. Molecular genetics and metabolism. 2011;104(3):231-4.\u003c/li\u003e\n \u003cli\u003eLoeber JG, Platis D, Zetterstr\u0026ouml;m RH, Almashanu S, Boemer F, Bonham JR, et al. Neonatal Screening in Europe Revisited: An ISNS Perspective on the Current State and Developments Since 2010. Int J Neonatal Screen. 2021;7(1).\u003c/li\u003e\n \u003cli\u003eSpiekerkoetter U, Krude H. Target Diseases for Neonatal Screening in Germany. Dtsch Arztebl Int. 2022;119(17):306-16.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"phenylketonuria, rare disease, children, factors, psycho-behavioral problems","lastPublishedDoi":"10.21203/rs.3.rs-5298122/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5298122/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePhenylketonuria (PKU) is a rare condition, and children diagnosed with PKU often face psycho-behavioral challenges, which can significantly impact their daily lives and social integration. Our objective was to evaluate the prevalence of psycho-behavioral difficulties and explore potential factors associated with their occurrence in PKU children aged 6\u0026ndash;18 years.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFrom May 2022 to May 2024, we recruited 100 children with PKU using a questionnaire survey. Data were analyzed using STATA software and the R programming language.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e25% of children aged 6\u0026ndash;18 years with PKU exhibited psycho-behavioral problems. Following multivariable adjustment, significant factors associated with these psycho-behavioral problems in the children were body mass index (BMI) (odds ratio, 95% CI, P: 95% CI: 1.135, 1.010\u0026ndash;1.276, 0.033), age (3.169, 1.024\u0026ndash;9.804, 0.045), pregnancy order (0.143, 0.033\u0026ndash;0.607, 0.008), delivery order (0.041, 0.004\u0026ndash;0.373, 0.005), mode of disease diagnosis (5.730, 1.935\u0026ndash;16.963, 0.002), and dietary therapy pressure (3.321, 1.083\u0026ndash;10.181, 0.036). A nomogram was constructed based on above significant factors, with descent prediction capability and accuracy.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eSix factors were identified to be closely associated with psycho-behavioral problems in PKU children. Our findings provide insights into the risk profiles behind psycho-behavioral issues in PKU, potentially enabling the development of preventive strategies.\u003c/p\u003e","manuscriptTitle":"Factors Associated with Psycho-behavioral Problems among 100 Phenylketonuria Children Aged 6-18 Years","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-12-03 23:49:19","doi":"10.21203/rs.3.rs-5298122/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Minor revision","date":"2025-03-18T08:38:36+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-02-10T17:49:33+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-03T10:34:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-10-22T13:44:07+00:00","index":"","fulltext":""},{"type":"submitted","content":"Orphanet Journal of Rare Diseases","date":"2024-10-20T07:29:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"orphanet-journal-of-rare-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ojrd","sideBox":"Learn more about [Orphanet Journal of Rare Diseases](http://ojrd.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ojrd/default.aspx","title":"Orphanet Journal of Rare Diseases","twitterHandle":"@bmc","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"be4044b7-3ec9-44cb-b098-2536d20791f3","owner":[],"postedDate":"December 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-16T15:59:03+00:00","versionOfRecord":{"articleIdentity":"rs-5298122","link":"https://doi.org/10.1186/s13023-025-03824-y","journal":{"identity":"orphanet-journal-of-rare-diseases","isVorOnly":false,"title":"Orphanet Journal of Rare Diseases"},"publishedOn":"2025-06-11 15:57:04","publishedOnDateReadable":"June 11th, 2025"},"versionCreatedAt":"2024-12-03 23:49:19","video":"","vorDoi":"10.1186/s13023-025-03824-y","vorDoiUrl":"https://doi.org/10.1186/s13023-025-03824-y","workflowStages":[]},"version":"v1","identity":"rs-5298122","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5298122","identity":"rs-5298122","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}