Cardiovascular Risk in Adolescents With Congenital Heart Disease Living in a Low-income Region: Cross-sectional Associations With Clinical, Behavioral and Sociodemographic Factors

Cardiovascular Risk in Adolescents With Congenital Heart Disease Living in a Low-income Region: Cross-sectional Associations With Clinical, Behavioral and Sociodemographic Factors | 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 Cardiovascular Risk in Adolescents With Congenital Heart Disease Living in a Low-income Region: Cross-sectional Associations With Clinical, Behavioral and Sociodemographic Factors Marylia Santos Pereira, Ana Carla Porciuncula Cavalcante, Adrielly Suely Santos Pereira, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7705645/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Mar, 2026 Read the published version in Pediatric Cardiology → Version 1 posted 10 You are reading this latest preprint version Abstract Background Adolescents with congenital heart disease (CHD) have high cardiovascular risk (CVR), related to clinical, behavioral and socioeconomic factors. A sedentary lifestyle, physical inactivity and unfavorable socioeconomic conditions can aggravate this risk, while regular physical activity, a healthy diet and lipid profile control are protective factors. Objective To determine the relationship among clinical, behavioral, and socioeconomic factors and CVR in adolescents with CHD. Methods Cross-sectional study with 75 adolescents, aged 10 to 18 years old, attending a reference outpatient service in Alagoas, Brazil. The Physical Activity Questionnaire for Children, Questionnaire for Screen Time of Adolescents, lipid and glycemic profile and Pathobiological Determinants of Atherosclerosis in Youth score were used. Associations were tested by chi-square or Fisher's exact test for categorical variables and Student's t-test for continuous variables. Multivariate binary logistic regression was used by the backward non-conditional method, adjusted for significant confounding factors (p < 0.20). Results A total of 75 adolescents were recruited, 62.6% showed low CVR, 82.7% exhibited excessive sedentary behavior and 90.7% were physically inactive, both associated with lipid alterations. Females had a lower odds ratio (OR) of 0.32 (95% CI = 0.11; 0.91) for higher CVR, while high complexity of CHD had an OR of 4.38 (95% CI = 1.02; 18.69) for high LDL-c levels. Adolescents with lower income had an OR of 3.29 (95% CI = 1.20; 9.08) for low HDL-c levels. Conclusion Adolescents with CHD have a high sedentary lifestyle, low levels of physical activity and clinical and socioeconomic factors that increase cardiovascular risk. Adolescent congenital heart disease sociodemographic factors behavioral factors cardiovascular risk factors Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Congenital heart diseases (CHD) are cardiac malformations, that is, as a group, the second leading cause of mortality in the first year of life[ 1 ]. In Brazil, approximately 30,000 children born annually with CHD, which corresponds to 10 cases for every 1,000 live births, constituting the third leading cause of neonatal death[ 2 ]. CHD can be classified according to pulmonary flow (hyperflow or hypoflow), presence of cyanosis (cyanotic or acyanotic), complexity (simple, moderate and high), and according to the International Classification of Diseases, 10th Revision (ICD-10) (Conotruncal defects; Non-conotruncal defects; Coaction of the aorta; Ventricular septal defect; Atrial septal defect; Other congenital heart diseases)[ 3 – 6 ]. Cardiovascular disease (CVD) represents a major challenge for global public health[ 7 ], being influenced by clinical, behavioral and socioeconomic factors[ 8 ]. In adolescents with CHD, this risk is aggravated due to structural and functional alterations of the heart that may predispose to early cardiovascular complications[ 9 ]. Factors such as sedentary lifestyle, obesity, dyslipidemia and arterial hypertension have been implicated in the CVR; these factors substantially increase their cardiovascular vulnerability[ 9 ] and such factors are established in adolescence[ 10 ]. Adolescents with CHD have higher levels of total cholesterol and low-density lipoprotein cholesterol (LDL), in addition to a higher prevalence of arterial hypertension when, compared to their peers without CHD[ 11 ]. Physical activity plays a fundamental role in mitigating cardiovascular risk[ 12 ], and it is considered an essential protective factor for adolescents with CHD[ 13 ], contributing to blood pressure control and lipid regulation[ 14 ]. Children and adolescents with CHD have a sedentary and inactive lifestyle[ 15 ]. Sedentarism refers to excessive sedentary behavior, such as sitting or lying down for long periods of time with low energy expenditure, while physical inactivity refers to the absence or insufficient practice of physical activity at levels recommended for health[ 16 , 17 ].Sedentary behavior has been associated with excess waist circumference and body fat[ 18 ], and when associated with poor diet, it can lead to the development and cardiometabolic complications[ 19 ], what could increase the risk of CVD[ 20 ]in adolescents with CHD. The complexity of CHD may be related to the cardiovascular risk, so more severe CHD cases may require specific and recurrent medical interventions, wich can lead more spending and limitations to physical activity, and consequently predisposition to obesity, dyslipidemia, and hypertension[ 6 ]. In the general population, sociodemographic conditions such as sex, family income, literacy of caregivers and neighborhood are examples of social determinants of health and significantly influence cardiovascular risk [ 21 ]. Low income and limited caregivers literacy are associated with less access to medical care, healthy food access and opportunities to practice sports, which intensifies sedentary behavior and other risk factors for CVD[ 1 , 22 ]. Poverty itself, in general, is an important predictor of increased risk of CVD, wich can add risk by unhealthy behaviors such as sedentary lifestyle and smoking[ 23 ]. METHODS Study Design This is a cross-sectional observational study, carried out from September 22, 2023 to December 17, 2024 at the regional reference service for outpatient treatment of children and adolescents with CHD in the state of Alagoas, “Casa do Coraçãozinho”, which is a partnership between “Sociedade Beneficente do Coração de Alagoas – CORDIAL” and “Hospital do Coração – HCOR”; it is the first center for pediatric cardiology subspecialties that provides care through the Unified Health System in the state. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist is available in Supplementary file 4. Context The state of Alagoas, where the municipality of Maceió is located in the northeast region of Brazil, has one of the lowest Human Development Indexes (HDI) in the country (0.684), ranking 26th in the national ranking [ 24 ]. Maceió has a municipal HDI (MHDI) of 0.721, while Inhapi has the worst MHDI in the state (0.484). Of the 102 municipalities in Alagoas, 86 have low HDI, and 2 have a very low HDI [ 24 ], marked by poverty, social inequality, low levels of education, limited access to health services and information on healthy habits, whether related to diet or lifestyle, factors that can contribute to the development of cardiovascular diseases[ 26 ]. Therefore, the average MHDI of the municipalities where the research participants reside is 0.574 (Supplementary file 2). Participants Participants were recruited to participate in the study prior after a routine consultation with a pediatric cardiologist or surgeon. Adolescents diagnosed with CHD, with medical records and followed at the referral clinic, aged between 10 and 18 years, of both sexes, were considered eligible for the study. Participants with inability to stand and/or move, inability to speak and/or hear or understand the questions presented, a diagnosis of Down syndrome; pregnancy; diagnosis of dwarfism and participants who refused to have blood collected were excluded. Variables, protocols and standards This study is part of an umbrella Project called “Adolescents with congenital heart disease: A diagnostic study of lifestyle, physical fitness and cardiometabolic risk”. The variables of this study were collected through an interview, using an online platform (Google Forms®). Physical and laboratory examinations were performed, and all responses were tabulated in a Microsoft Excel® spreadsheet. All assessments, including questionnaires, tests and blood collection, were performed in a specific and private room for the research, by a qualified, trained and calibrated team. First, the medical records were analyzed for screening and verification of eligibility criteria. Then, the participants were invited to the data collection room and, if accepted, the informed consent form was signed by the caregivers and the informed assent form by the adolescents (according to Brazilian legislation on research ethics). After acceptance, the questionnaires were applied by interview, related to sociodemographic and clinical data, physical activity practice and sedentary behavior. The research protocol included monitoring of vital signs and physical assessment (blood pressure, weight, height, waist circumference) and blood samples by a trained professional. Outcome variables – Cardiovascular Risk The cardiovascular risk factors analyzed were: blood pressure (BP), anthropometric measurements (body mass index [BMI], waist circumference), non-fasting lipid profile (total cholesterol (TC), triglycerides (TG)), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), and glucose were collected. The variables were analyzed, continuously and categorically. Blood Pressure was measured on the right arm using an Omron digital sphygmomanometer (Hem-7122, São Paulo, Brazil), with the adolescent resting for at least 5 minutes, sitting with their back supported, feet on the floor and right arm resting at heart level. BP was measured twice, at the beginning of the questionnaire and before the physical assessments began according to standardization[ 27 , 28 ]. The percentile based on age and sex was used as the cutoff point for BP assessment, cathegorized as normal if the measurements were under 90th percentile and abnormal, if above 90th percentile [ 29 ]. To assess body mass (in kilograms), was used a portable Omron digital scale (HBF-514c, Japan, 150 kg capacity)[ 30 ]. Height (in meters) was assessed using a portable stadiometer, with the adolescent in an upright position[ 30 ]. BMI data were calculated using Anthroplus software and interpreted according to World Health Organization (WHO) guidelines[ 31 ]. Waist circumference was assessed using a tape measure and refers to the circumference of the abdomen at its narrowest point between the tenth rib and the top of the iliac crest, perpendicular to the long axis of the trunk[ 28 ]. For its assessment, cutoff points were used according to age and sex [ 32 ]. The cutoff point for biochemical variables such as HDL-c, LDL-c, blood glucose, total cholesterol, and blood pressure followed the I Guideline for Atherosclerosis in Childhood (2005) and Update of the Brazilian Guideline on Dyslipidemia and Atherosclerosis Prevention (2017) (Supplementary file 5). The variables were dichotomized for the bivariate analysis, being determined astotal cholesterol: desirable and borderline/High, LDL: desirable and borderline/High, Triglycerides: desirable and borderline/High. To assess cardiovascular risk, the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) score was used, which early stratifies individuals aged 15 to 34 years by adding the values ​​attributed to modifiable and non-modifiable fator [ 33 , 34 ]. The PDAY score is calculated from the sum of points that are equivalent to the non-modifiable (age and sex) and modifiable (TC, HDL-c, BP, fasting glucose, non-HDL cholesterol, smoking and BMI) risk factors for atherosclerosis. Therefore, each risk factor assumes scores, which, when added, will result in the total cardiovascular risk score. Thus, the total score assigned to each risk variable will allow classification into low risk (≤ 0), intermediate risk (1–4), and high risk (≥ 5) for advanced coronary artery lesions. Exposure variables – Physical activity and sedentary behavior, Clinical conditions, sociodemographic factors. Habitual physical activity (PA) was assessed using the PAQ-C (Physical Activity Questionnaire for Children) questionnaire, applied in the form of an interview to the adolescents together with their guardians, which is a validated and reproducible questionnaire for the Brazilian population ( 3 sufficient PA) [ 35 ]recommended for children and adolescents with CHD (≥ 2.87 sufficient PA; <2.87 insufficient PA)[ 36 ]with the aim of estimating the level of habitual physical activity in the last seven days, through nine self-reported questions about habitual PA practice coded from 1 to 5. The final score is calculated from the arithmetic mean of the averages of the first question, the average of the second to eighth question and the average of the ninth[ 37 ]. The questions address : the weekly frequency of leisure and sports activities, the practice of physical activity during physical education class, at lunchtime, after school, in the evening and on weekends, as well as the level of physical activity in the last seven days. Sedentary behavior (SB) was assessed through screen time, which was assessed through questions from the QueST (Questionnaire for Screen Time of Adolescents), developed for Brazilian adolescents to estimate screen time (in hours) in five constructs: studying, working/internship-related activities, watching videos, playing games, and using social media/chat applications [ 38 ]. The participant must answer in hours and minutes the time spent on the activity in question (< 120 minutes adequate SB, ≥ 120 minutes excessive SB), being an easy-to-understand and reproducible questionnaire. The definition of excessive sedentary behavior was used as those who, adding the time of the reported activities, remain in this way for 2 hours or more, being considered sedentary, with the calculation being performed using the formula: ([volume on weekdays*5 + volume on weekend days*2]/7)[ 38 ]. The clinical conditions of the patients, including the type of CHD (cyanotic or acyanotic), complexity (simple, moderate or severe), number of cardiac surgeries (one or 2 or more), heart diseases were categorized according to the group: group 1: Conotruncal defects, group 2: Non-conotruncal defects, group 3: Coarctation of the aorta, group 4: Ventricular septal defect, group 5: Atrial septal defect, group 6: other cardiac and circulatory system anomalies[ 5 ] and the sociodemographic variables: sex (female and male), ethnicity (brown, black, yellow and White, according to self-assessment), family income (≤ 1 minimum wage; >1 minimum wage) considering the minimum wage of 2024 in Brazil ( $ 262,00), caregiver literacy (< 10 years, ≥ 10 years), place of residence (capital, other locations) were evaluated through the medical records and questionnaire respectively. Data analysis The researchers responsible for data collection received prior training to minimize biases, in addition to conducting a pilot study. Relative and absolute frequencies (95% confidence intervals) were calculated for categorical variables and mean (or median) and standard deviation (or interquartile range) for continuous variables. The normality (Gaussian distribution) of the variables was analyzed using the Shapiro-Wilk test, histograms, kurtosis and skewness, and pnorm. Chi-Square (X 2 ) analysis was performed to observe the association between the outcome variables and the exposure variables. In the binary logistic regression analysis, all predictor variables were included simultaneously, using the Backward non-conditional procedure to remove variables with p < 0.20 one at a time from the highest p value until reaching the final value. Student's t-test and Mann-Whitney U-test were used to test the difference between the sexes in the descriptive analyses of the data. All analyses were performed in the STATA® statistical package version 13.0 and in GraphPad Prism® version 5.0, establishing a p < 0.05. Ethical Aspects The study (CAAE: 70383923.9.0000.5012) was approved by the Research Ethics Committee of UFAL (Opinion No. 6,420,140). The adolescents' participation occurred after the signing of the Free and Informed Consent Form (FICF) by their guardians and the Free and Informed Assent Form (FIAF) by the participants. All information was stored with classified access to the researchers, ensuring confidentiality and privacy of the participants. RESULTS A total of 108 participants were eligible to participate in the study, of which 11 were excluded and 2 refused to participate 75 adolescents were included at the final sample (Fig. 1 ); 42.67% were male and 57.33% female, with a mean age of 12.70 ± 2.21. The majority were adolescents from the interior of Alagoas (53.3%), 82.7% of them declared themselves as brown (n = 51), with a family income predominantly or less (50.6%) (Table 1 ). The PDAY cardiovascular risk score was observed in the majority of the sample at low risk levels (62.6%); a low frequency of cardiovascular risk factors was also be observed, such as acceptable levels of blood pressure in 80.0% of the sample, normal total cholesterol in 66.6%, normal LDL-c in 85.3%, normal blood glucose in 96.0% and normal waist circumference in 81.3%; however, abnormal values were observed in the majority of participants in the HDL-c analysis (56.0%); 11 adolescents were not fasting on the day of the study (Table 1 ). Table 1 Characteristics of adolescent participants with Congenital Heart Disease Variables Total (n = 75) n (%) Age 10–14 years 56 (74,7) 15–18 years 19 (25,3) Sex Masculine 32 (42,7) Feminine 43 (57,3) Skin Color Brown, Black, Yellow 62 (82,6) White 13 (17,3) Education of the person in charge 10 anos of literacy 35 (46,7) Income ≤ 1 minimum wage ( $ 262,00) 38 (50,6) > 1 minimum wage ( $ 262,00) 37 (49,3) Place of Origin Capital (IDHM = 0,721) 35 (46,6) Other locations (IDHM = 0,574) 40 (53,3) Physical activity (score) Insufficiently Active (< 2,87) 68 (90,7) Active (≥ 2,87) 7 (9,33) Sedentary Behavior on Screens Normal ( 90º percentil) 15 (20,0) Total Cholesterol Desirable( 200 mg/dL) 8 (10,6) HDL-c Low ( 40 mg/dL) 33 (44,0) LDL-c Desirable( 130 mg/dL) 2 (2,6) Triglycerides Desirable(< 90 mg/dL) 48 (64,0) Borderline(90–129 mg/dL) 11 (14,6) High(≥ 130 mg/dL) 16 (21,3) Blood glucose Normal ( 100 mg/dL) 3 (4,0) Waist Circumference Suitable (in cm by sex and age) 61 (81,3) Inadequate (in cm by sex and age) 14 (18,6) PDAY (score) Low risk(≤ 0) 62 (62,7) Intermediate risk(≥ 1 e ≤ 4) 21 (28,0) High risk(≥ 5) 7 (9,3) PDAY: Pathobiological Determinants of Atherosclerosis in Youth; HDL: High Density Lipoprotein; LDL: Low Density Lipoprotein. Weighted Biochemical Values in Fasting and Non−Fasting. The most prevalent heart diseases in the sample were (Fig. 2 ): Atrial Septal Defect (ASD) (16.0%), Ventricular Septal Defect (VSD) (13.3%). Regarding the characteristics of the clinical factors of CHD, 69.3% of the adolescents did not present cyanosis at the time of data collection. Regarding the complexity of the heart disease, 58.6% of the cases were classified as simple, 34.6% as moderately complex and 6.6% as complex. Among the adolescents, 53.3% had never undergone any cardiac surgery related to CHD, 32.0% had undergone only one, and only 14.6% had undergone more than one surgery to correct the heart disease throughout their lives. In Table 2 , an association was observed between PDAY and sex (p = 0.015), in which male adolescents presented higher intermediate to high CVR. Low HDL-c was associated with lower income (p = 0.008). Furthermore, high LDL-c was associated with moderate to high complexity heart disease (p = 0.022). No significant associations were observed between the other variables analyzed (Supplementary file 1). Figure 3 (Supplementary file 3) shows the odds ratio of cardiovascular risk outcomes and demographic, behavioral, and clinical exposures assessed in this study. After adjusting for significant confounders considering p < 0.20, a significant association was found between moderate/high PDAY and sex (p = 0.033), in which male sex is associated with higher CVR. High LDL-c was associated with heart disease complexity (p = 0.046), indicating that greater complexity is associated with higher concentration of this lipid parameter. HDL-c showed an association with family income (p = 0.021), in which lower income was associated with lower concentration of this lipid parameter. The associations between sex and PDAY were adjusted for the following variables: number of surgeries, physical activity, and sedentary behavior; between LDL and heart disease complexity were adjusted for age and location, while the associations between HDL and income were adjusted for age, sex, and location. The other variables did not show statistical significance. Table 2 Bivariate analysis of the association of the second sociodemographic, clinical and behavioral variables of cardiovascular risk factors of adolescents with congenital heart disease treated at the reference outpatient clinic in Alagoas. Risk factor PDAY intermediate to high Blood Pressure high Waist Perimeter excessive Blood glucose elevated Total Cholesterol borderline to altered HDL-c low LDL-c borderline to altered Triglycerides borderline to altered % X 2 / p-valor % X 2 / p-valor % X 2 / p-valor % X 2 / p-valor % X 2 / p-valor % X 2 / p-valor % X 2 / p-valor % X 2 / p-valor Age 10 a 14 years 78,6 0,3602 (0,548) 93,3 3,4539 (0,096)* 75,0 0,0008 (1,000)* 66,7 0,745 (1,000)* 72,0 0,1410 (0,707) 80,9 1,9938 (0,158) 90,9 1,7979 (0,271*) 81,5 1,0358 (0,309) Sex Masculine 60,7 5,9493 (0,015) 40,0 0,0545 (0,815) 25,0 1,8227 (0,216)* 100,0 4,1992 (0,073)* 32,0 1,7442 (0,187) 50,0 2,0985 (0,147) 36,4 0,2094 (0,647) 44,4 0,0545 (0,815) Income ≤ 1 Minimum wage em dólar 50,0 0,0079 (0,929) 46,7 0,1200 (0,729) 50,0 0,0025 (0,960) 66,6 0,3201 (1,000)* 40,0 1,7070 (0,191) 64,3 7,0832 (0,008) 54,5 0,0776 (0,781) 63,0 2,5519 (0,110) Education of the person in charge < 10 years 50,0 0,1995 (0,655) 46,7 0,3348 (0,563) 50,0 0,0638 (0,801) 100,0 2,7344 (0,243)* 64,0 1,7143 (0,190) 61,9 2,8177 (0,093 45,4 0,3215 (0,571 51,8 0,0372 (0,847) Location Other Locations 46,4 0,8559 (0,355) 53,3 0,0000 (1,000) 50,0 0,0638 (0,801) 0,0 3,5714 (0,097)* 64,0 1,7143 (0,190) 59,5 1,4697 (0,225) 72,7 1,9481 (0,163) 63,0 1,5718 (0,210) Complexity of Heart Disease Moderate/Complex 53,5 2,7597 (0,097) 40,0 0,0137 (0,907) 50,0 0,4425 (0,506) 66,7 0,8271 (0,566)* 48,0 0,6873 (0,407) 42,8 0,0914 (0,762) 72,7 5,2393 (0,022) 44,4 0,1684 (0,682) Heart disease Cyanotic 8,5 0,0923 (0,761) 20,0 1,0033 (0,369)* 50,0 2,5113 (0,113) 33,3 0,0105 (1,000)* 24,0 0,7839 (0,376) 33,3 0,3192 (0,572) 36,4 0,1968 (0,657) 29,6 0,0213 (0,884) Number of Surgeries More than 1 60,7 3,5426 (0,060) 53,3 0,5540 (0,758) 59,3 0,8207 (0,617)* 0,0 2,7344 (0,403)* 52,0 0,4330 (0,805) 42,8 0,6198 (0,734) 45,4 2,1694 (0,338) 51,8 0,6629 (0,718) Physical Activity Insufficient 82,1 3,8362 (0,095)* 80,0 2,5210 (0,138)* 91,7 0,0169 (1,000)* 100,0 0,3217 (1,000)* 96,0 1,2605 (0,262) 88,1 0,7459 (0,388) 90,9 0,0009 (0,976) 88,9 0,1576 (0,691) Sedentary Behavior Excess 92,9 3,2382 (0,114)* 93,3 1,4888 (0,445)* 75,0 0,5860 (0,426)* 100,0 0,6552 (1,000)* 84,0 0,0465 (0,829) 83,3 0,0296 (0,863) 100,0 2,7029 (0,100) 18,5 0,0414 (0,839) PDAY: Pathobiological Determinants of Atherosclerosis in Youth; HDL: High Density Lipoprotein; LDL: Low Density Lipoprotein. *Fisher's exact test was applied for variables with n<5. DISCUSSION The main findings of this study were the intermediate to high PDAY cardiovascular risk score (37.3%) in adolescents with congenital heart disease, associated with the male gender. Furthermore, adolescents with more complex heart disease demonstrated high levels of LDL-c and those with lower incomes presented low levels of HDL-c. In addition, adolescents demonstrated insufficient levels of physical activity (90.7%) simultaneously with high levels of sedentary behavior (82.7%). Children and adolescents with CHD are predisposed to greater cardiovascular risk factors [ 39 ]. In the current study, a low cardiovascular risk was identified among most adolescents, however, 37.3% demonstrated intermediate to high risk. However, this finding does not indicate the absence of worrying factors, especially considering the cardiovascular context in which the studied population finds itself, in addition to the cardiovascular risk inherent to congenital heart disease [ 9 ]. Adolescence is the phase in which habits and conditions are formed that have an impact throughout life, such as poor diet, physical inactivity, obesity, hypertension and dyslipidemia, which perpetuate until adulthood and predisposes to CVR increase [ 40 ]. In this period, the presence of two or more risk factors considered influential in the increase in CVR in the following 10 years [ 34 ]. A meta-analysis study conducted with children and adults with CHD observed an association between individuals living with CHD and cardiovascular risk, describing that individuals with CHD, adults or children, have a 3.12 times greater chance of developing CVD, compared to those without CHD[ 39 ]. Also, Zacharias et al. (2016) observed in their study that individuals with CHD have a significantly higher risk (OR = 12.22) of developing a stroke, especially those with more complex CHD, compared to their healthy peers [ 41 ], which can be explained by the hemodynamic context of these individuals, such as cardiac flow, volume and blood pressure. In addition, children with CHD who underwent cardiac surgeries have a significantly higher mortality rate compared to their healthy peers who underwent non-cardiac surgeries (moderate: 3.9% and severe: 8.2%)[ 42 ].However, although 37.3% presented a high to intermediate risk, a difference was observed between the sexes, in which males presented a higher CVR when compared to females. This difference can be explained by biological, behavioral, social and cultural factors. Hormonal factors can act as a protective factor against CVR in females, in addition to culturally higher aware of women about health care, and in males, predominant levels of HDL-c and high blood pressure represent an important cardiovascular risk factor [ 34 ]. The influence of sociodemographic factors should also be considered in the analysis of cardiovascular risk. As with family income, adolescents with lower incomes are 3.29 times more likely to have low HDL-C levels (OR = 3.29; p = 0.021). Frota et al. (2007) report the importance of family income for better treatment and prognosis of children and adolescents living with CHD, making the investment necessary for the continuity of treatment, travel for consultations and routine exams, as well as maintenance of healthy habits essential for child growth and development relevant[ 43 ]. In the study by Faria and collaborators (2016), regional differences were observed, where there was a higher prevalence of low levels of HDL-c cholesterol in the North and Northeast regions, characterized by low HDI rates, combined with the prevalence of low triglycerides, indicating the presence of obesity and inadequate lifestyles and characterizing a process of atherogenic dyslipidemia [ 44 ]. Pacheco and collaborators (2022), in a study carried out in Florianópolis, explain that lower differences in HDL-c values ​​found in children and adolescents with CHD – associated with C-reactive protein in the same study – can be explained due to exposure to inflammatory stimuli, such as therapeutic procedures and infections, exercise and diet restrictions[ 45 ]. This association reinforces the relevance of the socioeconomic context and its influence on risk factors, considering limited access to: healthy food, opportunities for physical activity, adequate medical monitoring, and sometimes access to appropriate guidance. Maternal education, although not associated with CVR in this study, represents a risk factor with a broad global effect. Studies cite the caregivers literacy as a contributing factor to the development of coronary disease and, associated with family income, impacts the lives of individuals due to exposure to the factors mentioned above, impacting the patient's survival[ 46 , 47 ]. The complexity of the heart disease was the only clinical factor that demonstrated an association in the present study, where it was observed that adolescents with more severe heart diseases had high LDL levels (OR = 4.38; 95% CI = 1.02–18.69; p = 0.046). This finding indicates a possible relationship between the severity of the heart condition and metabolic changes, including physiological responses to heart disease that involve adaptations in lipid metabolismo [ 11 ]. However, no studies were found associating the complexity of heart disease with LDL-c levels in adolescentes and further studies are needed to determine the exact cause of this association. Severe heart disease is associated with an increase in heart failure, which leads to decreased functional capacity, muscle strength, need for surgical interventions and limitations in physical activity resulting in possible metabolic changes. However, little is known about the impact on lipid metabolismo [ 48 ]. The Bogalusa Heart Study demonstrated that high levels of LDL-c in childhood are associated with the early development of atherosclerotic plaques, and that altered lipid profiles in childhood are perpetuated throughout life, increasing CVR[ 49 , 50 ]. In a study carried out with 52 children with CHD and a mean age of 10.4 ± 2.8 years, elevated total and LDL cholesterol parameters were observed, characterized by dyslipidemia; however, there was no difference in this parameter between children with CHD and their healthy peers [ 48 ]. Therefore, studies are needed to deepen the influence of the complexity of heart disease on lipid metabolism and thus create strategies that optimize metabolism and minimize the effects of CC on increasing RCV. In this study, the majority of adolescents stood out as insufficiently active (90.7%), similar to another Brazilian study carried out with children and adolescents with congenital heart disease, which used the same instrument, which observed 95% of the sample as insufficiently active[ 51 ]. Additionally, excessive sedentary behavior was observed[ 51 ]. The higher frequency of physical inactivity and excessive sedentary behavior has been observed in the population with CHD in other studies with adolescents [ 9 , 52 , 53 ]. In the long term, these behaviors can contribute to the development of chronic non-communicable diseases, such as obesity, hypertension, high cholesterol, metabolic syndrome and cardiovascular diseases[ 54 ]. An interesting finding of our study is that, although 37.3% of adolescents have intermediate/high cardiovascular risk, only 9.3% of them have an adequate level of physical activity. In a review study, 9 of the 18 studies evaluated did not find significant differences between the level of physical activity between children with and without CHD, and 4 found that children with CHD are more inactive than their healthy peers. In addition, excessive sedentary behavior was also observed [ 55 ]. Brudy et al. (2020), in their cohort study, observed that 75.9% of children with CHD were active; however, despite not finding differences with their healthy peers, they observed that children who were overweight, obese or had severe heart disease practiced less activities than others [ 56 ]. In another study carried out with adolescent students without CHD, also using the PDAY score to stratify cardiovascular risk, similarly to our study, no significant results were found regarding the relationship between sedentary behavior and physical activity with CVR[ 34 ].This finding reinforces the complexity of the relationship between physical activity and cardiovascular risk, indicating that interventions need to be accompanied by strategies to improve other healthy habits in addition to physical activity. Excessive sedentary behavior is present in this study in 82.7% of adolescents in the current sample, in common with adolescents without CHD[ 57 ]. In a systematic review, in which studies also used screen time as an evaluation parameter, it was observed that > 2 hours of screen use in children and adolescents is associated with worse body composition, in addition, it is also associated with increased health risk [ 58 ]. An epidemiological study with Mendelian randomization showed that excessive sedentary behavior was associated with a higher risk of type 2 diabetes mellitus, hypertension and dyslipidemia, with increased total cholesterol and LDL-c, and lower HDL-c cholesterol levels [ 59 ]. Another recent study demonstrated that excessive CS [ 60 ] is associated with increased TG levels and reduced HDL cholesterol, also promoting insulin resistance and increased body fat deposition and lipid concentrations. Furthermore, it was observed that prolonged exposure to CS for 7 days, even with the maintenance of physical activity (PA) levels at any intensity, did not change lipid concentrations [ 60 ]. However, excessive sedentary behavior is often associated with risk factors for cardiovascular disease, regardless of the level of physical activity, whether moderate or vigorous. Thus, reducing sedentary time becomes an essential strategy for improving lifestyle and promoting cardiovascular health [ 61 ]. Furthermore, overprotection by parents and caregivers is an important factor that contributes to physical inactivity, leading to excessive sedentary behavior, motor skill deficits and consequently exacerbating cardiovascular risk factors [ 62 ]. This highlights the complexity and importance of recognizing the simultaneity of behaviors that can exacerbate cardiovascular risk, which suggests the need for greater attention in assisting adolescents living with CHD. This study has limitations due to its cross-sectional design, which prevents the establishment of causality between the factors analyzed and cardiovascular risk. Data on family history of cardiovascular diseases were also not collected. The PDAY score used is a validated score for adolescents aged 15 and over, although its stratification considers the same score for adolescents aged 10 to 19. However, the study also has relevant strengths, such as the investigation of a population from the northeast region of the country with a low HDI, the use of validated questionnaires, and the collection of data considering multiple factors simultaneously, including clinical, behavioral, sociodemographic and cardiovascular risk aspects. In conclusion, adolescents with CHD demonstrated high risk characteristics, in which only 9.3% of adolescents are active and present high rates of sedentary behavior (90.7%), factors that may contribute to increased cardiovascular risk in the long term. Although only 37.3% presented intermediate/high risk, boys were more vulnerable compared to girls. Furthermore, clinical factors, such as the complexity of the heart disease, were associated with high LDL levels, and the analysis of sociodemographic factors revealed that income significantly influences cardiovascular risk, with a higher prevalence of risk among those with lower income. These results highlight the need for cohort studies to investigate the causality between the conditions studied and cardiovascular risk, in addition to individualized interventions, such as awareness-raising actions among families and professionals about the benefits of physical activity and reducing sedentary behavior. Multidisciplinary training, social and school inclusion, in addition to the implementation of public policies for cardiovascular rehabilitation, considering clinical, socioeconomic and cultural factors, and actions to mitigate the impacts of sociodemographic factors, aiming to improve the prognosis of adolescents with congenital heart disease. Declarations Conflict of interest: The authors declare no conflict of interest. Ethical aspects This study followed the ethical principles of respect for people's autonomy, as outlined in Resolution No. 466 of December 12. Funding: This study was funded by the Postgraduate Program in Health Sciences (PPGCS), through PROAP, for biochemical analysis performed in an outsourced laboratory. In addition, a master's scholarship was granted by FAPEAL, under No. E:60030.000000126/2023. Author Contribution Study concept and design: Marylia Santos Pereira and Luiz Rodrigo Augustemak de Lima. Data acquisition: Marylia Santos Pereira, Ana Carla Porciuncula Cavalcante, Adrielly Suely Santos Pereira. Data analysis and interpretation: Marylia Santos Pereira and Luiz Rodrigo Augustemak de Lima. Critical review of the manuscript: Marylia Santos Pereira, Ana Carla Porciuncula Cavalcante, Adrielly Suely Santos Pereira, Christefany Régia Braz Costa, Filipe Antonio de Barros Sousa, Isabela de Carlos Back , Luiz Rodrigo Augustemak de Lima. Acknowledgement We would like to express our gratitude to the Alagoas Research Support Foundation (FAPEAL) and the Postgraduate Program in Health Sciences (PPGCS) for granting the master's scholarship, to Casa do Coraçãozinho and to the Cordial Foundation, especially to the coordination, reception and nursing staff, for making this study possible and providing the technical and logistical support necessary for its execution, and above all for their hospitality and fundamental contribution to the completion of data collection. We would like to thank the research participants and their families, who, by volunteering their time and information, contributed in an indispensable way to the completion of this work. 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16:08:22","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":170727,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7705645/v1/7168e79ec2edba8c7966bc6b.html"},{"id":97367116,"identity":"d101b3df-05bb-4acb-9c56-14f5759cfb9e","added_by":"auto","created_at":"2025-12-03 16:16:31","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":63460,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResearch collection flowchart.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7705645/v1/ff61720a27a76a3e0a1ff78b.jpg"},{"id":97367613,"identity":"89e9d98e-acb0-4602-b4d1-3e66c3492738","added_by":"auto","created_at":"2025-12-03 16:19:48","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":13007,"visible":true,"origin":"","legend":"\u003cp\u003eMost prevalent heart diseases among adolescents with congenital heart disease treated at the reference outpatient clinic in Alagoas.\u003c/p\u003e\n\u003cp\u003e\u003csub\u003eDVSVD: Double Outlet Right Ventricle; EA: Aortic Stenosis; T4F: Tetralogy of Fallot; ESBA: Subaortic Stenosis; EPV: Valvular Pulmonary Stenosis; AP: Pulmonary Atresia; AT: Tricuspid Atresia; DSAV: Atrioventricular Septal Defect; COA: Coarctation of the Aorta; VSD: Ventricular Septal Defect; ASD: Atrial Septal Defect; PFO: Patent Foramen Ovale; PDA: Patent Ductus Arteriosus; PVM: Mitral Valve Prolapse; MC: Non-compacted Myocardium. Group 1: Conotruncal Defects; Group 2: Non-conotruncal Defects; Group 3: Coarctation of the Aorta; Group 4: Ventricular Septal Defect; Group 5: Atrial Septal Defect; Group 6: Other Congenital Heart Diseases.\u003c/sub\u003e\u003c/p\u003e\n\u003cp\u003e\u003csub\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7705645/v1/007100d8ca8083889613f8f6.png"},{"id":97258201,"identity":"27ce9f8e-c40e-4427-b306-e80a59bf144d","added_by":"auto","created_at":"2025-12-02 13:46:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40983,"visible":true,"origin":"","legend":"\u003cp\u003eOdds ratios of cardiovascular risk and demographic, behavioral, and clinical exposures\u003c/p\u003e\n\u003cp\u003e\u003csub\u003ePDAY: Pathobiological Determinants of Atherosclerosis in Youth; HDL: High Density Lipoprotein; LDL: Low Density Lipoprotein. OR: Odds Ratio; . 95%CI = 95% confidence interval; p-value = statistical significance p \u0026lt; 0.20, NS: not significant. All variables were tested simultaneously and variables were removed in the Backward procedure starting with the highest p-value \u0026lt; 0.20 and significant model p \u0026lt; 0.05. Model A (PDAY): p = 0.0049; Model B (BP): p = 0.1242; Model C (PC): p = 0.2784; Model D (Glycemia): p = 0.1201 ; Model E (TC): p = 0.0713; Model F (HDL): p = 0.0110; Model G (LDL): p = 0.0347; Model H (TG): p= 0.1888\u003c/sub\u003e\u003c/p\u003e","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7705645/v1/4cdfde5bd7ecbe824ba9995e.png"},{"id":104740008,"identity":"ac6a628b-ab9a-4126-b142-3d56be4a44a5","added_by":"auto","created_at":"2026-03-16 16:14:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1233816,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7705645/v1/41ba0750-5216-46ae-91ae-7795ff575ecc.pdf"},{"id":97258196,"identity":"abda7f98-2efe-404c-868c-20fb7d4ec699","added_by":"auto","created_at":"2025-12-02 13:46:43","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":45579,"visible":true,"origin":"","legend":"","description":"","filename":"SUPPLEMENTARYMATERIAL.docx","url":"https://assets-eu.researchsquare.com/files/rs-7705645/v1/fa94d68f555d5e69eebba36a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eCardiovascular Risk in Adolescents With Congenital Heart Disease Living in a Low-income Region: Cross-sectional Associations With Clinical, Behavioral and Sociodemographic Factors\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eCongenital heart diseases (CHD) are cardiac malformations, that is, as a group, the second leading cause of mortality in the first year of life[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In Brazil, approximately 30,000 children born annually with CHD, which corresponds to 10 cases for every 1,000 live births, constituting the third leading cause of neonatal death[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. CHD can be classified according to pulmonary flow (hyperflow or hypoflow), presence of cyanosis (cyanotic or acyanotic), complexity (simple, moderate and high), and according to the International Classification of Diseases, 10th Revision (ICD-10) (Conotruncal defects; Non-conotruncal defects; Coaction of the aorta; Ventricular septal defect; Atrial septal defect; Other congenital heart diseases)[\u003cspan additionalcitationids=\"CR4 CR5\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCardiovascular disease (CVD) represents a major challenge for global public health[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], being influenced by clinical, behavioral and socioeconomic factors[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In adolescents with CHD, this risk is aggravated due to structural and functional alterations of the heart that may predispose to early cardiovascular complications[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Factors such as sedentary lifestyle, obesity, dyslipidemia and arterial hypertension have been implicated in the CVR; these factors substantially increase their cardiovascular vulnerability[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] and such factors are established in adolescence[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Adolescents with CHD have higher levels of total cholesterol and low-density lipoprotein cholesterol (LDL), in addition to a higher prevalence of arterial hypertension when, compared to their peers without CHD[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePhysical activity plays a fundamental role in mitigating cardiovascular risk[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], and it is considered an essential protective factor for adolescents with CHD[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], contributing to blood pressure control and lipid regulation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Children and adolescents with CHD have a sedentary and inactive lifestyle[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Sedentarism refers to excessive sedentary behavior, such as sitting or lying down for long periods of time with low energy expenditure, while physical inactivity refers to the absence or insufficient practice of physical activity at levels recommended for health[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].Sedentary behavior has been associated with excess waist circumference and body fat[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and when associated with poor diet, it can lead to the development and cardiometabolic complications[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], what could increase the risk of CVD[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]in adolescents with CHD. The complexity of CHD may be related to the cardiovascular risk, so more severe CHD cases may require specific and recurrent medical interventions, wich can lead more spending and limitations to physical activity, and consequently predisposition to obesity, dyslipidemia, and hypertension[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the general population, sociodemographic conditions such as sex, family income, literacy of caregivers and neighborhood are examples of social determinants of health and significantly influence cardiovascular risk [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Low income and limited caregivers literacy are associated with less access to medical care, healthy food access and opportunities to practice sports, which intensifies sedentary behavior and other risk factors for CVD[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Poverty itself, in general, is an important predictor of increased risk of CVD, wich can add risk by unhealthy behaviors such as sedentary lifestyle and smoking[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003e This is a cross-sectional observational study, carried out from September 22, 2023 to December 17, 2024 at the regional reference service for outpatient treatment of children and adolescents with CHD in the state of Alagoas, \u0026ldquo;Casa do Cora\u0026ccedil;\u0026atilde;ozinho\u0026rdquo;, which is a partnership between \u0026ldquo;Sociedade Beneficente do Cora\u0026ccedil;\u0026atilde;o de Alagoas \u0026ndash; CORDIAL\u0026rdquo; and \u0026ldquo;Hospital do Cora\u0026ccedil;\u0026atilde;o \u0026ndash; HCOR\u0026rdquo;; it is the first center for pediatric cardiology subspecialties that provides care through the Unified Health System in the state. The STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) checklist is available in Supplementary file 4.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eContext\u003c/h3\u003e\n\u003cp\u003eThe state of Alagoas, where the municipality of Macei\u0026oacute; is located in the northeast region of Brazil, has one of the lowest Human Development Indexes (HDI) in the country (0.684), ranking 26th in the national ranking [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Macei\u0026oacute; has a municipal HDI (MHDI) of 0.721, while Inhapi has the worst MHDI in the state (0.484). Of the 102 municipalities in Alagoas, 86 have low HDI, and 2 have a very low HDI [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], marked by poverty, social inequality, low levels of education, limited access to health services and information on healthy habits, whether related to diet or lifestyle, factors that can contribute to the development of cardiovascular diseases[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Therefore, the average MHDI of the municipalities where the research participants reside is 0.574 (Supplementary file 2).\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eParticipants were recruited to participate in the study prior after a routine consultation with a pediatric cardiologist or surgeon. Adolescents diagnosed with CHD, with medical records and followed at the referral clinic, aged between 10 and 18 years, of both sexes, were considered eligible for the study. Participants with inability to stand and/or move, inability to speak and/or hear or understand the questions presented, a diagnosis of Down syndrome; pregnancy; diagnosis of dwarfism and participants who refused to have blood collected were excluded.\u003c/p\u003e\n\u003ch3\u003eVariables, protocols and standards\u003c/h3\u003e\n\u003cp\u003eThis study is part of an umbrella Project called \u0026ldquo;Adolescents with congenital heart disease: A diagnostic study of lifestyle, physical fitness and cardiometabolic risk\u0026rdquo;. The variables of this study were collected through an interview, using an online platform (Google Forms\u0026reg;). Physical and laboratory examinations were performed, and all responses were tabulated in a Microsoft Excel\u0026reg; spreadsheet. All assessments, including questionnaires, tests and blood collection, were performed in a specific and private room for the research, by a qualified, trained and calibrated team.\u003c/p\u003e\u003cp\u003eFirst, the medical records were analyzed for screening and verification of eligibility criteria. Then, the participants were invited to the data collection room and, if accepted, the informed consent form was signed by the caregivers and the informed assent form by the adolescents (according to Brazilian legislation on research ethics). After acceptance, the questionnaires were applied by interview, related to sociodemographic and clinical data, physical activity practice and sedentary behavior. The research protocol included monitoring of vital signs and physical assessment (blood pressure, weight, height, waist circumference) and blood samples by a trained professional.\u003c/p\u003e\n\u003ch3\u003eOutcome variables – Cardiovascular Risk\u003c/h3\u003e\n\u003cp\u003eThe cardiovascular risk factors analyzed were: blood pressure (BP), anthropometric measurements (body mass index [BMI], waist circumference), non-fasting lipid profile (total cholesterol (TC), triglycerides (TG)), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), and glucose were collected. The variables were analyzed, continuously and categorically.\u003c/p\u003e\u003cp\u003eBlood Pressure was measured on the right arm using an Omron digital sphygmomanometer (Hem-7122, S\u0026atilde;o Paulo, Brazil), with the adolescent resting for at least 5 minutes, sitting with their back supported, feet on the floor and right arm resting at heart level. BP was measured twice, at the beginning of the questionnaire and before the physical assessments began according to standardization[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The percentile based on age and sex was used as the cutoff point for BP assessment, cathegorized as normal if the measurements were under 90th percentile and abnormal, if above 90th percentile [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo assess body mass (in kilograms), was used a portable Omron digital scale (HBF-514c, Japan, 150 kg capacity)[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Height (in meters) was assessed using a portable stadiometer, with the adolescent in an upright position[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. BMI data were calculated using Anthroplus software and interpreted according to World Health Organization (WHO) guidelines[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eWaist circumference was assessed using a tape measure and refers to the circumference of the abdomen at its narrowest point between the tenth rib and the top of the iliac crest, perpendicular to the long axis of the trunk[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. For its assessment, cutoff points were used according to age and sex [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e The cutoff point for biochemical variables such as HDL-c, LDL-c, blood glucose, total cholesterol, and blood pressure followed the I Guideline for Atherosclerosis in Childhood (2005) and Update of the Brazilian Guideline on Dyslipidemia and Atherosclerosis Prevention (2017) (Supplementary file 5). The variables were dichotomized for the bivariate analysis, being determined astotal cholesterol: desirable and borderline/High, LDL: desirable and borderline/High, Triglycerides: desirable and borderline/High.\u003c/p\u003e\u003cp\u003eTo assess cardiovascular risk, the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) score was used, which early stratifies individuals aged 15 to 34 years by adding the values ​​attributed to modifiable and non-modifiable fator [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The PDAY score is calculated from the sum of points that are equivalent to the non-modifiable (age and sex) and modifiable (TC, HDL-c, BP, fasting glucose, non-HDL cholesterol, smoking and BMI) risk factors for atherosclerosis. Therefore, each risk factor assumes scores, which, when added, will result in the total cardiovascular risk score. Thus, the total score assigned to each risk variable will allow classification into low risk (\u0026le;\u0026thinsp;0), intermediate risk (1\u0026ndash;4), and high risk (\u0026ge;\u0026thinsp;5) for advanced coronary artery lesions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExposure variables \u0026ndash; Physical activity and sedentary behavior, Clinical conditions, sociodemographic factors.\u003c/b\u003e\u003c/p\u003e\u003cp\u003eHabitual physical activity (PA) was assessed using the PAQ-C (Physical Activity Questionnaire for Children) questionnaire, applied in the form of an interview to the adolescents together with their guardians, which is a validated and reproducible questionnaire for the Brazilian population (\u0026lt;\u0026thinsp;3 insufficient PA, \u0026gt;\u0026thinsp;3 sufficient PA) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]recommended for children and adolescents with CHD (\u0026ge;\u0026thinsp;2.87 sufficient PA; \u0026lt;2.87 insufficient PA)[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]with the aim of estimating the level of habitual physical activity in the last seven days, through nine self-reported questions about habitual PA practice coded from 1 to 5.\u003c/p\u003e\u003cp\u003eThe final score is calculated from the arithmetic mean of the averages of the first question, the average of the second to eighth question and the average of the ninth[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The questions \u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003eaddress\u003c/span\u003e: the weekly frequency of leisure and sports activities, the practice of physical activity during physical education class, at lunchtime, after school, in the evening and on weekends, as well as the level of physical activity in the last seven days.\u003c/p\u003e\u003cp\u003eSedentary behavior (SB) was assessed through screen time, which was assessed through questions from the QueST (Questionnaire for Screen Time of Adolescents), developed for Brazilian adolescents to estimate screen time (in hours) in five constructs: studying, working/internship-related activities, watching videos, playing games, and using social media/chat applications [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The participant must answer in hours and minutes the time spent on the activity in question (\u0026lt;\u0026thinsp;120 minutes adequate SB, \u0026ge;\u0026thinsp;120 minutes excessive SB), being an easy-to-understand and reproducible questionnaire. The definition of excessive sedentary behavior was used as those who, adding the time of the reported activities, remain in this way for 2 hours or more, being considered sedentary, with the calculation being performed using the formula: ([volume on weekdays*5\u0026thinsp;+\u0026thinsp;volume on weekend days*2]/7)[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe clinical conditions of the patients, including the type of CHD (cyanotic or acyanotic), complexity (simple, moderate or severe), number of cardiac surgeries (one or 2 or more), heart diseases were categorized according to the group: group 1: Conotruncal defects, group 2: Non-conotruncal defects, group 3: Coarctation of the aorta, group 4: Ventricular septal defect, group 5: Atrial septal defect, group 6: other cardiac and circulatory system anomalies[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] and the sociodemographic variables: sex (female and male), ethnicity (brown, black, yellow and White, according to self-assessment), family income (\u0026le;\u0026thinsp;1 minimum wage; \u0026gt;1 minimum wage) considering the minimum wage of 2024 in Brazil (\u003cspan\u003e$\u003c/span\u003e 262,00), caregiver literacy (\u0026lt;\u0026thinsp;10 years, \u0026ge; 10 years), place of residence (capital, other locations) were evaluated through the medical records and questionnaire respectively.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData analysis\u003c/h2\u003e\u003cp\u003eThe researchers responsible for data collection received prior training to minimize biases, in addition to conducting a pilot study. Relative and absolute frequencies (95% confidence intervals) were calculated for categorical variables and mean (or median) and standard deviation (or interquartile range) for continuous variables. The normality (Gaussian distribution) of the variables was analyzed using the Shapiro-Wilk test, histograms, kurtosis and skewness, and pnorm.\u003c/p\u003e\u003cp\u003eChi-Square (X\u003csup\u003e2\u003c/sup\u003e) analysis was performed to observe the association between the outcome variables and the exposure variables. In the binary logistic regression analysis, all predictor variables were included simultaneously, using the Backward non-conditional procedure to remove variables with p\u0026thinsp;\u0026lt;\u0026thinsp;0.20 one at a time from the highest p value until reaching the final value. Student's t-test and Mann-Whitney U-test were used to test the difference between the sexes in the descriptive analyses of the data. All analyses were performed in the STATA\u0026reg; statistical package version 13.0 and in GraphPad Prism\u0026reg; version 5.0, establishing a p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eEthical Aspects\u003c/h3\u003e\n\u003cp\u003eThe study (CAAE: 70383923.9.0000.5012) was approved by the Research Ethics Committee of UFAL (Opinion No. 6,420,140). The adolescents' participation occurred after the signing of the Free and Informed Consent Form (FICF) by their guardians and the Free and Informed Assent Form (FIAF) by the participants. All information was stored with classified access to the researchers, ensuring confidentiality and privacy of the participants.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 108 participants were eligible to participate in the study, of which 11 were excluded and 2 refused to participate 75 adolescents were included at the final sample (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e); 42.67% were male and 57.33% female, with a mean age of 12.70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.21. The majority were adolescents from the interior of Alagoas (53.3%), 82.7% of them declared themselves as brown (n\u0026thinsp;=\u0026thinsp;51), with a family income predominantly or less (50.6%) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eThe PDAY cardiovascular risk score was observed in the majority of the sample at low risk levels (62.6%); a low frequency of cardiovascular risk factors was also be observed, such as acceptable levels of blood pressure in 80.0% of the sample, normal total cholesterol in 66.6%, normal LDL-c in 85.3%, normal blood glucose in 96.0% and normal waist circumference in 81.3%; however, abnormal values were observed in the majority of participants in the HDL-c analysis (56.0%); 11 adolescents were not fasting on the day of the study (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristics of adolescent participants with Congenital Heart Disease\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;75)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;14 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (74,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15\u0026ndash;18 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (25,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMasculine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (42,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFeminine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (57,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSkin Color\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBrown, Black, Yellow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (82,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (17,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEducation of the person in charge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;10 anos of literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (53,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;10 anos of literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (46,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;1 minimum wage (\u003cspan\u003e$\u003c/span\u003e 262,00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (50,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;1 minimum wage (\u003cspan\u003e$\u003c/span\u003e 262,00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (49,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlace of Origin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCapital (IDHM\u0026thinsp;=\u0026thinsp;0,721)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (46,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther locations (IDHM\u0026thinsp;=\u0026thinsp;0,574)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (53,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePhysical activity (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsufficiently Active (\u0026lt;\u0026thinsp;2,87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68 (90,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActive (\u0026ge;\u0026thinsp;2,87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (9,33)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSedentary Behavior on Screens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal (\u0026lt;\u0026thinsp;120 min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (17,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcess (\u0026ge;\u0026thinsp;120 min)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (82,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal (\u0026le;\u0026thinsp;90\u0026ordm; percentil)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (80,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChanged (\u0026gt;\u0026thinsp;90\u0026ordm; percentil)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (20,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTotal Cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDesirable(\u0026lt;\u0026thinsp;170 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e50 (66,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBorderline(170\u0026ndash;199 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (22,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh(\u0026gt;\u0026thinsp;200 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (10,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHDL-c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow (\u0026lt;\u0026thinsp;40 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e42 (56,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDesirable(\u0026gt;\u0026thinsp;40 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e33 (44,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLDL-c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDesirable(\u0026lt;\u0026thinsp;100 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (85,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBorderline(100\u0026ndash;129 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (12,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh(\u0026gt;\u0026thinsp;130 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (2,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTriglycerides\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDesirable(\u0026lt;\u0026thinsp;90 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (64,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBorderline(90\u0026ndash;129 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (14,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh(\u0026ge;\u0026thinsp;130 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (21,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlood glucose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNormal (\u0026lt;\u0026thinsp;100 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e72 (96,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChanged(\u0026gt;\u0026thinsp;100 mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (4,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWaist Circumference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSuitable (in cm by sex and age)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (81,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInadequate (in cm by sex and age)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (18,6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePDAY (score)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow risk(\u0026le;\u0026thinsp;0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (62,7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntermediate risk(\u0026ge;\u0026thinsp;1 e\u0026thinsp;\u0026le;\u0026thinsp;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (28,0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh risk(\u0026ge;\u0026thinsp;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (9,3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003ePDAY: Pathobiological Determinants of Atherosclerosis in Youth; HDL: High Density Lipoprotein; LDL: Low Density Lipoprotein. Weighted Biochemical Values in Fasting and Non\u0026minus;Fasting.\u003c/p\u003e\n\u003cp\u003eThe most prevalent heart diseases in the sample were (Fig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e): Atrial Septal Defect (ASD) (16.0%), Ventricular Septal Defect (VSD) (13.3%). Regarding the characteristics of the clinical factors of CHD, 69.3% of the adolescents did not present cyanosis at the time of data collection. Regarding the complexity of the heart disease, 58.6% of the cases were classified as simple, 34.6% as moderately complex and 6.6% as complex. Among the adolescents, 53.3% had never undergone any cardiac surgery related to CHD, 32.0% had undergone only one, and only 14.6% had undergone more than one surgery to correct the heart disease throughout their lives.\u003c/p\u003e\n\u003cp\u003eIn Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, an association was observed between PDAY and sex (p\u0026thinsp;=\u0026thinsp;0.015), in which male adolescents presented higher intermediate to high CVR. Low HDL-c was associated with lower income (p\u0026thinsp;=\u0026thinsp;0.008). Furthermore, high LDL-c was associated with moderate to high complexity heart disease (p\u0026thinsp;=\u0026thinsp;0.022). No significant associations were observed between the other variables analyzed (Supplementary file 1).\u003c/p\u003e\n\u003cp\u003eFigure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e (Supplementary file 3) shows the odds ratio of cardiovascular risk outcomes and demographic, behavioral, and clinical exposures assessed in this study. After adjusting for significant confounders considering p\u0026thinsp;\u0026lt;\u0026thinsp;0.20, a significant association was found between moderate/high PDAY and sex (p\u0026thinsp;=\u0026thinsp;0.033), in which male sex is associated with higher CVR. High LDL-c was associated with heart disease complexity (p\u0026thinsp;=\u0026thinsp;0.046), indicating that greater complexity is associated with higher concentration of this lipid parameter. HDL-c showed an association with family income (p\u0026thinsp;=\u0026thinsp;0.021), in which lower income was associated with lower concentration of this lipid parameter. The associations between sex and PDAY were adjusted for the following variables: number of surgeries, physical activity, and sedentary behavior; between LDL and heart disease complexity were adjusted for age and location, while the associations between HDL and income were adjusted for age, sex, and location. The other variables did not show statistical significance.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab2\" border=\"1\" class=\"fr-table-selection-hover\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBivariate analysis of the association of the second sociodemographic, clinical and behavioral variables of cardiovascular risk factors of adolescents with congenital heart disease treated at the reference outpatient clinic in Alagoas.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRisk factor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003ePDAY\u003c/p\u003e\n \u003cp\u003eintermediate to high\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBlood Pressure\u003c/p\u003e\n \u003cp\u003ehigh\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eWaist Perimeter excessive\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eBlood glucose\u003c/p\u003e\n \u003cp\u003eelevated\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTotal Cholesterol\u003c/p\u003e\n \u003cp\u003eborderline to altered\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eHDL-c\u003c/p\u003e\n \u003cp\u003elow\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eLDL-c borderline to\u003c/p\u003e\n \u003cp\u003ealtered\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eTriglycerides\u003c/p\u003e\n \u003cp\u003eborderline to altered\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e%\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e / p-valor\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 a 14 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e78,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3602 (0,548)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e93,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,4539 (0,096)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0008 (1,000)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,745 (1,000)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,1410 (0,707)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,9938 (0,158)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,7979 (0,271*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e81,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,0358 (0,309)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMasculine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,9493 (0,015)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0545 (0,815)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,8227 (0,216)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4,1992 (0,073)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,7442 (0,187)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,0985 (0,147)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,2094 (0,647)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0545 (0,815)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026le;\u0026thinsp;1 Minimum wage em d\u0026oacute;lar\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0079 (0,929)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,1200 (0,729)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0025 (0,960)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3201 (1,000)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,7070 (0,191)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,0832 (0,008)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0776 (0,781)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,5519 (0,110)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation of the person in charge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;10 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,1995 (0,655)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3348 (0,563)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0638 (0,801)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,7344 (0,243)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,7143 (0,190)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e61,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,8177 (0,093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3215 (0,571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0372 (0,847)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther Locations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e46,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,8559 (0,355)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0000 (1,000)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0638 (0,801)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,5714 (0,097)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,7143 (0,190)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,4697 (0,225)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,9481 (0,163)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e63,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,5718 (0,210)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComplexity of Heart Disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate/Complex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,7597 (0,097)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e40,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0137 (0,907)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,4425 (0,506)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e66,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,8271 (0,566)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,6873 (0,407)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0914 (0,762)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e72,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,2393 (0,022)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,1684 (0,682)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeart disease\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCyanotic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0923 (0,761)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,0033 (0,369)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,5113 (0,113)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0105 (1,000)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e24,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,7839 (0,376)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e33,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3192 (0,572)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e36,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,1968 (0,657)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e29,6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0213 (0,884)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of Surgeries\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMore than 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e60,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,5426 (0,060)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,5540 (0,758)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,8207 (0,617)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,7344 (0,403)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,4330 (0,805)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e42,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,6198 (0,734)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45,4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,1694 (0,338)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e51,8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,6629 (0,718)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePhysical Activity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInsufficient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e82,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,8362 (0,095)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e80,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,5210 (0,138)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e91,7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0169 (1,000)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,3217 (1,000)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e96,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,2605 (0,262)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88,1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,7459 (0,388)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0009 (0,976)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e88,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,1576 (0,691)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSedentary Behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExcess\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e92,9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3,2382 (0,114)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e93,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1,4888 (0,445)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,5860 (0,426)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,6552 (1,000)*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0465 (0,829)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e83,3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0296 (0,863)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e100,0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2,7029 (0,100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18,5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0,0414 (0,839)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cstrong\u003ePDAY: Pathobiological Determinants of Atherosclerosis in Youth; HDL: High Density Lipoprotein; LDL: Low Density Lipoprotein. *Fisher\u0026apos;s exact test was applied for variables with n\u0026lt;5.\u003c/strong\u003e\u003c/sub\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe main findings of this study were the intermediate to high PDAY cardiovascular risk score (37.3%) in adolescents with congenital heart disease, associated with the male gender. Furthermore, adolescents with more complex heart disease demonstrated high levels of LDL-c and those with lower incomes presented low levels of HDL-c. In addition, adolescents demonstrated insufficient levels of physical activity (90.7%) simultaneously with high levels of sedentary behavior (82.7%).\u003c/p\u003e\u003cp\u003eChildren and adolescents with CHD are predisposed to greater cardiovascular risk factors [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. In the current study, a low cardiovascular risk was identified among most adolescents, however, 37.3% demonstrated intermediate to high risk. However, this finding does not indicate the absence of worrying factors, especially considering the cardiovascular context in which the studied population finds itself, in addition to the cardiovascular risk inherent to congenital heart disease [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Adolescence is the phase in which habits and conditions are formed that have an impact throughout life, such as poor diet, physical inactivity, obesity, hypertension and dyslipidemia, which perpetuate until adulthood and predisposes to CVR increase [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. In this period, the presence of two or more risk factors considered influential in the increase in CVR in the following 10 years [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eA meta-analysis study conducted with children and adults with CHD observed an association between individuals living with CHD and cardiovascular risk, describing that individuals with CHD, adults or children, have a 3.12 times greater chance of developing CVD, compared to those without CHD[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Also, Zacharias et al. (2016) observed in their study that individuals with CHD have a significantly higher risk (OR\u0026thinsp;=\u0026thinsp;12.22) of developing a stroke, especially those with more complex CHD, compared to their healthy peers [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], which can be explained by the hemodynamic context of these individuals, such as cardiac flow, volume and blood pressure. In addition, children with CHD who underwent cardiac surgeries have a significantly higher mortality rate compared to their healthy peers who underwent non-cardiac surgeries (moderate: 3.9% and severe: 8.2%)[\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].However, although 37.3% presented a high to intermediate risk, a difference was observed between the sexes, in which males presented a higher CVR when compared to females. This difference can be explained by biological, behavioral, social and cultural factors. Hormonal factors can act as a protective factor against CVR in females, in addition to culturally higher aware of women about health care, and in males, predominant levels of HDL-c and high blood pressure represent an important cardiovascular risk factor [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe influence of sociodemographic factors should also be considered in the analysis of cardiovascular risk. As with family income, adolescents with lower incomes are 3.29 times more likely to have low HDL-C levels (OR\u0026thinsp;=\u0026thinsp;3.29; p\u0026thinsp;=\u0026thinsp;0.021). Frota et al. (2007) report the importance of family income for better treatment and prognosis of children and adolescents living with CHD, making the investment necessary for the continuity of treatment, travel for consultations and routine exams, as well as maintenance of healthy habits essential for child growth and development relevant[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn the study by Faria and collaborators (2016), regional differences were observed, where there was a higher prevalence of low levels of HDL-c cholesterol in the North and Northeast regions, characterized by low HDI rates, combined with the prevalence of low triglycerides, indicating the presence of obesity and inadequate lifestyles and characterizing a process of atherogenic dyslipidemia [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e\u003cp\u003ePacheco and collaborators (2022), in a study carried out in Florian\u0026oacute;polis, explain that lower differences in HDL-c values ​​found in children and adolescents with CHD \u0026ndash; associated with C-reactive protein in the same study \u0026ndash; can be explained due to exposure to inflammatory stimuli, such as therapeutic procedures and infections, exercise and diet restrictions[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. This association reinforces the relevance of the socioeconomic context and its influence on risk factors, considering limited access to: healthy food, opportunities for physical activity, adequate medical monitoring, and sometimes access to appropriate guidance. Maternal education, although not associated with CVR in this study, represents a risk factor with a broad global effect. Studies cite the caregivers literacy as a contributing factor to the development of coronary disease and, associated with family income, impacts the lives of individuals due to exposure to the factors mentioned above, impacting the patient's survival[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe complexity of the heart disease was the only clinical factor that demonstrated an association in the present study, where it was observed that adolescents with more severe heart diseases had high LDL levels (OR\u0026thinsp;=\u0026thinsp;4.38; 95% CI\u0026thinsp;=\u0026thinsp;1.02\u0026ndash;18.69; p\u0026thinsp;=\u0026thinsp;0.046). This finding indicates a possible relationship between the severity of the heart condition and metabolic changes, including physiological responses to heart disease that involve adaptations in lipid metabolismo [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, no studies were found associating the complexity of heart disease with LDL-c levels in adolescentes and further studies are needed to determine the exact cause of this association. Severe heart disease is associated with an increase in heart failure, which leads to decreased functional capacity, muscle strength, need for surgical interventions and limitations in physical activity resulting in possible metabolic changes. However, little is known about the impact on lipid metabolismo [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe Bogalusa Heart Study demonstrated that high levels of LDL-c in childhood are associated with the early development of atherosclerotic plaques, and that altered lipid profiles in childhood are perpetuated throughout life, increasing CVR[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eIn a study carried out with 52 children with CHD and a mean age of 10.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.8 years, elevated total and LDL cholesterol parameters were observed, characterized by dyslipidemia; however, there was no difference in this parameter between children with CHD and their healthy peers [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Therefore, studies are needed to deepen the influence of the complexity of heart disease on lipid metabolism and thus create strategies that optimize metabolism and minimize the effects of CC on increasing RCV.\u003c/p\u003e\u003cp\u003eIn this study, the majority of adolescents stood out as insufficiently active (90.7%), similar to another Brazilian study carried out with children and adolescents with congenital heart disease, which used the same instrument, which observed 95% of the sample as insufficiently active[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Additionally, excessive sedentary behavior was observed[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. The higher frequency of physical inactivity and excessive sedentary behavior has been observed in the population with CHD in other studies with adolescents [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. In the long term, these behaviors can contribute to the development of chronic non-communicable diseases, such as obesity, hypertension, high cholesterol, metabolic syndrome and cardiovascular diseases[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAn interesting finding of our study is that, although 37.3% of adolescents have intermediate/high cardiovascular risk, only 9.3% of them have an adequate level of physical activity. In a review study, 9 of the 18 studies evaluated did not find significant differences between the level of physical activity between children with and without CHD, and 4 found that children with CHD are more inactive than their healthy peers. In addition, excessive sedentary behavior was also observed [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eBrudy et al. (2020), in their cohort study, observed that 75.9% of children with CHD were active; however, despite not finding differences with their healthy peers, they observed that children who were overweight, obese or had severe heart disease practiced less activities than others [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. In another study carried out with adolescent students without CHD, also using the PDAY score to stratify cardiovascular risk, similarly to our study, no significant results were found regarding the relationship between sedentary behavior and physical activity with CVR[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e].This finding reinforces the complexity of the relationship between physical activity and cardiovascular risk, indicating that interventions need to be accompanied by strategies to improve other healthy habits in addition to physical activity.\u003c/p\u003e\u003cp\u003eExcessive sedentary behavior is present in this study in 82.7% of adolescents in the current sample, in common with adolescents without CHD[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. In a systematic review, in which studies also used screen time as an evaluation parameter, it was observed that \u0026gt;\u0026thinsp;2 hours of screen use in children and adolescents is associated with worse body composition, in addition, it is also associated with increased health risk [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAn epidemiological study with Mendelian randomization showed that excessive sedentary behavior was associated with a higher risk of type 2 diabetes mellitus, hypertension and dyslipidemia, with increased total cholesterol and LDL-c, and lower HDL-c cholesterol levels [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. Another recent study demonstrated that excessive CS [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] is associated with increased TG levels and reduced HDL cholesterol, also promoting insulin resistance and increased body fat deposition and lipid concentrations. Furthermore, it was observed that prolonged exposure to CS for 7 days, even with the maintenance of physical activity (PA) levels at any intensity, did not change lipid concentrations [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, excessive sedentary behavior is often associated with risk factors for cardiovascular disease, regardless of the level of physical activity, whether moderate or vigorous. Thus, reducing sedentary time becomes an essential strategy for improving lifestyle and promoting cardiovascular health [\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. Furthermore, overprotection by parents and caregivers is an important factor that contributes to physical inactivity, leading to excessive sedentary behavior, motor skill deficits and consequently exacerbating cardiovascular risk factors [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. This highlights the complexity and importance of recognizing the simultaneity of behaviors that can exacerbate cardiovascular risk, which suggests the need for greater attention in assisting adolescents living with CHD.\u003c/p\u003e\u003cp\u003eThis study has limitations due to its cross-sectional design, which prevents the establishment of causality between the factors analyzed and cardiovascular risk. Data on family history of cardiovascular diseases were also not collected. The PDAY score used is a validated score for adolescents aged 15 and over, although its stratification considers the same score for adolescents aged 10 to 19. However, the study also has relevant strengths, such as the investigation of a population from the northeast region of the country with a low HDI, the use of validated questionnaires, and the collection of data considering multiple factors simultaneously, including clinical, behavioral, sociodemographic and cardiovascular risk aspects.\u003c/p\u003e\u003cp\u003eIn conclusion, adolescents with CHD demonstrated high risk characteristics, in which only 9.3% of adolescents are active and present high rates of sedentary behavior (90.7%), factors that may contribute to increased cardiovascular risk in the long term. Although only 37.3% presented intermediate/high risk, boys were more vulnerable compared to girls.\u003c/p\u003e\u003cp\u003eFurthermore, clinical factors, such as the complexity of the heart disease, were associated with high LDL levels, and the analysis of sociodemographic factors revealed that income significantly influences cardiovascular risk, with a higher prevalence of risk among those with lower income. These results highlight the need for cohort studies to investigate the causality between the conditions studied and cardiovascular risk, in addition to individualized interventions, such as awareness-raising actions among families and professionals about the benefits of physical activity and reducing sedentary behavior. Multidisciplinary training, social and school inclusion, in addition to the implementation of public policies for cardiovascular rehabilitation, considering clinical, socioeconomic and cultural factors, and actions to mitigate the impacts of sociodemographic factors, aiming to improve the prognosis of adolescents with congenital heart disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003eConflict of interest:\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthical aspects\u003c/strong\u003e\u003cp\u003e This study followed the ethical principles of respect for people's autonomy, as outlined in Resolution No. 466 of December 12.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e\u003cp\u003eThis study was funded by the Postgraduate Program in Health Sciences (PPGCS), through PROAP, for biochemical analysis performed in an outsourced laboratory. In addition, a master's scholarship was granted by FAPEAL, under No. E:60030.000000126/2023.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eStudy concept and design: Marylia Santos Pereira and Luiz Rodrigo Augustemak de Lima. Data acquisition: Marylia Santos Pereira, Ana Carla Porciuncula Cavalcante, Adrielly Suely Santos Pereira. Data analysis and interpretation: Marylia Santos Pereira and Luiz Rodrigo Augustemak de Lima. Critical review of the manuscript: Marylia Santos Pereira, Ana Carla Porciuncula Cavalcante, Adrielly Suely Santos Pereira, Christefany R\u0026eacute;gia Braz Costa, Filipe Antonio de Barros Sousa, Isabela de Carlos Back , Luiz Rodrigo Augustemak de Lima.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe would like to express our gratitude to the Alagoas Research Support Foundation (FAPEAL) and the Postgraduate Program in Health Sciences (PPGCS) for granting the master's scholarship, to Casa do Cora\u0026ccedil;\u0026atilde;ozinho and to the Cordial Foundation, especially to the coordination, reception and nursing staff, for making this study possible and providing the technical and logistical support necessary for its execution, and above all for their hospitality and fundamental contribution to the completion of data collection. We would like to thank the research participants and their families, who, by volunteering their time and information, contributed in an indispensable way to the completion of this work.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCappellesso VR, de Aguiar AP (2017) Cardiopatias cong\u0026ecirc;nitas em crian\u0026ccedil;as e adolescentes:caracteriza\u0026ccedil;\u0026atilde;o cl\u0026iacute;nico-epidemiol\u0026oacute;gica em um hospital infantil de Manaus-AM. 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Rev Sa\u0026uacute;de P\u0026uacute;blica 50:10s\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePacheco MA, Cardoso SM, Honicky M, Moreno YMF, de Lima LRA, Marcos CS, de Back I C (2022) HDL-Cholesterol in Children and Adolescents with Congenital Heart Disease. Int J Cardiovasc Sci 35:784\u0026ndash;793\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePrecoma DB (2021) A Educa\u0026ccedil;\u0026atilde;o como Determinante Social Associado ao Risco Cardiovascular. Arq Bras Cardiol 117:13\u0026ndash;14\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003ePowell KL, Stephens SR, Stephens AS (2021) Cardiovascular risk factor mediation of the effects of education and Genetic Risk Score on cardiovascular disease: a prospective observational cohort study of the Framingham Heart Study. BMJ Open 11:e045210\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFuenmayor G, Redondo ACC, Shiraishi KS, Souza R, Elias PF, Jatene IB (2013) Preval\u0026ecirc;ncia de dislipidemia em popula\u0026ccedil;\u0026atilde;o infantil com cardiopatia cong\u0026ecirc;nita. Arq Bras Cardiol 101:273\u0026ndash;276\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTracy RE, Newman WP, Wattigney WA, Berenson GS (1995) Risk factors and atherosclerosis in youth autopsy findings of the Bogalusa Heart Study. Am J Med Sci 310(Suppl 1):S37\u0026ndash;41\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBerenson GS, Srinivasan SR, Bao W, Newman WP, Tracy RE, Wattigney WA (1998) Association between Multiple Cardiovascular Risk Factors and Atherosclerosis in Children and Young Adults. 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Exerc Sport Sci Rev 45:80\u0026ndash;86\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVertematti S (2023) A Atividade F\u0026iacute;sica e Qualidade de Vida de Crian\u0026ccedil;as com Cardiopatias Cong\u0026ecirc;nitas: Uma Quest\u0026atilde;o de Sa\u0026uacute;de P\u0026uacute;blica. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.scielo.br/j/abc/a/q3KqZNBwj9nhcSzqdTzWNSz/?lang=pt\u003c/span\u003e\u003cspan address=\"https://www.scielo.br/j/abc/a/q3KqZNBwj9nhcSzqdTzWNSz/?lang=pt\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 23 Oct 2023\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"pediatric-cardiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pedc","sideBox":"Learn more about [Pediatric Cardiology](http://link.springer.com/journal/246)","snPcode":"246","submissionUrl":"https://submission.nature.com/new-submission/246/3","title":"Pediatric Cardiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Adolescent, congenital heart disease, sociodemographic factors, behavioral factors, cardiovascular risk factors","lastPublishedDoi":"10.21203/rs.3.rs-7705645/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7705645/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAdolescents with congenital heart disease (CHD) have high cardiovascular risk (CVR), related to clinical, behavioral and socioeconomic factors. A sedentary lifestyle, physical inactivity and unfavorable socioeconomic conditions can aggravate this risk, while regular physical activity, a healthy diet and lipid profile control are protective factors.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eTo determine the relationship among clinical, behavioral, and socioeconomic factors and CVR in adolescents with CHD.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eCross-sectional study with 75 adolescents, aged 10 to 18 years old, attending a reference outpatient service in Alagoas, Brazil. The Physical Activity Questionnaire for Children, Questionnaire for Screen Time of Adolescents, lipid and glycemic profile and Pathobiological Determinants of Atherosclerosis in Youth score were used. Associations were tested by chi-square or Fisher's exact test for categorical variables and Student's t-test for continuous variables. Multivariate binary logistic regression was used by the backward non-conditional method, adjusted for significant confounding factors (p\u0026thinsp;\u0026lt;\u0026thinsp;0.20).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eA total of 75 adolescents were recruited, 62.6% showed low CVR, 82.7% exhibited excessive sedentary behavior and 90.7% were physically inactive, both associated with lipid alterations. Females had a lower odds ratio (OR) of 0.32 (95% CI\u0026thinsp;=\u0026thinsp;0.11; 0.91) for higher CVR, while high complexity of CHD had an OR of 4.38 (95% CI\u0026thinsp;=\u0026thinsp;1.02; 18.69) for high LDL-c levels. Adolescents with lower income had an OR of 3.29 (95% CI\u0026thinsp;=\u0026thinsp;1.20; 9.08) for low HDL-c levels.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eAdolescents with CHD have a high sedentary lifestyle, low levels of physical activity and clinical and socioeconomic factors that increase cardiovascular risk.\u003c/p\u003e","manuscriptTitle":"Cardiovascular Risk in Adolescents With Congenital Heart Disease Living in a Low-income Region: Cross-sectional Associations With Clinical, Behavioral and Sociodemographic Factors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-02 13:46:38","doi":"10.21203/rs.3.rs-7705645/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-26T16:24:55+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-26T01:38:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-20T04:41:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"55905851183009886761003125333160646976","date":"2025-11-05T01:55:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"201560479845789117688875664817561624127","date":"2025-10-31T17:42:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74562981356849963452795589926866784427","date":"2025-10-12T23:26:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-30T00:20:24+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-25T07:39:28+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-25T07:38:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"Pediatric Cardiology","date":"2025-09-24T16:10:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"pediatric-cardiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pedc","sideBox":"Learn more about [Pediatric Cardiology](http://link.springer.com/journal/246)","snPcode":"246","submissionUrl":"https://submission.nature.com/new-submission/246/3","title":"Pediatric Cardiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"bf7ca26a-1717-4279-a2df-90c93ddcbf70","owner":[],"postedDate":"December 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-03-16T16:09:52+00:00","versionOfRecord":{"articleIdentity":"rs-7705645","link":"https://doi.org/10.1007/s00246-026-04218-y","journal":{"identity":"pediatric-cardiology","isVorOnly":false,"title":"Pediatric Cardiology"},"publishedOn":"2026-03-12 15:58:24","publishedOnDateReadable":"March 12th, 2026"},"versionCreatedAt":"2025-12-02 13:46:38","video":"","vorDoi":"10.1007/s00246-026-04218-y","vorDoiUrl":"https://doi.org/10.1007/s00246-026-04218-y","workflowStages":[]},"version":"v1","identity":"rs-7705645","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7705645","identity":"rs-7705645","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}