Oral Contraceptives in Adolescents: A Retrospective population-based study on Blood Pressure and Metabolic Dysregulation

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Methods This a retrospective cohort with 14,299 adolescents aged 14 to 17 years. Crude and adjusted analyses were performed using Poisson regression to estimate the prevalence ratios. Data clustering analysis was performed using machine learning approaches supported by an unsupervised neural network of self-organizing maps. Results We found that 14.5% (n = 2,076) of the women adolescents use oral contraceptives. Moreover, an increased prevalence of high blood pressure (4.9%), dyslipidemia (31.6%), and insulin resistance (34.7%) was observed among adolescents who use oral contraceptives as compared to those who do not. Our analysis also showed that 2.3% of adolescents using oral contraceptives had both high blood pressure levels and dyslipidemia, whereas 3.2% had high blood pressure levels combined with insulin resistance. The algorithmic investigative approach demonstrated that total cholesterol, LDLc, HDLc, insulin, and HOMA-IR were the most predicted variables to assist classificatory association in the context of oral contraceptive use among women adolescents with high blood pressure. Conclusions These findings suggest that oral contraceptives were associated with an increased prevalence of high blood pressure, dyslipidemia, and insulin resistance among women adolescents. Although the indication of this therapy is adequate to avoid unintended pregnancies, their use must be based on rigorous individual evaluation and under constant control of the cardiometabolic risk factors. oral contraception adolescent cardiometabolic profile blood pressure self-organizing maps Figures Figure 1 INTRODUCTION Oral contraceptives are the predominant contraceptive method among adolescents and are also widely prescribed for menstrual regulation and acne treatment [ 1 , 2 ]. These agents, composed of synthetic hormones such as estrogen and progestin, prevent ovulation and thus, serve their primary purpose [ 3 ]. Beyond contraception, oral contraceptives influence various metabolic pathways, revealing a broader pharmacological impact [ 3 ]. Since their introduction, extensive research has evaluated the risks and benefits associated with oral contraceptive use [ 3 ]. Adverse effects have been documented, including immunological [ 4 ], metabolic [ 5 ], and vascular complications [ 6 , 7 ]. In adult women, oral contraceptives have been associated with modest blood pressure elevations and a 2.8-fold increased risk of developing arterial hypertension [ 7 , 8 ]. However, the prevalence and impact of oral contraceptive-related hypertension in adolescent women remain uncertain. There is conflicting evidence regarding the cardiovascular effects in this demographic, with some studies noting a significant association between oral contraceptives and elevated blood pressure [ 10 – 12 ], while others report no substantial correlation [ 13 ]. Given that young women initiating oral contraceptive use may continue it over many years, the long-term hormonal exposure raises concerns about potential clinical outcomes. Despite the significance, few studies have specifically investigated these effects in the adolescent population. This study aims to assess the prevalence of high blood pressure in adolescent women using oral contraceptives within a national cohort, examine the co-occurrence of dyslipidemia and insulin resistance, and explore the contribution of oral contraceptives to these cardiometabolic conditions. METHODS Setting and Sample : We conducted a retrospective cohort study using a national database, which examines cardiovascular risk factor profiles in adolescents. Details of the sampling design, rationale, sample characteristics, questionnaires, clinical evaluation, and biochemical profiles have been previously published [ 14 ]. To select the study cohort, we first identified females in the database (n = 21,262). Subsequently, we excluded women adolescents from an ethnic minority (e.g., indigenous, Asiatic), those aged below 14 years old, and those with missing information on race and clinical and biochemical variables (n = 14,299). A total of 2,076 women adolescents were users of oral contraceptives, while the remaining 11,223 were not. To perform the analyses, we used the following classification criteria: a) overweight/obesity (body mass index [BMI]-for-age between > Z-score + 1 and < Z-score + 3); b) high blood pressure (BP) levels (BP ≥ 130/80 mmHg); c) dyslipidemia (presence of at least one of the following alterations in the lipid profile: total cholesterol ≥ 200 mg/dl; triglycerides [TGs] ≥ 150 mg/dl; high density lipoprotein-cholesterol [HDLc] 100 mg/dl); d) insulin resistance (HOMA-IR values > 2.32); and e) physical activity (≥ 300 min/week of moderate-to-vigorous physical activity). All participants signed an informed consent form at the time of enrollment. The study was approved by the Research Ethics Committee of the head institution of the national database center (IESC/UFRJ - Process 45/2008) and the accomplishment of the current study was approved by the Research Ethics Committee of the Federal University of São Paulo (Approval Number: 3.007.121). Data Analysis and Neural Network of Self-Organizing Maps : Categorical variables are expressed as absolute number of individuals, prevalence, and 95% confidence intervals (CI). Chi-square tests were used to test the association between contraceptive use and the presence of cardiometabolic risk factors. Crude and adjusted analyses were performed using Poisson regression to estimate the prevalence ratios and 95% CIs. All statistical tests were two-tailed, and the significance level was set at P < 0.05. Statistical analyses were performed using the Stata software version 14 (StataCorp. 2015. Stata statistical software: Release 14. College Station, TX, StataCorp LP). Data clustering analysis was performed by machine learning approaches and supported by an unsupervised neural network of self-organizing maps (SOM) using R software [ 15 ]. This neural network map analysis allows the visual identification of potential relationships between clinical variables produced by the clustering process as well as the discovery of patterns and behaviors for each variable. RESULTS We identified 2,076 (14.5%) women adolescents among the study population who used oral contraceptives. Table 1 shows the characteristics of the study population. Women adolescents who used oral contraceptives were older (71.1%) and more likely to smoke cigarettes (6.6%) and drink alcohol (41%). We found no significant differences in the prevalence of overweight/obesity ( P = 0.728) and level of physical activity ( P = 0.964) between users and non-users of oral contraceptives (Table 1 ). Table 1 Characteristic of the study population and the prevalence of cardiovascular risk factors among female adolescents classified as non-users or users of oral contraceptive. Non-Users of Oral Contraceptive n = 12,223 Users of Oral Contraceptive n = 2,076 P-value Age n (%) 14–15 years 16–17 years 6465 (52.9) 5758 (47.1) 601 (28.9) 1475 (71.1) < 0.001 Race n (%) White Black/brown 4,415 (36.1) 7,808 (63.8) 968 (46.6) 1,108 (53.4) < 0.001 Smoking n (%) No Yes 11,815 (96.7) 408 (3.3) 1,939 (93.4) 137 (6.6) < 0.001 Alcohol consumption n (%) No Yes 9,417 (77) 2,806 (23) 1,224 (59) 852 (41) < 0.001 BMI status n (%) Normal Overweight/Obesity 9,363 (74.6) 3,100 (25.4) 1,535 (73.9) 541 (26.1) 0.728 Physically active n (%) No Yes 6,801 (55.6) 5,422 (44.4) 1,154 (55.6) 922 (44.4) 0.964 High blood pressure n (%) No Yes 11,857 (97.0) 366 (3.0) 1,972 (95.0) 101 (4.9) < 0.001 Dyslipidemia n (%) No Yes 10,597 (86.7) 1,626 (13.3) 1,420 (68.4) 656 (31.6) < 0.001 Insulin Resistance n (%) No Yes 9,082 (74.3) 3,141 (25.7) 1,356 (65.3) 720 (34.7) < 0.001 Values expressed as absolute number (prevalence). Categorical data were analyzed by the chi-square test in an unadjusted model. Women adolescents who used oral contraceptives had an increased prevalence of high BP levels, dyslipidemia, and insulin resistance (Table 1 ). We also observed a higher prevalence of the co-occurrence of these risk factors among oral contraceptive users. Our analysis showed that 2.3% [95% CI: 1.7–2.9; P < 0.001] of women adolescents using oral contraceptives had both high BP levels and dyslipidemia, whereas 3.2% [95% CI: 2.4–3.9; P < 0.001] had high BP levels combined with insulin resistance. The race-and age-adjusted prevalence ratio showed that the prevalence of high BP levels was elevated among women adolescents who used oral contraceptives, had dyslipidemia, insulin resistance, and were overweight or obese (Table 2 ), indicating that modifiable risk factors and the use of oral contraceptives are important components in the prevalence of high BP in women adolescents. Table 2 Crude and age-adjusted prevalence ratio of factors associated with the presence of high blood pressure. Crude prevalence ratio (95% CI) P-value Race-and age-adjusted prevalence ratio (95% CI) P-value Oral Contraceptive Use No Yes 1.0 a 1.52 (1.36–1.84) < 0.001 1.0 a 1.46 (1.38–1.79) < 0.001 Smoking No Yes 1.0 a 1.09 (0.63–1.55) 0.968 1.0 a 1.07 (0.59–1.47) 0.768 Alcohol Consumption No Yes 1.0 a 1.17 (0.72–1.25) 0.874 1.0 a 1.36 (0.89–1.88) 0.089 Overweight/Obesity No Yes 1.0 a 1.57 (1.32–1.86) < 0.001 1.0 a 1.62 (1.48–1.95) < 0.001 Physically Active No Yes 1.0 a 0.88 (0.83–1.15) 0.799 1.0 a 0.90 (0.86–1.14) 0.791 Dyslipidemia No Yes 1.0 a 1.23 (1.12–1.47) 0.028 1.0 a 1.24 (1.03–1.45) < 0.001 Insulin Resistance No Yes 1.0 a 1.22 (1.16–1.58) < 0.001 1.0 a 1.18 (1.14–1.37) < 0.001 Values expressed as prevalence ratio (95% CI). Data were analyzed by Poisson regression in a crude and race-age-adjusted model. a reference category. Finally, we carried out SOM analysis involving clustering algorithms to investigate the dataset comprised only of women adolescents with high BP levels. Principal component analysis by global reduction of data dimension showed that total cholesterol, LDLc, insulin and HOMA-IR contributed significantly to the clustering process (Fig. 1 A and 1 B). Moreover, we found that age, total cholesterol, HDLc, LDLc, insulin, and HOMA-IR were the most predicted variables to assist classificatory association in the context of oral contraceptive use among these women adolescents (Fig. 1 C). DISCUSSION Adolescence is a critical period between childhood and adulthood during which it is important to develop positive practices and shape behaviors. In developing countries, it is estimated that around 36 million girls aged 15–19 years are sexually active, approximately 20 million of whom do not use modern methods of contraception [ 16 ]. Understanding the clinical pharmacology of oral contraceptives is crucial to discerning their impact on blood pressure regulation in adolescents. In the current database-driven, cross-sectional study among women adolescents aged 14–17 years, we identified that 14.5% of this population used oral contraceptives. An increased prevalence of high BP levels among women adolescents who use oral contraceptives was found, and Poisson regression analysis adjusted for age showed that the use of oral contraceptives indeed increased the prevalence of high BP levels by 46%. Interestingly, the algorithmic investigative approach using SOM analysis demonstrated that lipid and glycemic variables were the most predicted to assist classificatory association in the context of oral contraceptive use among women adolescents with high BP levels. The use of oral contraceptives has been previously demonstrated to be associated with elevated blood pressure levels in other cohorts [ 10 – 12 ]. A small study conducted among 17-year-old girls found that the use of oral contraceptives was associated with an approximately 5 mmHg increase in SBP [ 10 ]. A report that evaluated 1,248 women adolescents from the Western Australian Pregnancy Study observed that 30% of adolescents using oral contraceptives had an increase of 3.3 and 1.7 mmHg in systolic and diastolic levels, respectively [ 11 ]. Recently, a large and representative sample of German adolescents also showed a significant association between hormonal contraceptive use and elevated arterial blood pressure [ 12 ]. There is also evidence illustrating the importance of the duration and dosage of oral contraceptives in promoting negative effects on blood pressure [ 7 , 17 ]. Some authors reported that oral contraceptive use for more than 24 months promoted a 1.9-fold higher risk of hypertension as compared to those with no history of oral contraceptive use [ 17 ]. A meta-analysis observed an increase of 13% in the risk of hypertension per 5 years of oral contraceptive use [ 7 ]. These authors also showed that the highest doses of oral contraceptives caused a 50% higher risk of hypertension as compared to the lowest doses [ 7 ]. Clinically, the dose-response relationship observed in the association between oral contraceptive use and hypertension underscores the importance of personalized medicine in the prescription of these drugs. Unfortunately, information regarding the duration of use or dosage of oral contraceptives was not available in this national database. The pressor mechanisms of oral contraceptives are not fully understood and are believed to be an effect of multiple underlying pathways. The pharmacodynamic actions of oral contraceptives, particularly the estrogen component, include modulation of the renin-angiotensin-aldosterone system (RAAS), oxidative stress, and endothelial dysfunction are all likely to play interrelated roles [ 18 – 20 ]. Estrogen is known to increase circulating levels of angiotensinogen, renin, angiotensin II, and aldosterone. This action promotes both chronic salt retention and expansion of blood volume, leading to elevated blood pressure [ 18 ]. In turn, angiotensin II also increases superoxide anion production via activation of NADPH oxidase, leading to oxidative stress and, consequently, reduced nitric oxide bioavailability [ 18 ]. This effect could also be implicated in pathological signaling, leading to high blood pressure levels secondary to oral contraceptive use. Future clinical pharmacology research should focus on identifying genetic markers that predict blood pressure response to oral contraceptives, enabling more tailored and safer contraceptive options for adolescents. High BP levels, dyslipidemia, and insulin resistance frequently occur as comorbidities and can increase risk of other cardiometabolic diseases. We observed a higher prevalence of these comorbidities among oral contraceptive users, suggesting that these adolescents have a less favorable profile of cardiovascular risk factors and are more likely to develop metabolic syndrome. Moreover, dyslipidemia resulted in an increased of high blood pressure levels risk of 24%, whereas insulin resistance increased the age-adjusted prevalence of high blood pressure by 18%. The biological mechanisms involved in these interactions remain unclear. The use of oral contraceptives was associated with an unfavorable lipid profile and impaired glucose metabolism. Several studies have reported that women who use oral contraceptives have elevated levels of total cholesterol, LDLc, very low-density lipoprotein (VLDL), and TGs [ 21 , 22 ], Oral contraceptives can partially promote these alterations by affecting the lipid metabolism in the liver. It has been suggested that progestogen components promote hepatic lipase activity, facilitating VLDL conversion into LDL, while estrogen-induced changes in TGs are due to the activity of a hepatic microsomal enzyme [ 23 ]. There is also evidence of an association between oral contraceptive use and cholesterol metabolism, with increased levels of both apolipoprotein A-II precursors and apolipoprotein C-III [ 20 ]. However, these molecular mechanisms are dependent on the duration of use and hormonal composition of the oral contraceptive used. With regard to the association between oral contraceptive use and abnormal glucose regulation, studies have demonstrated that oral contraceptive use is associated with glucose intolerance, hyperinsulinemia, and insulin resistance, even at low doses [ 5 , 24 , 25 ]. However, these mechanisms have not been clarified in detail. Insulin resistance appears to result primarily from the effect of estrogen on progestogen components [ 5 ]. Estrogen enhances progesterone receptor binding in the pancreas, leading to augmented insulin release [ 5 ]. In addition, progestogens may decrease the number of insulin receptors at peripheral sites or alter the mechanisms of the post-receptor signaling response [ 26 ]. Interestingly, TGs have a direct effect on pancreatic β-cells, leading to increased insulin secretion [ 27 , 28 ]. Thus, insulin resistance observed in oral contraceptive users may also be secondary to dyslipidemia. However, it is tempting to speculate that the activation of the RAAS by the estrogen component could result in organ-specific angiotensin II-mediated mechanisms, such as changes in skeletal muscle, adipose, and liver, leading to insulin resistance. Therefore, RAAS activation may be a common link between oral contraceptive use and the co-occurrence of high blood pressure and insulin resistance observed in adolescents. Further studies are needed to investigate whether this mechanism is involved in mediating cardiometabolic disorders associated with hormonal contraceptive use. A major strength of our study is the evaluation of a database containing a country-wide cohort with a significant number of adolescents using oral contraceptives. This facilitated the assessment of the prevalence of hypertension and its co-occurrence with other risk factors in a large population. On the other hand, the cross-sectional design and lack of information about formulation, dose, or duration of oral contraceptive use can be listed as the main limitations of the current study. Oral contraceptives are increasingly prescribed at younger ages to prevent unintended pregnancies at the initiation of sexual activity. From a clinical pharmacology perspective, this prescription necessitates a careful risk-benefit analysis, considering both the contraceptive efficacy and the potential for exacerbating cardiometabolic risk factors. The role of these drugs in the prevalence of hypertension and its co-occurrence with dyslipidemia and insulin resistance highlights the need to conduct prospective studies in adolescents and evaluate the possible future outcomes in adult life. DECLARATIONS Author contribution P.X.A. and M.C.F. were responsible for article conceptualization. P.X.A. and P.M. made the literature search and prepared the tables. D.C.A. and A.A.S. made the neural network of self-organizing maps. All authors wrote the main manuscript text. All authors were responsible for data curation, drafting, and approval of the manuscript. Funding This research is not funded by a specific project. Availability of data and materials Not applicable. ETHICAL DECLARATIONS Ethical approval Not applicable. Consent to participate Not applicable. Consent to publish Not applicable. Competing interests The authors declare that they have no competing interests. REFERENCES Borges AL, Fujimori E, Kuschnir MC, Chofakian CB, de Moraes AJ, Azevedo GD, et al (2016) ERICA: sexual initiation and contraception in Brazilian adolescents. Rev Saude Publica 50:15s. https://doi: 10.1590/S01518-8787.2016050006686. Todd N, Black A (2020). Contraception for Adolescents. J Clin Res Pediatr Endocrinol 12:28-40. https://doi: 10.4274/jcrpe.galenos.2019.2019.S0003. Brynhildsen J (2014). 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Cite Share Download PDF Status: Published Journal Publication published 30 Mar, 2024 Read the published version in European Journal of Clinical Pharmacology → Version 1 posted Editorial decision: Revision requested 25 Jan, 2024 Reviews received at journal 11 Dec, 2023 Reviewers agreed at journal 20 Nov, 2023 Reviewers invited by journal 17 Nov, 2023 Editor assigned by journal 15 Nov, 2023 Submission checks completed at journal 15 Nov, 2023 First submitted to journal 12 Nov, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3601869","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":249558914,"identity":"561a14e8-8fb7-4ed4-85d5-8fd943812e55","order_by":0,"name":"Priscila Xavier Araújo","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Priscila","middleName":"Xavier","lastName":"Araújo","suffix":""},{"id":249558916,"identity":"141cbdcb-6113-42e4-824f-a6c192ddc356","order_by":1,"name":"Priscila Moreira","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Priscila","middleName":"","lastName":"Moreira","suffix":""},{"id":249558920,"identity":"e1b1127a-7431-4a35-8dc0-b264165f4c3c","order_by":2,"name":"Danilo Candido Almeida","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Danilo","middleName":"Candido","lastName":"Almeida","suffix":""},{"id":249558926,"identity":"1c13736f-f6d9-4c66-992e-2045d69b7a2d","order_by":3,"name":"Alexandra Aparecida Souza","email":"","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alexandra","middleName":"Aparecida","lastName":"Souza","suffix":""},{"id":249558928,"identity":"525ce2a7-e7eb-4c8c-80f2-d4987fcf25af","order_by":4,"name":"Maria do Carmo Franco","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie3OsWrCUBTG8e8iJMsB10BFn6BwJKA4FF+lUkiXiENBHAUhLj6A0BdxvBJol9SuGaQkFG6XDro5OPRG6SASo5vI/Q+X7ww/uIDJdKVJoLpfK4DsoR5iWEjc3RBTTUieQfBPSqSfQnI//kjlBtwrv47S74dgWSF7rBIx+8oljeiZ5xNwa7p8c91uoIgoarKIXvKJ9CAJW0bsW3fdIKS241uOCB7zyafCfAvmWkZamlDtR50msYeQNOGMiIw4aBQQhbCiRT323PpkoQn5Te5Epz7mlda/A+Zq/JQmm37YJvtdJetZPtnHh6eFInCUdSkwmUym2+4PTTJRFnU4t6IAAAAASUVORK5CYII=","orcid":"","institution":"Federal University of São Paulo","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Maria","middleName":"do Carmo","lastName":"Franco","suffix":""}],"badges":[],"createdAt":"2023-11-12 22:14:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3601869/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3601869/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00228-024-03671-z","type":"published","date":"2024-03-30T15:01:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":46671780,"identity":"142c877b-6a97-483a-876f-9288074c24d5","added_by":"auto","created_at":"2023-11-17 18:26:26","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":128575,"visible":true,"origin":"","legend":"\u003cp\u003eSOM analysis involving clustering algorithms to investigate the dataset comprised only of women adolescents with hypertension \u003cstrong\u003e(A)\u003c/strong\u003e Vectorial contribution of each numerical variable in principal component analysis (PCA) with heat color density code; \u003cstrong\u003e(B)\u003c/strong\u003e clustering heatmap with clinical variables contribution in PCA divided by component dimension (dim1 and dim2); \u003cstrong\u003e(C) \u003c/strong\u003efeature vector visualization map presents a visual representation of data set mapped into a four-by-four hexagonally-oriented grid, the weight vectors are represented using colored triangles, where each color represents a variable. The size of the triangle is related to the magnitude of the value for the respective variable.\u003c/p\u003e","description":"","filename":"Figure1FinalVersion.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3601869/v1/fd82f0c32d2bfcc5e5a8c6b5.jpg"},{"id":53869897,"identity":"14af7309-3b11-466f-a80b-6da460014a83","added_by":"auto","created_at":"2024-04-01 15:12:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":351217,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3601869/v1/05ed8701-858e-4acf-893e-8bf42e115347.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Oral Contraceptives in Adolescents: A Retrospective population-based study on Blood Pressure and Metabolic Dysregulation","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eOral contraceptives are the predominant contraceptive method among adolescents and are also widely prescribed for menstrual regulation and acne treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These agents, composed of synthetic hormones such as estrogen and progestin, prevent ovulation and thus, serve their primary purpose [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Beyond contraception, oral contraceptives influence various metabolic pathways, revealing a broader pharmacological impact [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince their introduction, extensive research has evaluated the risks and benefits associated with oral contraceptive use [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Adverse effects have been documented, including immunological [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], metabolic [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and vascular complications [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In adult women, oral contraceptives have been associated with modest blood pressure elevations and a 2.8-fold increased risk of developing arterial hypertension [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, the prevalence and impact of oral contraceptive-related hypertension in adolescent women remain uncertain. There is conflicting evidence regarding the cardiovascular effects in this demographic, with some studies noting a significant association between oral contraceptives and elevated blood pressure [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], while others report no substantial correlation [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGiven that young women initiating oral contraceptive use may continue it over many years, the long-term hormonal exposure raises concerns about potential clinical outcomes. Despite the significance, few studies have specifically investigated these effects in the adolescent population. This study aims to assess the prevalence of high blood pressure in adolescent women using oral contraceptives within a national cohort, examine the co-occurrence of dyslipidemia and insulin resistance, and explore the contribution of oral contraceptives to these cardiometabolic conditions.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e \u003cb\u003eSetting and Sample\u003c/b\u003e: We conducted a retrospective cohort study using a national database, which examines cardiovascular risk factor profiles in adolescents. Details of the sampling design, rationale, sample characteristics, questionnaires, clinical evaluation, and biochemical profiles have been previously published [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. To select the study cohort, we first identified females in the database (n\u0026thinsp;=\u0026thinsp;21,262). Subsequently, we excluded women adolescents from an ethnic minority (e.g., indigenous, Asiatic), those aged below 14 years old, and those with missing information on race and clinical and biochemical variables (n\u0026thinsp;=\u0026thinsp;14,299). A total of 2,076 women adolescents were users of oral contraceptives, while the remaining 11,223 were not. To perform the analyses, we used the following classification criteria: a) overweight/obesity (body mass index [BMI]-for-age between \u0026gt;\u0026thinsp;Z-score\u0026thinsp;+\u0026thinsp;1 and \u0026lt;\u0026thinsp;Z-score\u0026thinsp;+\u0026thinsp;3); b) high blood pressure (BP) levels (BP\u0026thinsp;\u0026ge;\u0026thinsp;130/80 mmHg); c) dyslipidemia (presence of at least one of the following alterations in the lipid profile: total cholesterol\u0026thinsp;\u0026ge;\u0026thinsp;200 mg/dl; triglycerides [TGs]\u0026thinsp;\u0026ge;\u0026thinsp;150 mg/dl; high density lipoprotein-cholesterol [HDLc]\u0026thinsp;\u0026lt;\u0026thinsp;40 mg/dl; low density lipoprotein-cholesterol [LDLc]\u0026thinsp;\u0026gt;\u0026thinsp;100 mg/dl); d) insulin resistance (HOMA-IR values\u0026thinsp;\u0026gt;\u0026thinsp;2.32); and e) physical activity (\u0026ge;\u0026thinsp;300 min/week of moderate-to-vigorous physical activity).\u003c/p\u003e \u003cp\u003e All participants signed an informed consent form at the time of enrollment. The study was approved by the Research Ethics Committee of the head institution of the national database center (IESC/UFRJ - Process 45/2008) and the accomplishment of the current study was approved by the Research Ethics Committee of the Federal University of S\u0026atilde;o Paulo (Approval Number: 3.007.121).\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Analysis and Neural Network of Self-Organizing Maps\u003c/b\u003e: Categorical variables are expressed as absolute number of individuals, prevalence, and 95% confidence intervals (CI). Chi-square tests were used to test the association between contraceptive use and the presence of cardiometabolic risk factors. Crude and adjusted analyses were performed using Poisson regression to estimate the prevalence ratios and 95% CIs. All statistical tests were two-tailed, and the significance level was set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Statistical analyses were performed using the Stata software version 14 (StataCorp. 2015. Stata statistical software: Release 14. College Station, TX, StataCorp LP). Data clustering analysis was performed by machine learning approaches and supported by an unsupervised neural network of self-organizing maps (SOM) using R software [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This neural network map analysis allows the visual identification of potential relationships between clinical variables produced by the clustering process as well as the discovery of patterns and behaviors for each variable.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eWe identified 2,076 (14.5%) women adolescents among the study population who used oral contraceptives. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the characteristics of the study population. Women adolescents who used oral contraceptives were older (71.1%) and more likely to smoke cigarettes (6.6%) and drink alcohol (41%). We found no significant differences in the prevalence of overweight/obesity (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.728) and level of physical activity (\u003cem\u003eP\u0026thinsp;=\u003c/em\u003e\u0026thinsp;0.964) between users and non-users of oral contraceptives (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCharacteristic of the study population and the prevalence of cardiovascular risk factors among female adolescents classified as non-users or users of oral contraceptive.\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\u003eNon-Users of Oral Contraceptive\u003c/p\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;12,223\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eUsers of Oral Contraceptive\u003c/p\u003e\n\u003cp\u003en\u0026thinsp;=\u0026thinsp;2,076\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\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 n (%)\u003c/p\u003e\n\u003cp\u003e14\u0026ndash;15 years\u003c/p\u003e\n\u003cp\u003e16\u0026ndash;17 years\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6465 (52.9)\u003c/p\u003e\n\u003cp\u003e5758 (47.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e601 (28.9)\u003c/p\u003e\n\u003cp\u003e1475 (71.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eRace n (%)\u003c/p\u003e\n\u003cp\u003eWhite\u003c/p\u003e\n\u003cp\u003eBlack/brown\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e4,415 (36.1)\u003c/p\u003e\n\u003cp\u003e7,808 (63.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e968 (46.6)\u003c/p\u003e\n\u003cp\u003e1,108 (53.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmoking n (%)\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e11,815 (96.7)\u003c/p\u003e\n\u003cp\u003e408 (3.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1,939 (93.4)\u003c/p\u003e\n\u003cp\u003e137 (6.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlcohol consumption n (%)\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9,417 (77)\u003c/p\u003e\n\u003cp\u003e2,806 (23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1,224 (59)\u003c/p\u003e\n\u003cp\u003e852 (41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI status n (%)\u003c/p\u003e\n\u003cp\u003eNormal\u003c/p\u003e\n\u003cp\u003eOverweight/Obesity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9,363 (74.6)\u003c/p\u003e\n\u003cp\u003e3,100 (25.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1,535 (73.9)\u003c/p\u003e\n\u003cp\u003e541 (26.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.728\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePhysically active n (%)\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e6,801 (55.6)\u003c/p\u003e\n\u003cp\u003e5,422 (44.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1,154 (55.6)\u003c/p\u003e\n\u003cp\u003e922 (44.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.964\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eHigh blood pressure n (%)\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e11,857 (97.0)\u003c/p\u003e\n\u003cp\u003e366 (3.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1,972 (95.0)\u003c/p\u003e\n\u003cp\u003e101 (4.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDyslipidemia n (%)\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e10,597 (86.7)\u003c/p\u003e\n\u003cp\u003e1,626 (13.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1,420 (68.4)\u003c/p\u003e\n\u003cp\u003e656 (31.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin Resistance n (%)\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e9,082 (74.3)\u003c/p\u003e\n\u003cp\u003e3,141 (25.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1,356 (65.3)\u003c/p\u003e\n\u003cp\u003e720 (34.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"4\"\u003e\u003cem\u003eValues expressed as absolute number (prevalence). Categorical data were analyzed by the chi-square test in an unadjusted model.\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eWomen adolescents who used oral contraceptives had an increased prevalence of high BP levels, dyslipidemia, and insulin resistance (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). We also observed a higher prevalence of the co-occurrence of these risk factors among oral contraceptive users. Our analysis showed that 2.3% [95% CI: 1.7\u0026ndash;2.9; \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001] of women adolescents using oral contraceptives had both high BP levels and dyslipidemia, whereas 3.2% [95% CI: 2.4\u0026ndash;3.9; \u003cem\u003eP\u0026thinsp;\u0026lt;\u003c/em\u003e\u0026thinsp;0.001] had high BP levels combined with insulin resistance.\u003c/p\u003e\n\u003cp\u003eThe race-and age-adjusted prevalence ratio showed that the prevalence of high BP levels was elevated among women adolescents who used oral contraceptives, had dyslipidemia, insulin resistance, and were overweight or obese (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), indicating that modifiable risk factors and the use of oral contraceptives are important components in the prevalence of high BP in women adolescents.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eCrude and age-adjusted prevalence ratio of factors associated with the presence of high blood pressure.\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\u003eCrude prevalence ratio\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eRace-and age-adjusted prevalence ratio\u003c/p\u003e\n\u003cp\u003e(95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eP-value\u003c/em\u003e\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\u003eOral Contraceptive Use\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.52 (1.36\u0026ndash;1.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.46 (1.38\u0026ndash;1.79)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmoking\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.09 (0.63\u0026ndash;1.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.968\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.07 (0.59\u0026ndash;1.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.768\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eAlcohol Consumption\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.17 (0.72\u0026ndash;1.25)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.874\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.36 (0.89\u0026ndash;1.88)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.089\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOverweight/Obesity\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.57 (1.32\u0026ndash;1.86)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.62 (1.48\u0026ndash;1.95)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePhysically Active\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e0.88 (0.83\u0026ndash;1.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.799\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e0.90 (0.86\u0026ndash;1.14)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.791\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDyslipidemia\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.23 (1.12\u0026ndash;1.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.24 (1.03\u0026ndash;1.45)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eInsulin Resistance\u003c/p\u003e\n\u003cp\u003eNo\u003c/p\u003e\n\u003cp\u003eYes\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.22 (1.16\u0026ndash;1.58)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e1.0 \u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e1.18 (1.14\u0026ndash;1.37)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003ctfoot\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"5\"\u003e\u003cem\u003eValues expressed as prevalence ratio (95% CI). Data were analyzed by Poisson regression in a crude and race-age-adjusted model.\u003c/em\u003e \u003csup\u003e\u003cem\u003ea\u003c/em\u003e\u003c/sup\u003e \u003cem\u003ereference category.\u003c/em\u003e\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tfoot\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFinally, we carried out SOM analysis involving clustering algorithms to investigate the dataset comprised only of women adolescents with high BP levels. Principal component analysis by global reduction of data dimension showed that total cholesterol, LDLc, insulin and HOMA-IR contributed significantly to the clustering process (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eB). Moreover, we found that age, total cholesterol, HDLc, LDLc, insulin, and HOMA-IR were the most predicted variables to assist classificatory association in the context of oral contraceptive use among these women adolescents (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eAdolescence is a critical period between childhood and adulthood during which it is important to develop positive practices and shape behaviors. In developing countries, it is estimated that around 36\u0026nbsp;million girls aged 15\u0026ndash;19 years are sexually active, approximately 20\u0026nbsp;million of whom do not use modern methods of contraception [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Understanding the clinical pharmacology of oral contraceptives is crucial to discerning their impact on blood pressure regulation in adolescents. In the current database-driven, cross-sectional study among women adolescents aged 14\u0026ndash;17 years, we identified that 14.5% of this population used oral contraceptives. An increased prevalence of high BP levels among women adolescents who use oral contraceptives was found, and Poisson regression analysis adjusted for age showed that the use of oral contraceptives indeed increased the prevalence of high BP levels by 46%. Interestingly, the algorithmic investigative approach using SOM analysis demonstrated that lipid and glycemic variables were the most predicted to assist classificatory association in the context of oral contraceptive use among women adolescents with high BP levels.\u003c/p\u003e \u003cp\u003eThe use of oral contraceptives has been previously demonstrated to be associated with elevated blood pressure levels in other cohorts [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. A small study conducted among 17-year-old girls found that the use of oral contraceptives was associated with an approximately 5 mmHg increase in SBP [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. A report that evaluated 1,248 women adolescents from the Western Australian Pregnancy Study observed that 30% of adolescents using oral contraceptives had an increase of 3.3 and 1.7 mmHg in systolic and diastolic levels, respectively [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Recently, a large and representative sample of German adolescents also showed a significant association between hormonal contraceptive use and elevated arterial blood pressure [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. There is also evidence illustrating the importance of the duration and dosage of oral contraceptives in promoting negative effects on blood pressure [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Some authors reported that oral contraceptive use for more than 24 months promoted a 1.9-fold higher risk of hypertension as compared to those with no history of oral contraceptive use [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. A meta-analysis observed an increase of 13% in the risk of hypertension per 5 years of oral contraceptive use [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These authors also showed that the highest doses of oral contraceptives caused a 50% higher risk of hypertension as compared to the lowest doses [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Clinically, the dose-response relationship observed in the association between oral contraceptive use and hypertension underscores the importance of personalized medicine in the prescription of these drugs. Unfortunately, information regarding the duration of use or dosage of oral contraceptives was not available in this national database.\u003c/p\u003e \u003cp\u003eThe pressor mechanisms of oral contraceptives are not fully understood and are believed to be an effect of multiple underlying pathways. The pharmacodynamic actions of oral contraceptives, particularly the estrogen component, include modulation of the renin-angiotensin-aldosterone system (RAAS), oxidative stress, and endothelial dysfunction are all likely to play interrelated roles [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Estrogen is known to increase circulating levels of angiotensinogen, renin, angiotensin II, and aldosterone. This action promotes both chronic salt retention and expansion of blood volume, leading to elevated blood pressure [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In turn, angiotensin II also increases superoxide anion production via activation of NADPH oxidase, leading to oxidative stress and, consequently, reduced nitric oxide bioavailability [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. This effect could also be implicated in pathological signaling, leading to high blood pressure levels secondary to oral contraceptive use. Future clinical pharmacology research should focus on identifying genetic markers that predict blood pressure response to oral contraceptives, enabling more tailored and safer contraceptive options for adolescents.\u003c/p\u003e \u003cp\u003eHigh BP levels, dyslipidemia, and insulin resistance frequently occur as comorbidities and can increase risk of other cardiometabolic diseases. We observed a higher prevalence of these comorbidities among oral contraceptive users, suggesting that these adolescents have a less favorable profile of cardiovascular risk factors and are more likely to develop metabolic syndrome. Moreover, dyslipidemia resulted in an increased of high blood pressure levels risk of 24%, whereas insulin resistance increased the age-adjusted prevalence of high blood pressure by 18%.\u003c/p\u003e \u003cp\u003eThe biological mechanisms involved in these interactions remain unclear. The use of oral contraceptives was associated with an unfavorable lipid profile and impaired glucose metabolism. Several studies have reported that women who use oral contraceptives have elevated levels of total cholesterol, LDLc, very low-density lipoprotein (VLDL), and TGs [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], Oral contraceptives can partially promote these alterations by affecting the lipid metabolism in the liver. It has been suggested that progestogen components promote hepatic lipase activity, facilitating VLDL conversion into LDL, while estrogen-induced changes in TGs are due to the activity of a hepatic microsomal enzyme [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. There is also evidence of an association between oral contraceptive use and cholesterol metabolism, with increased levels of both apolipoprotein A-II precursors and apolipoprotein C-III [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, these molecular mechanisms are dependent on the duration of use and hormonal composition of the oral contraceptive used.\u003c/p\u003e \u003cp\u003eWith regard to the association between oral contraceptive use and abnormal glucose regulation, studies have demonstrated that oral contraceptive use is associated with glucose intolerance, hyperinsulinemia, and insulin resistance, even at low doses [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, these mechanisms have not been clarified in detail. Insulin resistance appears to result primarily from the effect of estrogen on progestogen components [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Estrogen enhances progesterone receptor binding in the pancreas, leading to augmented insulin release [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In addition, progestogens may decrease the number of insulin receptors at peripheral sites or alter the mechanisms of the post-receptor signaling response [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Interestingly, TGs have a direct effect on pancreatic β-cells, leading to increased insulin secretion [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Thus, insulin resistance observed in oral contraceptive users may also be secondary to dyslipidemia. However, it is tempting to speculate that the activation of the RAAS by the estrogen component could result in organ-specific angiotensin II-mediated mechanisms, such as changes in skeletal muscle, adipose, and liver, leading to insulin resistance. Therefore, RAAS activation may be a common link between oral contraceptive use and the co-occurrence of high blood pressure and insulin resistance observed in adolescents. Further studies are needed to investigate whether this mechanism is involved in mediating cardiometabolic disorders associated with hormonal contraceptive use.\u003c/p\u003e \u003cp\u003eA major strength of our study is the evaluation of a database containing a country-wide cohort with a significant number of adolescents using oral contraceptives. This facilitated the assessment of the prevalence of hypertension and its co-occurrence with other risk factors in a large population. On the other hand, the cross-sectional design and lack of information about formulation, dose, or duration of oral contraceptive use can be listed as the main limitations of the current study.\u003c/p\u003e \u003cp\u003eOral contraceptives are increasingly prescribed at younger ages to prevent unintended pregnancies at the initiation of sexual activity. From a clinical pharmacology perspective, this prescription necessitates a careful risk-benefit analysis, considering both the contraceptive efficacy and the potential for exacerbating cardiometabolic risk factors. The role of these drugs in the prevalence of hypertension and its co-occurrence with dyslipidemia and insulin resistance highlights the need to conduct prospective studies in adolescents and evaluate the possible future outcomes in adult life.\u003c/p\u003e"},{"header":"DECLARATIONS","content":"\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eP.X.A. and M.C.F. were responsible for article conceptualization. P.X.A. and P.M. made the literature search and prepared the tables. D.C.A. and A.A.S. made the neural network of self-organizing maps. All authors wrote the main manuscript text. All authors were responsible for data curation, drafting, and approval of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research is not funded by a specific project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICAL DECLARATIONS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to publish\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e"},{"header":"REFERENCES","content":"\u003col\u003e\n\u003cli\u003eBorges AL, Fujimori E, Kuschnir MC, Chofakian CB, de Moraes AJ, Azevedo GD, et al (2016) ERICA: sexual initiation and contraception in Brazilian adolescents. Rev Saude Publica 50:15s. https://doi: 10.1590/S01518-8787.2016050006686.\u003c/li\u003e\n\u003cli\u003eTodd N, Black A (2020). Contraception for Adolescents. J Clin Res Pediatr Endocrinol 12:28-40. https://doi: 10.4274/jcrpe.galenos.2019.2019.S0003.\u003c/li\u003e\n\u003cli\u003eBrynhildsen J (2014). Combined hormonal contraceptives: prescribing patterns, compliance, and benefits versus risks. Therapeutic advances in drug safety 5: 201\u0026ndash;13. https://doi: 10.1177/2042098614548857.\u003c/li\u003e\n\u003cli\u003eWilliams WV (2017). Hormonal contraception and the development of autoimmunity: A review of the literature. The Linacre quarterly 84: 275\u0026ndash;95. https://doi: 10.1080/00243639.2017.1360065. \u003c/li\u003e\n\u003cli\u003eGodsland IF (2005). Oestrogens and insulin secretion. Diabetologia.; 48: 2213\u0026ndash;20. https://doi: 10.1007/s00125-005-1930-0.\u003c/li\u003e\n\u003cli\u003eLalude OO (2013). Risk of cardiovascular events with hormonal contraception: insights from the Danish cohort study. Current cardiology reports. 15: 374. https://doi: 10.1007/s11886-013-0374-2.\u003c/li\u003e\n\u003cli\u003eLiu H, Yao J, Wang W, Zhang D (2017). Association between duration of oral contraceptive use and risk of hypertension: A meta-analysis. J Clin Hypertens (Greenwich) 19:1032-41. https://doi: 10.1111/jch.13042. \u003c/li\u003e\n\u003cli\u003eSteenland MW, Zapata LB, Brahmi D, Marchbanks PA, Curtis KM (2013). Appropriate follow up to detect potential adverse events after initiation of select contraceptive methods: a systematic review. Contraception. 87: 611\u0026ndash;24. https://doi: 10.1016/j.contraception.2012.09.017.\u003c/li\u003e\n\u003cli\u003eGourdy P, Bachelot A, Catteau-Jonard S, et al (2012). Hormonal contraception in women at risk of vascular and metabolic disorders: guidelines of the French Society of Endocrinology. Ann Endocrinol (Paris) 73:469-87. https://doi: 10.1016/j.ando.2012.09.001.\u003c/li\u003e\n\u003cli\u003eNawrot TS, Den Hond E, Fagard RH, Hoppenbrouwers K, Staessen JA (2003). Blood pressure, serum total cholesterol and contraceptive pill use in 17-year-old girls. Eur J Cardiovasc Prev Rehabil. 10:438-42. https://doi: 10.1097/01.hjr.0000103463.31435.1e.\u003c/li\u003e\n\u003cli\u003eLe-Ha C, Beilin LJ, Burrows S, Huang RC, Oddy WH, Hands B, Mori TA (2013). Oral contraceptive use in girls and alcohol consumption in boys are associated with increased blood pressure in late adolescence. Eur J Prev Cardiol. 20:947-55. https://doi: 10.1177/2047487312452966. \u003c/li\u003e\n\u003cli\u003eLewandowski SK, Duttge G, Meyer T (2020). Quality of life and mental health in adolescent users of oral contraceptives. Results from the nationwide, representative German Health Interview and Examination Survey for Children and Adolescents (KiGGS). Qual Life Res. 29:2209-18. https://doi: 10.1007/s11136-020-02456-y. \u003c/li\u003e\n\u003cli\u003eKharbanda EO, Parker ED, Sinaiko AR, Daley MF, Margolis KL, Becker M, et al (2014). Initiation of oral contraceptives and changes in blood pressure and body mass index in healthy adolescents. J Pediatr. 165:1029-33. https://doi: 10.1016/j.jpeds.2014.07.048. \u003c/li\u003e\n\u003cli\u003eBloch KV, Szklo M, Kuschnir MC, Abreu Gde A, Barufaldi LA, Klein CH, et al (2015). The Study of Cardiovascular Risk in Adolescents--ERICA: rationale, design and sample characteristics of a national survey examining cardiovascular risk factor profile in Brazilian adolescents. BMC Public Health. 15:94. https://doi: 10.1186/s12889-015-1442-x.\u003c/li\u003e\n\u003cli\u003eSouza AA, Almeida DC, Barcelos TS, Bortoletto RC, Munoz R, Waldman H, et al (2021). Simple hemogram to support the decision-making of COVID-19 diagnosis using clusters analysis with self-organizing maps neural network. Soft comput. 17:1-12. https://doi: 10.1007/s00500-021-05810-5.\u003c/li\u003e\n\u003cli\u003eDarroch JE, Woog V, Bankole A, Ashford L. Adding it Up: Costs and Benefits of Meeting the Contraceptive Needs of Adolescents, New York: Guttmacher Institute, 2016. Guttmacher Institute, 2016. https://www.guttmacher.org/report/adding-it-meeting-contraceptive-needs-of-adolescents\u003c/li\u003e\n\u003cli\u003ePark H, Kim K (2013). Associations between oral contraceptive use and risks of hypertension and prehypertension in a cross-sectional study of Korean women. BMC Womens Health. 13:39. https://doi: 10.1186/1472-6874-13-39.\u003c/li\u003e\n\u003cli\u003eGoldhaber SZ, Hennekens CH, Spark RF, Evans DA, Rosner B, Taylor JO, et al (1984). Plasma renin substrate, renin activity, and aldosterone levels in a sample of oral contraceptive users from a community survey. Am Heart J. 107:119-22. https://doi: 10.1016/0002-8703(84)90144-3. \u003c/li\u003e\n\u003cli\u003eChen JT, Kotani K (2012). Oral contraceptive therapy increases oxidative stress in pre-menopausal women. Int J Prev Med. 3:893-6. https://doi: 10.4103/2008-7802.104862.\u003c/li\u003e\n\u003cli\u003eJosse AR, Garcia-Bailo B, Fischer K, El-Sohemy A (2012). Novel effects of hormonal contraceptive use on the plasma proteome. PLoS One. 7: e45162. https://doi: 10.1371/journal.pone.0045162.\u003c/li\u003e\n\u003cli\u003eNaz F, Jyoti S, Akhtar N, Afzal M, Siddique YH (2012). Lipid profile of women using oral contraceptive pills. Pak J Biol Sci. 15:947-50. https://doi: 10.3923/pjbs.2012.947.950.\u003c/li\u003e\n\u003cli\u003eMomeni Z, Dehghani A, Fallahzadeh H, Koohgardi M, Dafei M, Hekmatimoghaddam SH, et al (2020). The impacts of pill contraceptive low-dose on plasma levels of nitric oxide, homocysteine, and lipid profiles in the exposed vs. non exposed women: as the risk factor for cardiovascular diseases. Contracept Reprod Med. 5:7. https://doi: 10.1186/s40834-020-00110-z. \u003c/li\u003e\n\u003cli\u003ePalmisano BT, Zhu L, Stafford JM (2017). Role of Estrogens in the Regulation of Liver Lipid Metabolism. Adv Exp Med Biol 1043:227-56. https://doi: 10.1007/978-3-319-70178-3_12.\u003c/li\u003e\n\u003cli\u003eFrempong BA, Ricks M, Sen S, Sumner AE (2008). Effect of low-dose oral contraceptives on metabolic risk factors in African-American women. J Clin Endocrinol Metab 93(6):2097-103. https://doi: 10.1210/jc.2007-2599.\u003c/li\u003e\n\u003cli\u003eDeleskog A, Hilding A, \u0026Ouml;stenson CG (2011). Oral contraceptive use and abnormal glucose regulation in Swedish middle aged women. Diabetes Res Clin Pract 92:288-92. https://doi: 10.1016/j.diabres.2011.02.014.\u003c/li\u003e\n\u003cli\u003eCort\u0026eacute;s ME, Alfaro AA (2014). The effects of hormonal contraceptives on glycemic regulation. Linacre Q. 81:209-18. https://doi: 10.1179/2050854914Y.0000000023.\u003c/li\u003e\n\u003cli\u003eGinsberg HN, Zhang YL, Hernandez-Ono A (2005). Regulation of plasma triglycerides in insulin resistance and diabetes. Arch Med Res 36:232-40. https://doi: 10.1016/j.arcmed.2005.01.005.\u003c/li\u003e\n\u003cli\u003eTric\u0026ograve; D, Natali A, Mari A, Ferrannini E, Santoro N, Caprio S (2018). Triglyceride-rich very low-density lipoproteins (VLDL) are independently associated with insulin secretion in a multiethnic cohort of adolescents. Diabetes Obes Metab 20:2905-10. https://doi: 10.1111/dom.13467.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcl","sideBox":"Learn more about [European Journal of Clinical Pharmacology](http://link.springer.com/journal/228)","snPcode":"228","submissionUrl":"https://submission.nature.com/new-submission/228/3","title":"European Journal of Clinical Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"oral contraception, adolescent, cardiometabolic profile, blood pressure, self-organizing maps","lastPublishedDoi":"10.21203/rs.3.rs-3601869/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3601869/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aimed to explore the relationship between oral contraceptive use and blood pressure values and in a national cohort of women adolescents and to investigate the level of coexistence of the high blood pressure levels, dyslipidemia, and insulin resistance.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis a retrospective cohort with 14,299 adolescents aged 14 to 17 years. Crude and adjusted analyses were performed using Poisson regression to estimate the prevalence ratios. Data clustering analysis was performed using machine learning approaches supported by an unsupervised neural network of self-organizing maps.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe found that 14.5% (n\u0026thinsp;=\u0026thinsp;2,076) of the women adolescents use oral contraceptives. Moreover, an increased prevalence of high blood pressure (4.9%), dyslipidemia (31.6%), and insulin resistance (34.7%) was observed among adolescents who use oral contraceptives as compared to those who do not. Our analysis also showed that 2.3% of adolescents using oral contraceptives had both high blood pressure levels and dyslipidemia, whereas 3.2% had high blood pressure levels combined with insulin resistance. The algorithmic investigative approach demonstrated that total cholesterol, LDLc, HDLc, insulin, and HOMA-IR were the most predicted variables to assist classificatory association in the context of oral contraceptive use among women adolescents with high blood pressure.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese findings suggest that oral contraceptives were associated with an increased prevalence of high blood pressure, dyslipidemia, and insulin resistance among women adolescents. Although the indication of this therapy is adequate to avoid unintended pregnancies, their use must be based on rigorous individual evaluation and under constant control of the cardiometabolic risk factors.\u003c/p\u003e","manuscriptTitle":"Oral Contraceptives in Adolescents: A Retrospective population-based study on Blood Pressure and Metabolic Dysregulation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-11-17 18:26:21","doi":"10.21203/rs.3.rs-3601869/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-01-25T10:43:33+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-12-11T14:37:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0d8f4fd6-6ac8-4d14-8bd5-d67491477b95","date":"2023-11-20T18:45:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-11-17T07:01:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-11-15T08:39:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-11-15T08:39:10+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Journal of Clinical Pharmacology","date":"2023-11-12T22:01:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-journal-of-clinical-pharmacology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ejcl","sideBox":"Learn more about [European Journal of Clinical Pharmacology](http://link.springer.com/journal/228)","snPcode":"228","submissionUrl":"https://submission.nature.com/new-submission/228/3","title":"European Journal of Clinical Pharmacology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"94e3c1ac-841d-4bca-9ef5-661c13c67fb3","owner":[],"postedDate":"November 17th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-04-01T15:09:07+00:00","versionOfRecord":{"articleIdentity":"rs-3601869","link":"https://doi.org/10.1007/s00228-024-03671-z","journal":{"identity":"european-journal-of-clinical-pharmacology","isVorOnly":false,"title":"European Journal of Clinical Pharmacology"},"publishedOn":"2024-03-30 15:01:38","publishedOnDateReadable":"March 30th, 2024"},"versionCreatedAt":"2023-11-17 18:26:21","video":"","vorDoi":"10.1007/s00228-024-03671-z","vorDoiUrl":"https://doi.org/10.1007/s00228-024-03671-z","workflowStages":[]},"version":"v1","identity":"rs-3601869","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3601869","identity":"rs-3601869","version":["v1"]},"buildId":"wLkW0s4AflPzk-lpfg-fK","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}