Prevalence and Associated Risk Factors of Elevated Blood Pressure Among Adolescents in Selected Universities in Ogun State, Nigeria: A Cross-Sectional Study

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In Nigeria, evidence on the prevalence and determinants of elevated blood pressure among adolescents, particularly those enrolled in tertiary institutions, remains limited. Understanding the magnitude of the problem and its associated factors is essential for the development of targeted preventive strategies. This study investigated the prevalence and associated risk factors for elevated blood pressure among adolescents at selected universities in Ogun State, Nigeria. Methods This cross-sectional study surveyed 306 adolescents aged 16–19 years enrolled at universities in Ogun State, Nigeria. Data, including anthropometric and blood pressure measurements, were collected using a structured, validated questionnaire. Data were analysed via descriptive and inferential analyses (chi-square tests, binomial tests, and logistic regression) to examine associations and predictors of elevated blood pressure. Statistical significance was set at p < 0.05. Results The prevalence of elevated blood pressure was 17.3% (CI = 13.1–21.5). Body mass index (χ² = 15.47, p < 0.001) and family history of hypertension (χ² = 9.56, p < 0.008) were significantly associated with elevated blood pressure and remained significant predictors. Lifestyle and psychosocial factors were not significantly associated with elevated blood pressure. Conclusion Elevated blood pressure among adolescents in the selected universities was high and was influenced by a combination of sociodemographic, biological, and lifestyle factors. Preventive interventions, including routine screening within tertiary institutions, are essential to mitigate the long-term cardiovascular risks associated with elevated blood pressure. Epidemiology Adolescents Biological factors Elevated blood pressure Lifestyle factors Prevalence Sociodemographic factors BACKGROUND Hypertension has historically been viewed as a condition that primarily affects middle-aged and older adults. However, an expanding body of evidence over the past two decades suggests that elevated blood pressure is increasingly diagnosed during adolescence (10–19 years) [ 1 ]. This shift in disease patterns has important public health implications because adolescence is a sensitive developmental phase during which lifestyle behaviours, including dietary habits, physical activity, and substance use, are formed and frequently persist into later life, contributing to future cardiovascular risk profiles [ 2 , 3 ]. In sub-Saharan Africa, adolescent hypertension is an emergent concern. Findings across the region indicate substantial heterogeneity in prevalence estimates of hypertension and elevated blood pressure (EBP), ranging from less than 1% to more than 30%, with pooled prevalence figures of approximately 5–6%, but these values have risen in recent years [ 4 ]. Within Nigeria, the prevalence of hypertension and elevated blood pressure ranges between 0.1% and 26.7% [ 5 , 6 , 7 , 8 ]. These studies repeatedly implicate overweight and obesity, increased waist circumference, and sedentary behaviour as principal correlates of increased blood pressure in adolescents. Other risk factors for high blood pressure in adolescents include age, sex, obesity, physical inactivity, family history of hypertension in first-degree relatives, socioeconomic status, cigarette smoking, and alcohol intake [ 6 , 9 ]. In addition, studies have also reported either a greater prevalence in mid-adolescence or an increasing risk with age [ 6 , 10 ]. However, comparability across studies is limited by differing blood pressure thresholds, measurement protocols, and sampling frames (school-only vs community), highlighting the need for localized surveys. The consequences of hypertension/increased blood pressure in adolescents are numerous and severe. The prevalence and severity of atherosclerosis are linked to childhood hypertension, a significant modifiable risk factor for cardiovascular disease. Furthermore, hypertension persists from infancy into adulthood and is linked to harmful cardiac alterations and vascular damage, which are linked to early cardiovascular disease in adulthood [ 11 ]. Therefore, the primary prevention of cardiovascular disease, especially for at-risk individuals such as those with obesity, diabetes, or chronic renal disease, among others, depends on early detection and efficient treatment of hypertension in children and adolescents [ 6 , 11 ]. Moreover, early detection can promptly hinder advancements in the treatment of hypertension and its complications [ 6 ], thereby protecting and promoting overall well-being. This calls for continuous routine screening and the identification of those at risk of grave consequences. Studies in Nigeria have focused primarily on adolescents in lower educational institutions, even though studies have noted an increasing prevalence with the age/stage or stage of adolescence. Thus, this study sought to determine the prevalence and associated risk factors for elevated blood pressure among adolescents enrolled in universities in Ogun State, Nigeria, underpinned by Blum’s model of health determinants [ 12 ], which illustrates how the environment, lifestyle, heredity, and medical care interact to influence health outcomes. METHODS Aim, Design, and Setting This cross-sectional study was conducted to determine the prevalence of elevated BP and its associated risk factors in a population of 62,176 university students between January and March 2026. Universities in Ogun State are both public and private and are hosts to students from all over the country with various cultural, ethnic, and socioeconomic statuses. The study was conducted at six universities selected across the three Senatorial districts of the state, which ensured geographic and institutional representation. Participants were eligible if they consented or obtained consent from parents where applicable. Those with preexisting chronic illness or medical conditions that could influence anthropometric and BP measurements and who declined anthropometric measurements were excluded. Sample and sampling procedure A sample of 306 participants was derived via the single population proportions formula described by Cochran. A multistage sampling procedure was employed to select the study participants. First, universities were selected from each of the three Senatorial districts in Ogun State. Two universities were selected per senatorial district, one public and one private, via simple random sampling. In one district with only one public university, purposive sampling was used to select the only existing university, and simple random sampling was then used to select the private university. In districts where no public university existed, two private universities were selected via simple random sampling. The number of students to be sampled from each university was derived by proportionate allocation via the following formula: s n = student population per school/total population in all schools × sample size. In the third stage, faculties were selected, beginning with stratification into health-related and non-health-related faculties. Two faculties were then selected from each category via simple random sampling to ensure diversity in academic orientation. The number of students to be sampled from each faculty was determined proportionally via the following formula: f n = number of students in the faculty × total sample allocated to the university/ total number of students in the selected faculties. In the fourth stage, the two departments with the largest student populations were selected from the faculties. The number of respondents selected from each department was determined via proportional allocation, guided by the following formula: d n = Department Population × Faculty Sample/Total Population of selected departments. In the fifth stage, eligible students aged 16–19 years were selected from each department via systematic random sampling. The sampling interval was determined by dividing the number of eligible students by the allocated departmental sample size. A random starting point was chosen, and every hth eligible student was selected until the required sample size was achieved. The sampling interval (h) was determined separately for each department via the following formula: h n = Number of eligible students in the department/Departmental sample size. The selected students were approached in classrooms during scheduled lectures, with permission obtained from course coordinators and lecturers, and recruitment took place at the end of lectures to minimize academic disruption. Written informed consent was obtained from each eligible respondent before data collection commenced. Data collection and measurements Data were collected via a structured pretested questionnaire adapted from the literature related to all variables of interest [ 13 , 14 , 15 , 16 , 17 , 18 , 19 ] Reviews from three experts in public health promotion confirmed the content validation by assessing the relevance, clarity, and cultural appropriateness of the instrument. Minor modifications were subsequently made to ensure the questionnaire’s adequacy. The questionnaire was developed into five sections, which collected data on sociodemographic characteristics and potential risk factors. For the anthropometric measurements, the heights, recorded to the nearest 0.1 cm, and the weights, recorded to the nearest 0.1 kg, were measured via a stadiometer and a calibrated digital weighing scale, respectively. The body mass index (BMI) was subsequently calculated and recorded in kg/m². Blood pressure readings were taken via a calibrated automated digital sphygmomanometer. The participants were allowed to rest for at least 5 minutes before the measurements were taken. All processes followed standard protocols. Three blood pressure readings were taken at two-minute intervals, and the average of the second and third readings was used for analysis. Elevated blood pressure was defined according to established adolescent guidelines [ 20 ]. All protocols received ethical approval. Permission was also obtained from the university's administration. Confidentiality and anonymity were maintained throughout the study. Data analysis The data collected were carefully checked for completeness and consistency before analysis. The completed questionnaires were coded and entered into IBM SPSS version 27. Data cleaning procedures, including range checks, identification of missing values, and correction of entry errors, were performed to ensure data accuracy. Descriptive statistics were used to summarize the characteristics of the study participants and key study variables. Descriptive statistics (frequencies, percentages, means, and standard deviations) were used to describe the data. Inferential statistics (chi-square test and binary logistic regression) were used to test the hypotheses. In the binary logistic regression analysis to identify significant independent predictors of elevated blood pressure among adolescents, variables that were statistically significant at the bivariate level were entered into the regression model. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported to determine the strength and direction of associations between predictors and elevated blood pressure. Significance was set at p < 0.05. RESULTS Demographic characteristics of the adolescents The majority of the respondents were aged 18–19 years, and female participants constituted the larger proportion of the study population. Most reported receiving over ₦40,000 as a monthly allowance. In addition, the majority indicated that their parents had a tertiary education (Table 1 ). Table 1 Sociodemographic characteristics Demographic characteristics Number of participants = 306 Frequency (n) Percentage (%) Age 16–17 72 23.5 18–19 234 76.5 Sex Male 111 36.3 Female 195 63.7 Level of Study 100 78 25.5 200 124 40.5 300 400 50 54 16.4 17.6 Average Monthly Allowance ₦40,000 84 106 27.5 34.6 Highest Parental Education Primary 10 3.3 Secondary 74 24.2 Tertiary 222 72.5 Type of accommodation On-campus 173 56.5 Off-campus 132 43.5 Blood pressure distribution Table 2 shows that elevated blood pressure was prevalent in 17% of the respondents, whereas hypertension was present in 32.9% of the respondents. Table 2 Distribution of Blood Pressure among Respondents Number of participants = 306 Frequency (n) % 95% CI Blood Pressure Category Normal BP 154 50.3 44.7–55.9 Elevated BP 53 17.3 13.1–21.5 Stage 1 Hypertension 71 23.2 18.4–28.0 Stage 2 Hypertension 28 9.2 6.0 -12.4 Risk factor characteristics Tables 3, 4, and 5 (Additional file 1) present the biological, lifestyle, and psychosocial characteristics of the respondents. The largest proportion of participants had a normal BMI, whereas smaller proportions were underweight, overweight, or obese. The mean height, weight, and BMI of the respondents were 1.69 ± 0.10 m, 65.9 ± 19.6 kg, and 22.8 ± 5.7 kg/m², respectively. (Table 3). Most had poor dietary habits (69.5%) or high salt intake (63.4%). Alcohol was consumed by 5.3% of the participants, tobacco by 1.6%, and drugs by 2.6%. The majority were physically inactive (66.3%) (Table 4). High stress was reported by 41.8% of the participants (Table 5). Most had high family support (96.1%). Most (76.5%) experienced short sleep durations (Table 5). Risk factors associated with elevated blood pressure Table 6 indicates that only BMI (χ² = 15.47, p < 0.001) and family history (χ² = 9.56, p < 0.008) were significant risk factors for EBP among these adolescents. Furthermore, logistic regression analysis revealed that these factors were also significant independent predictors of EBP (Table 7 ). Table 6 Association between risk factors and elevated blood pressure Variable Sub variable Elevated BP χ² P value Normal BP Elevated BP Age 16–17 35 37 0.111 0.739 18–19 119 115 Sex Male 49 62 2.663 0.103 Female 105 90 BMI Underweight 43 27 15.470 0.001* Normal 75 71 Overweight 30 33 Obese 4 21 Alcohol Consumption Non-drinker 12 23 0.050 0.824 Alcohol User 6 10 Tobacco usage Non-tobacco smoker 152 2 149 3 0.217 0.641 Tobacco User 4 7 Salt Intake High Salt Intake 98 96 0.008 0.931 Low salt intake 56 56 Sleep Duration Adequate Sleep Duration 38 34 0.226 0.634 Short Sleep Duration 116 118 Stress Level Low Stress 90 88 0.009 0.923 High Stress 64 64 Family History Yes 23 45 9.563 < 0.008* No 131 107 * indicates that the p value is statistically significant (< 0.05) Table 7 Predictors of elevated blood pressure Variable Category B SE Wald p value AOR 95% CI BMI Category Normal (Ref) Underweight Overweight Obese -1.857 -1.478 -1.400 0.615 0.584 0.613 9.119 6.408 5.214 0.003* 0.011* 0.022* 1.00 0.156 0.228 0.246 0.047–0.521 0.073–0.716 0.074–0.820 Physical Activity Active (Ref) Inactive 0.110 0.256 0.186 0.667 1.116 0.676–1.843 Dietary Habit Good (Ref) Poor -0.056 0.281 0.040 0.841 1.00 0.945 0.545–1.638 Family History of Hypertension No (Ref) Yes 0.837 0.423 3.912 0.048* 1.00 2.310 1.008–5.295 Sex Male (Ref) Female 0.269 0.259 1.082 0.298 1.00 1.309 0.788–2.172 Psychosocial Stress Low (Ref) High 0.032 0.247 0.016 0.898 1.00 1.032 0.636–1.674 Salt Intake Low (Ref) High 0.047 0.252 0.035 0.851 1.00 1.048 0.640–1.716 p < 0.05 was considered statistically significant (*). DISCUSSIONS This study examined the prevalence and determinants of elevated blood pressure (EBP) among adolescents at selected universities in Ogun State, Nigeria. These findings indicate that elevated blood pressure is prevalent and is influenced mainly by the biological factors of BMI and family history. These factors remained significant predictors of EBP after further analysis. The prevalence of elevated blood pressure among the adolescents in this study was greater than that reported elsewhere [ 6 ]. This difference may reflect regional variations in lifestyle, dietary practices, and physical activity. This finding aligns with emerging evidence that adolescent hypertension is rising globally, particularly in sub-Saharan Africa, where dietary transitions, increased consumption of processed foods, and sedentary lifestyles have been linked to increased blood pressure among youth [ 4 ]. National studies also report increasing levels of prehypertension and hypertension among university students, suggesting that cardiovascular risk factors manifest earlier in life [ 9 ]. The prevalence observed in this study underscores the growing vulnerability of adolescent populations to cardiovascular risk factors and highlights the urgent need for targeted preventive strategies. Several studies have shown that excess body weight is a strong predictor of elevated blood pressure among adolescents, as increased adiposity influences vascular resistance, sympathetic nervous system activity, and insulin sensitivity [ 6 ]. Gafane-Matemane et al. [ 4 ] reported that overweight and obese adolescents in sub-Saharan Africa are at increased risk of elevated blood pressure, whereas Li et al. [ 21 ] and Wang et al. [ 22 ] similarly identified body weight and family history as key determinants of adolescent hypertension. The findings of this study therefore reinforce the biological link between body composition and cardiovascular risk [ 4 , 21 , 22 ]. The association and predictive power of family history suggest the influence of genetic predispositions and shared environmental factors within families. Shokunbi et al. [ 9 ] reported a similar association in Ogun State, whereas Atoh et al. [ 6 ] reported an increased likelihood of elevated blood pressure among adolescents with a positive family history. Ruan et al. [ 23 ] further emphasized the importance of familial risk factors in adolescent hypertension across different populations. This finding highlights the need to incorporate family history into screening and preventive strategies, as individuals with genetic susceptibility may require closer monitoring even in the absence of other risk factors [ 6 , 9 , 23 ]. Neither lifestyle nor psychosocial factors were associated with EBP. However, this does not imply that lifestyle factors are unimportant; rather, their effects may not have been sufficiently pronounced to reach statistical significance in this sample. The uniform lifestyle environment among university students may also have reduced observable differences in exposure. Additionally, behaviours such as alcohol, tobacco use, and sleep may have been underreported owing to social desirability bias. Despite insignificant results in the present study, others have demonstrated associations [ 6 , 7 , 24 ]. Hence, the results need to be interpreted with caution, as lifestyle factors remain important contributors to long-term cardiovascular risk. Psychosocial stress was examined but was not significantly associated with elevated blood pressure. While stress can affect cardiovascular health through sympathetic nervous system activation and behavioral changes, the findings suggest that in this adolescent population, short-term or self-reported stress may not manifest as measurable differences in blood pressure [ 22 , 25 ]. Despite its strengths in contributing to the need for routine screening for elevated blood pressure in adolescents, this study has several limitations. The cross-sectional design limits cause‒and‒effect accountability between EBP and identified risk factors. The self-reported behavioural factors were liable to recall and social desirability biases. Although a multistage sampling technique with proportional allocation was employed, the study was conducted at selected universities within Ogun State, which may limit the generalisability of the findings to all adolescents in Nigeria, particularly those not enrolled in tertiary institutions. CONCLUSION Overall, the findings highlight that elevated blood pressure among adolescents is still prevalent and is influenced by biological factors. These results reinforce evidence from Nigeria and Sub-Saharan Africa indicating that adolescent hypertension is increasing and underscore the urgent need for early screening and health education interventions that account for modifiable and nonmodifiable risk factors. Abbreviations EBP-Elevated Blood Pressure CI-Confidence Interval BMI-Body Mass Index Declarations Ethics approval and consent to participate Approval for this study was obtained from the Babcock University Health Research Ethics Committee (BUHREC0112/26/1631). Consent for publication Consent was obtained from all participants. For those under 18 years of age, assent was obtained from parents. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding No external funding was received for this study. Authors' contributions SA conceptualised and designed the study, interpreted the data, and critically reviewed the manuscript for important intellectual content. IO designed the study, collected the data, analysed and interpreted the data, and critically assessed the manuscript. JO conceptualised, interpreted the data, critically analysed the manuscript for intellectual content, and approved the final manuscript. Acknowledgements Not applicable References World Health Organization. (2021). (b). Adolescent health and development. https://www.who.int/ Nagata JM, Weinstein S, Alsamman S, Lee CM, Dooley EE, Ganson KT et al. Association of physical activity and screen time with cardiovascular disease risk in the Adolescent Brain Cognitive Development Study. BMC Public Health. 2024;24(1):1346. doi:10.1186/s12889-024-18790-6 Lewandowska A, Rudzki G, Lewandowski T, Bartosiewicz A, Próchnicki M, Stryjkowska-Góra et al. Overweight and obesity among adolescents: health-conscious behaviours, acceptance, and the health behaviours of their parents. BMC Public Health. 2025;25(1):418. Published 2025 Feb 2. doi:10.1186/s12889-025-21591-0 Gafane-Matemane LF, Craig A, Kruger R, Alaofin OS, Ware LJ, Jones ESW et al. Hypertension in sub-Saharan Africa: the current profile, recent advances, gaps, and priorities. J Hum Hypertens. 2025;39(2):95-110. doi:10.1038/s41371-024-00913-6 Ejike CECC. Prevalence of Hypertension in Nigerian Children and Adolescents: A Systematic Review and Trend Analysis of Data from the Past Four Decades. J Trop Pediatr. 2017;63(3):229-241. doi:10.1093/tropej/fmw087 Atoh I, Ezeogu J, Okeke CV, Umeh SI, Ekure E, Omokhodion SI, Njokanma FO. High blood pressure pattern amongst adolescents in Lagos, South West Nigeria. 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Family history and obesity as predictors of adolescent hypertension in China: A cross-sectional study. BMC Public Health.2023;23(1):16331. Ruan X, Zhu A, Wang T, Chen K, Luo M, Li Z et al. Global Prevalence of Hypertension in Children and Adolescents Younger Than 19 Years: A Systematic Review and Meta-Analysis. JAMA Pediatr. 2025;179(9):987-999. doi:10.1001/jamapediatrics.2025.2206 Liu K, Li C, Gong H, Guo Y, Hou B, Chen L. Prevalence and Risk Factors for Hypertension in Adolescents Aged 12 to 17 Years: A School-Based Study in China. Hypertens 2021; 78(5):1577-1585.doi:/10.1161/HYPERTENSIONAHA.121.17300 Craig A, Ware LJ, Mapanga W, Norris SA. A comparison of paediatric hypertension clinical practice guidelines and their ability to predict adult hypertension in an African birth cohort. J Hum Hypertens. 2023;37(6):455-462. doi:10.1038/s41371-022-00709-6 Additional Declarations The authors declare no competing interests. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9572596","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":632191830,"identity":"45b3af57-c915-4599-9163-004fe72e9f60","order_by":0,"name":"Saratu Ajike","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYFCCg81AwiaBQQLEOQDFRGhJI0kLAzMQHyZBC3/j4WaDD3/O5/HPbn744McZBjm+GwlsD7/g0SJx4GBz4sy228USd44ZG/bcYDCWvJHAbiyDzxqglsO8DbcTG27ksEkzfGBI3AC0RVoCjw55kJY/f84lzodqqSeoxQCoJZmB7QDQcJCWGwwJBkAtkh/waDEEajHsbUsuNgT75YyE4cwzD9uk8XlF7sbxxxI//tjlyd0GhdgxG3m+48nHJH/g0yNxAJULxIwNzDz4tPA3YBFkxGvLKBgFo2AUjDQAAA6rXBwmry7+AAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0001-7526-9416","institution":"Babcock University","correspondingAuthor":true,"prefix":"","firstName":"Saratu","middleName":"","lastName":"Ajike","suffix":""},{"id":632191831,"identity":"27af0af5-03d0-4f2e-aa0d-308545cba85c","order_by":1,"name":"Iyanuoluwa Okelola","email":"","orcid":"https://orcid.org/0009-0005-2361-4376","institution":"Babcock University","correspondingAuthor":false,"prefix":"","firstName":"Iyanuoluwa","middleName":"","lastName":"Okelola","suffix":""},{"id":632191832,"identity":"187ba4a3-6a20-4f54-83af-8cbadcd9fb9c","order_by":2,"name":"Jekayinoluwa Ogunbadejo","email":"","orcid":"","institution":"Babcock University","correspondingAuthor":false,"prefix":"","firstName":"Jekayinoluwa","middleName":"","lastName":"Ogunbadejo","suffix":""}],"badges":[],"createdAt":"2026-04-30 06:03:43","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-9572596/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9572596/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108803718,"identity":"4e24b393-792c-4687-a24d-9369fd245e5d","added_by":"auto","created_at":"2026-05-08 15:04:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":348061,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9572596/v1/26946735-009d-4590-9e35-9b035ff02285.pdf"},{"id":108382618,"identity":"84e4b547-1502-42c5-b203-92a74e3674fe","added_by":"auto","created_at":"2026-05-04 05:25:29","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":24681,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementaryfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-9572596/v1/6157a6d8f37dd7df32681dd6.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePrevalence and Associated Risk Factors of Elevated Blood Pressure Among Adolescents in Selected Universities in Ogun State, Nigeria: A Cross-Sectional Study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eHypertension has historically been viewed as a condition that primarily affects middle-aged and older adults. However, an expanding body of evidence over the past two decades suggests that elevated blood pressure is increasingly diagnosed during adolescence (10\u0026ndash;19 years) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This shift in disease patterns has important public health implications because adolescence is a sensitive developmental phase during which lifestyle behaviours, including dietary habits, physical activity, and substance use, are formed and frequently persist into later life, contributing to future cardiovascular risk profiles [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn sub-Saharan Africa, adolescent hypertension is an emergent concern. Findings across the region indicate substantial heterogeneity in prevalence estimates of hypertension and elevated blood pressure (EBP), ranging from less than 1% to more than 30%, with pooled prevalence figures of approximately 5\u0026ndash;6%, but these values have risen in recent years [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Within Nigeria, the prevalence of hypertension and elevated blood pressure ranges between 0.1% and 26.7% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These studies repeatedly implicate overweight and obesity, increased waist circumference, and sedentary behaviour as principal correlates of increased blood pressure in adolescents. Other risk factors for high blood pressure in adolescents include age, sex, obesity, physical inactivity, family history of hypertension in first-degree relatives, socioeconomic status, cigarette smoking, and alcohol intake [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition, studies have also reported either a greater prevalence in mid-adolescence or an increasing risk with age [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, comparability across studies is limited by differing blood pressure thresholds, measurement protocols, and sampling frames (school-only vs community), highlighting the need for localized surveys.\u003c/p\u003e \u003cp\u003eThe consequences of hypertension/increased blood pressure in adolescents are numerous and severe. The prevalence and severity of atherosclerosis are linked to childhood hypertension, a significant modifiable risk factor for cardiovascular disease. Furthermore, hypertension persists from infancy into adulthood and is linked to harmful cardiac alterations and vascular damage, which are linked to early cardiovascular disease in adulthood [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTherefore, the primary prevention of cardiovascular disease, especially for at-risk individuals such as those with obesity, diabetes, or chronic renal disease, among others, depends on early detection and efficient treatment of hypertension in children and adolescents [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Moreover, early detection can promptly hinder advancements in the treatment of hypertension and its complications [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], thereby protecting and promoting overall well-being. This calls for continuous routine screening and the identification of those at risk of grave consequences. Studies in Nigeria have focused primarily on adolescents in lower educational institutions, even though studies have noted an increasing prevalence with the age/stage or stage of adolescence. Thus, this study sought to determine the prevalence and associated risk factors for elevated blood pressure among adolescents enrolled in universities in Ogun State, Nigeria, underpinned by Blum\u0026rsquo;s model of health determinants [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], which illustrates how the environment, lifestyle, heredity, and medical care interact to influence health outcomes.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAim, Design, and Setting\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted to determine the prevalence of elevated BP and its associated risk factors in a population of 62,176 university students between January and March 2026. Universities in Ogun State are both public and private and are hosts to students from all over the country with various cultural, ethnic, and socioeconomic statuses. The study was conducted at six universities selected across the three Senatorial districts of the state, which ensured geographic and institutional representation. Participants were eligible if they consented or obtained consent from parents where applicable. Those with preexisting chronic illness or medical conditions that could influence anthropometric and BP measurements and who declined anthropometric measurements were excluded.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample and sampling procedure\u003c/h3\u003e\n\u003cp\u003eA sample of 306 participants was derived via the single population proportions formula described by Cochran. A multistage sampling procedure was employed to select the study participants. First, universities were selected from each of the three Senatorial districts in Ogun State. Two universities were selected per senatorial district, one public and one private, via simple random sampling. In one district with only one public university, purposive sampling was used to select the only existing university, and simple random sampling was then used to select the private university. In districts where no public university existed, two private universities were selected via simple random sampling. The number of students to be sampled from each university was derived by proportionate allocation via the following formula: s\u003csub\u003en =\u003c/sub\u003e student population per school/total population in all schools \u0026times; sample size. In the third stage, faculties were selected, beginning with stratification into health-related and non-health-related faculties. Two faculties were then selected from each category via simple random sampling to ensure diversity in academic orientation. The number of students to be sampled from each faculty was determined proportionally via the following formula: f\u003csub\u003en\u003c/sub\u003e = number of students in the faculty \u0026times; total sample allocated to the university/ total number of students in the selected faculties. In the fourth stage, the two departments with the largest student populations were selected from the faculties. The number of respondents selected from each department was determined via proportional allocation, guided by the following formula: d\u003csub\u003en\u003c/sub\u003e = Department Population \u0026times; Faculty Sample/Total Population of selected departments. In the fifth stage, eligible students aged 16\u0026ndash;19 years were selected from each department via systematic random sampling. The sampling interval was determined by dividing the number of eligible students by the allocated departmental sample size. A random starting point was chosen, and every hth eligible student was selected until the required sample size was achieved. The sampling interval (h) was determined separately for each department via the following formula: h\u003csub\u003en\u003c/sub\u003e = Number of eligible students in the department/Departmental sample size. The selected students were approached in classrooms during scheduled lectures, with permission obtained from course coordinators and lecturers, and recruitment took place at the end of lectures to minimize academic disruption.\u003c/p\u003e \u003cp\u003eWritten informed consent was obtained from each eligible respondent before data collection commenced.\u003c/p\u003e\n\u003ch3\u003eData collection and measurements\u003c/h3\u003e\n\u003cp\u003eData were collected via a structured pretested questionnaire adapted from the literature related to all variables of interest [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eReviews from three experts in public health promotion confirmed the content validation by assessing the relevance, clarity, and cultural appropriateness of the instrument. Minor modifications were subsequently made to ensure the questionnaire\u0026rsquo;s adequacy. The questionnaire was developed into five sections, which collected data on sociodemographic characteristics and potential risk factors.\u003c/p\u003e \u003cp\u003eFor the anthropometric measurements, the heights, recorded to the nearest 0.1 cm, and the weights, recorded to the nearest 0.1 kg, were measured via a stadiometer and a calibrated digital weighing scale, respectively. The body mass index (BMI) was subsequently calculated and recorded in kg/m\u0026sup2;. Blood pressure readings were taken via a calibrated automated digital sphygmomanometer. The participants were allowed to rest for at least 5 minutes before the measurements were taken. All processes followed standard protocols. Three blood pressure readings were taken at two-minute intervals, and the average of the second and third readings was used for analysis. Elevated blood pressure was defined according to established adolescent guidelines [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e All protocols received ethical approval. Permission was also obtained from the university's administration. Confidentiality and anonymity were maintained throughout the study.\u003c/p\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eThe data collected were carefully checked for completeness and consistency before analysis. The completed questionnaires were coded and entered into IBM SPSS version 27. Data cleaning procedures, including range checks, identification of missing values, and correction of entry errors, were performed to ensure data accuracy. Descriptive statistics were used to summarize the characteristics of the study participants and key study variables. Descriptive statistics (frequencies, percentages, means, and standard deviations) were used to describe the data. Inferential statistics (chi-square test and binary logistic regression) were used to test the hypotheses. In the binary logistic regression analysis to identify significant independent predictors of elevated blood pressure among adolescents, variables that were statistically significant at the bivariate level were entered into the regression model. Adjusted odds ratios (AORs) with 95% confidence intervals (CIs) were reported to determine the strength and direction of associations between predictors and elevated blood pressure. Significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eDemographic characteristics of the adolescents\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe majority of the respondents were aged 18\u0026ndash;19 years, and female participants constituted the larger proportion of the study population. Most reported receiving over ₦40,000 as a monthly allowance. In addition, the majority indicated that their parents had a tertiary education (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDemographic characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNumber of participants\u0026thinsp;=\u0026thinsp;306\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e76.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLevel of Study\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e300\u003c/p\u003e \u003cp\u003e400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50\u003c/p\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.4\u003c/p\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAverage Monthly Allowance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;₦10,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e₦10,000\u0026ndash;20,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e₦21,000\u0026ndash;40,000\u003c/p\u003e \u003cp\u003e\u0026gt;₦40,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.5\u003c/p\u003e \u003cp\u003e34.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHighest Parental Education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTertiary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eType of accommodation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOn-campus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e173\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOff-campus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBlood pressure distribution\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows that elevated blood pressure was prevalent in 17% of the respondents, whereas hypertension was present in 32.9% of the respondents.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Blood Pressure among Respondents\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eNumber of participants\u0026thinsp;=\u0026thinsp;306\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e% 95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood Pressure Category\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.3 44.7\u0026ndash;55.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.3 13.1\u0026ndash;21.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 1 Hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23.2 18.4\u0026ndash;28.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage 2 Hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.2 6.0 -12.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eRisk factor characteristics\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTables\u0026nbsp;3, 4, and 5 (Additional file 1) present the biological, lifestyle, and psychosocial characteristics of the respondents. The largest proportion of participants had a normal BMI, whereas smaller proportions were underweight, overweight, or obese. The mean height, weight, and BMI of the respondents were 1.69\u0026thinsp;\u0026plusmn;\u0026thinsp;0.10 m, 65.9\u0026thinsp;\u0026plusmn;\u0026thinsp;19.6 kg, and 22.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.7 kg/m\u0026sup2;, respectively. (Table\u0026nbsp;3). Most had poor dietary habits (69.5%) or high salt intake (63.4%). Alcohol was consumed by 5.3% of the participants, tobacco by 1.6%, and drugs by 2.6%. The majority were physically inactive (66.3%) (Table\u0026nbsp;4). High stress was reported by 41.8% of the participants (Table\u0026nbsp;5). Most had high family support (96.1%). Most (76.5%) experienced short sleep durations (Table\u0026nbsp;5).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eRisk factors associated with elevated blood pressure\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e6\u003c/span\u003e indicates that only BMI (χ\u0026sup2; = 15.47, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and family history (χ\u0026sup2; = 9.56, p\u0026thinsp;\u0026lt;\u0026thinsp;0.008) were significant risk factors for EBP among these adolescents. Furthermore, logistic regression analysis revealed that these factors were also significant independent predictors of EBP (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation between risk factors and elevated blood pressure\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSub variable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eElevated BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eχ\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNormal BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eElevated BP\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16\u0026ndash;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.739\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e2.663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.103\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e15.470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.001*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eAlcohol Consumption\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-drinker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAlcohol User\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eTobacco usage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-tobacco smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152\u003c/p\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149\u003c/p\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.641\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTobacco User\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSalt Intake\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh Salt Intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow salt intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSleep Duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdequate Sleep Duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.226\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShort Sleep Duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eStress Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eFamily History\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003e* indicates that the \u003cem\u003ep\u003c/em\u003e value is statistically significant (\u0026lt;\u0026thinsp;0.05)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePredictors of elevated blood pressure\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWald\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ep value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eAOR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI Category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal (Ref)\u003c/p\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003cp\u003eOverweight\u003c/p\u003e \u003cp\u003eObese\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-1.857\u003c/p\u003e \u003cp\u003e-1.478\u003c/p\u003e \u003cp\u003e-1.400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.615\u003c/p\u003e \u003cp\u003e0.584\u003c/p\u003e \u003cp\u003e0.613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9.119\u003c/p\u003e \u003cp\u003e6.408\u003c/p\u003e \u003cp\u003e5.214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.003*\u003c/p\u003e \u003cp\u003e0.011*\u003c/p\u003e \u003cp\u003e0.022*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.156\u003c/p\u003e \u003cp\u003e0.228\u003c/p\u003e \u003cp\u003e0.246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.047\u0026ndash;0.521\u003c/p\u003e \u003cp\u003e0.073\u0026ndash;0.716\u003c/p\u003e \u003cp\u003e0.074\u0026ndash;0.820\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical Activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eActive (Ref)\u003c/p\u003e \u003cp\u003eInactive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.667\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.676\u0026ndash;1.843\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDietary Habit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGood (Ref)\u003c/p\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.056\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.281\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.040\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e0.945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.545\u0026ndash;1.638\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily History of Hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo (Ref)\u003c/p\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.837\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.423\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.912\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.048*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e2.310\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.008\u0026ndash;5.295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale (Ref)\u003c/p\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.259\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.082\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.298\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e1.309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.788\u0026ndash;2.172\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychosocial Stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow (Ref)\u003c/p\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.898\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e1.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.636\u0026ndash;1.674\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalt Intake\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow (Ref)\u003c/p\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.047\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003cp\u003e1.048\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.640\u0026ndash;1.716\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was\u003c/em\u003e considered statistically significant (*).\u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSIONS","content":"\u003cp\u003eThis study examined the prevalence and determinants of elevated blood pressure (EBP) among adolescents at selected universities in Ogun State, Nigeria. These findings indicate that elevated blood pressure is prevalent and is influenced mainly by the biological factors of BMI and family history. These factors remained significant predictors of EBP after further analysis.\u003c/p\u003e \u003cp\u003eThe prevalence of elevated blood pressure among the adolescents in this study was greater than that reported elsewhere [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This difference may reflect regional variations in lifestyle, dietary practices, and physical activity. This finding aligns with emerging evidence that adolescent hypertension is rising globally, particularly in sub-Saharan Africa, where dietary transitions, increased consumption of processed foods, and sedentary lifestyles have been linked to increased blood pressure among youth [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. National studies also report increasing levels of prehypertension and hypertension among university students, suggesting that cardiovascular risk factors manifest earlier in life [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. The prevalence observed in this study underscores the growing vulnerability of adolescent populations to cardiovascular risk factors and highlights the urgent need for targeted preventive strategies.\u003c/p\u003e \u003cp\u003eSeveral studies have shown that excess body weight is a strong predictor of elevated blood pressure among adolescents, as increased adiposity influences vascular resistance, sympathetic nervous system activity, and insulin sensitivity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Gafane-Matemane et al. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] reported that overweight and obese adolescents in sub-Saharan Africa are at increased risk of elevated blood pressure, whereas Li et al. [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and Wang et al. [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] similarly identified body weight and family history as key determinants of adolescent hypertension. The findings of this study therefore reinforce the biological link between body composition and cardiovascular risk [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe association and predictive power of family history suggest the influence of genetic predispositions and shared environmental factors within families. Shokunbi et al. [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e] reported a similar association in Ogun State, whereas Atoh et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] reported an increased likelihood of elevated blood pressure among adolescents with a positive family history. Ruan et al. [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] further emphasized the importance of familial risk factors in adolescent hypertension across different populations. This finding highlights the need to incorporate family history into screening and preventive strategies, as individuals with genetic susceptibility may require closer monitoring even in the absence of other risk factors [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNeither lifestyle nor psychosocial factors were associated with EBP. However, this does not imply that lifestyle factors are unimportant; rather, their effects may not have been sufficiently pronounced to reach statistical significance in this sample. The uniform lifestyle environment among university students may also have reduced observable differences in exposure. Additionally, behaviours such as alcohol, tobacco use, and sleep may have been underreported owing to social desirability bias. Despite insignificant results in the present study, others have demonstrated associations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Hence, the results need to be interpreted with caution, as lifestyle factors remain important contributors to long-term cardiovascular risk.\u003c/p\u003e \u003cp\u003ePsychosocial stress was examined but was not significantly associated with elevated blood pressure. While stress can affect cardiovascular health through sympathetic nervous system activation and behavioral changes, the findings suggest that in this adolescent population, short-term or self-reported stress may not manifest as measurable differences in blood pressure [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite its strengths in contributing to the need for routine screening for elevated blood pressure in adolescents, this study has several limitations. The cross-sectional design limits cause‒and‒effect accountability between EBP and identified risk factors. The self-reported behavioural factors were liable to recall and social desirability biases. Although a multistage sampling technique with proportional allocation was employed, the study was conducted at selected universities within Ogun State, which may limit the generalisability of the findings to all adolescents in Nigeria, particularly those not enrolled in tertiary institutions.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOverall, the findings highlight that elevated blood pressure among adolescents is still prevalent and is influenced by biological factors. These results reinforce evidence from Nigeria and Sub-Saharan Africa indicating that adolescent hypertension is increasing and underscore the urgent need for early screening and health education interventions that account for modifiable and nonmodifiable risk factors.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eEBP-Elevated Blood Pressure\u003c/p\u003e\n\u003cp\u003eCI-Confidence Interval\u003c/p\u003e\n\u003cp\u003eBMI-Body Mass Index\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eApproval for this study was obtained from the Babcock University Health Research Ethics Committee (BUHREC0112/26/1631).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConsent was obtained from all participants. For those under 18 years of age, assent was obtained from parents.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author upon reasonable request.\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\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo external funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSA conceptualised and designed the study, interpreted the data, and critically reviewed the manuscript for important intellectual content. IO designed the study, collected the data, analysed and interpreted the data, and critically assessed the manuscript. JO conceptualised, interpreted the data, critically analysed the manuscript for intellectual content, and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. (2021). (b). Adolescent health and development. https://www.who.int/ \u003c/li\u003e\n\u003cli\u003eNagata JM, Weinstein S, Alsamman S, Lee CM, Dooley EE, Ganson KT et al. Association of physical activity and screen time with cardiovascular disease risk in the Adolescent Brain Cognitive Development Study. BMC Public Health. 2024;24(1):1346. doi:10.1186/s12889-024-18790-6\u003c/li\u003e\n\u003cli\u003eLewandowska A, Rudzki G, Lewandowski T, Bartosiewicz A, Pr\u0026oacute;chnicki M, Stryjkowska-G\u0026oacute;ra et al. Overweight and obesity among adolescents: health-conscious behaviours, acceptance, and the health behaviours of their parents. BMC Public Health. 2025;25(1):418. Published 2025 Feb 2. doi:10.1186/s12889-025-21591-0\u003c/li\u003e\n\u003cli\u003eGafane-Matemane LF, Craig A, Kruger R, Alaofin OS, Ware LJ, Jones ESW et al. Hypertension in sub-Saharan Africa: the current profile, recent advances, gaps, and priorities. J Hum Hypertens. 2025;39(2):95-110. doi:10.1038/s41371-024-00913-6\u003c/li\u003e\n\u003cli\u003eEjike CECC. Prevalence of Hypertension in Nigerian Children and Adolescents: A Systematic Review and Trend Analysis of Data from the Past Four Decades. 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International Journal of Adolescent Health, 2021;1(2):15\u0026ndash;22. doi: 10.4314/ahs.v21i4.32\u003c/li\u003e\n\u003cli\u003eAbah RO, Ukpabi DE, Okoko JA. Prevalence of Hypertension Among Adolescents in Benue South, Nigeria. Journal of Hypertension and Cardiology, 2025;3(4):27-37.doi: 10.14302/issn.2329-9487.jhc-25-5726\u003c/li\u003e\n\u003cli\u003eKhoury M, Urbina EM. Hypertension in adolescents: diagnosis, treatment, and implications. Lancet Child Adolesc Health. 2021;5(5):357-366. doi:10.1016/S2352-4642(20)30344-8\u003c/li\u003e\n\u003cli\u003eBlum HL. Planning for Health: Development and Application of Social Change Theory. Human Sciences, 1974.\u003c/li\u003e\n\u003cli\u003eCenters for Disease Control and Prevention. Youth Risk Behavior Surveillance System (YRBSS). 2023. https://www.cdc.gov/healthyyouth/data/yrbs/index.htm \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Global School-based Student Health Survey (GSHS). 2018. Available from: https://www.who.int/teams/noncommunicable-diseases/surveillance/systems-tools/global-school-based-student-health-survey \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. (2011). WHO STEPwise approach to NCD risk factor surveillance (STEPS). https://www.who.int/teams/noncommunicable-diseases/surveillance/systems-tools/steps \u003c/li\u003e\n\u003cli\u003eBuysse DJ, Reynolds CF 3rd, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193-213. doi:10.1016/0165-1781(89)90047-4.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Alcohol, Smoking and Substance Involvement Screening Test (ASSIST). 2010. https://www.who.int/publications/i/item/9789241599380\u003c/li\u003e\n\u003cli\u003eCohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav. 1983;24(4):385\u0026ndash;396. https://www.jstor.org/stable/2136404\u003c/li\u003e\n\u003cli\u003eZimet GD, Dahlem NW, Zimet SG, Farley GK. The multidimensional scale of perceived social support. Journal of Personality Assessment. 1988; 52(1):30\u0026ndash;41. doi:10.1207/s15327752jpa5201_2\u003c/li\u003e\n\u003cli\u003eFlynn JT, Kaelber DC, Baker-Smith CM, Blowey D, Carroll AE, Daniels SR et al. Clinical Practice Guideline for Screening and Management of High Blood Pressure in Children and Adolescents. Pediatrics. 2017;140(3):e20171904. doi:10.1542/peds.2017-1904\u003c/li\u003e\n\u003cli\u003eLi, X., Zhang, Y., \u0026amp;amp; Chen, J. (2021). Obesity and blood pressure in adolescents: Evidence from a cross-sectional study in China. Clinical Hypertension, 27, 2. https://doi.org/10.1186/s40885-024-00278-5\u003c/li\u003e\n\u003cli\u003eWang Y, Li H, Chen S. Family history and obesity as predictors of adolescent hypertension in China: A cross-sectional study. BMC Public Health.2023;23(1):16331.\u003c/li\u003e\n\u003cli\u003eRuan X, Zhu A, Wang T, Chen K, Luo M, Li Z et al. Global Prevalence of Hypertension in Children and Adolescents Younger Than 19 Years: A Systematic Review and Meta-Analysis. JAMA Pediatr. 2025;179(9):987-999. doi:10.1001/jamapediatrics.2025.2206\u003c/li\u003e\n\u003cli\u003eLiu K, Li C, Gong H, Guo Y, Hou B, Chen L. Prevalence and Risk Factors for Hypertension in Adolescents Aged 12 to 17 Years: A School-Based Study in China. Hypertens 2021; 78(5):1577-1585.doi:/10.1161/HYPERTENSIONAHA.121.17300\u003c/li\u003e\n\u003cli\u003eCraig A, Ware LJ, Mapanga W, Norris SA. A comparison of paediatric hypertension clinical practice guidelines and their ability to predict adult hypertension in an African birth cohort. J Hum Hypertens. 2023;37(6):455-462. doi:10.1038/s41371-022-00709-6\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Adolescents, Biological factors, Elevated blood pressure, Lifestyle factors, Prevalence, Sociodemographic factors","lastPublishedDoi":"10.21203/rs.3.rs-9572596/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9572596/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eElevated blood pressure (EBP) among adolescents has emerged as a growing public health concern globally because of its potential progression to hypertension and cardiovascular diseases in adults. In Nigeria, evidence on the prevalence and determinants of elevated blood pressure among adolescents, particularly those enrolled in tertiary institutions, remains limited. Understanding the magnitude of the problem and its associated factors is essential for the development of targeted preventive strategies. This study investigated the prevalence and associated risk factors for elevated blood pressure among adolescents at selected universities in Ogun State, Nigeria.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study surveyed 306 adolescents aged 16\u0026ndash;19 years enrolled at universities in Ogun State, Nigeria. Data, including anthropometric and blood pressure measurements, were collected using a structured, validated questionnaire. Data were analysed via descriptive and inferential analyses (chi-square tests, binomial tests, and logistic regression) to examine associations and predictors of elevated blood pressure. Statistical significance was set at \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of elevated blood pressure was 17.3% (CI\u0026thinsp;=\u0026thinsp;13.1\u0026ndash;21.5). Body mass index (χ\u0026sup2; = 15.47, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and family history of hypertension (χ\u0026sup2; = 9.56, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.008) were significantly associated with elevated blood pressure and remained significant predictors. Lifestyle and psychosocial factors were not significantly associated with elevated blood pressure.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eElevated blood pressure among adolescents in the selected universities was high and was influenced by a combination of sociodemographic, biological, and lifestyle factors. Preventive interventions, including routine screening within tertiary institutions, are essential to mitigate the long-term cardiovascular risks associated with elevated blood pressure.\u003c/p\u003e","manuscriptTitle":"Prevalence and Associated Risk Factors of Elevated Blood Pressure Among Adolescents in Selected Universities in Ogun State, Nigeria: A Cross-Sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-04 05:25:09","doi":"10.21203/rs.3.rs-9572596/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4280acb1-4692-4bd4-b0ff-4d670cab33b9","owner":[],"postedDate":"May 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":67454005,"name":"Epidemiology"}],"tags":[],"updatedAt":"2026-05-04T05:25:09+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-04 05:25:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9572596","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9572596","identity":"rs-9572596","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}