Predictors Of High Blood Pressure Research Articles

The present study attempts to associate anthropometric markers and blood pressure, thereby determining the most effective predictive marker for hypertension. A total sample of 350 adults aged 20 to 70 years was included in the study after getting consent. Anthropometric data and blood pressure were collected using standard procedures. Significant t-tests, chi-square tests, one-way ANOVA and Pearson correlation analyses were performed between the anthropometric body adiposity measures and blood pressure. The adjusted odds ratio (AOR) was calculated to assess the risk of hypertension. The receiver operating characteristic (ROC) curve analysis was performed to find the anthropometric markers predictive cut-off values. The prevalence of hypertension was 23.4% in males and 22.3% in females, respectively. The nutritional status of overweight and obese individuals was greater in females (38.9% and 13.1%) compared to males (37.1% and 8.6%). Anthropometric indicators, including BMI, WC, WHR, and WHtR, strongly correlate with elevated blood pressure in both sexes. The ROC analysis shows WHtR has the highest area under curve (AUC) value of 0.669 in males, whereas BMI has an AUC of 0.804 in females, indicating it is a more effective predictor for high blood pressure. A multivariate logistic regression analysis showed that age (6.20; 5.30), anxiety (8.13; 6.69), alcohol use (11.81; 6.64), physical activity (8.32; 9.17), smoking (10.05; 10.44), and salt intake (6.31; 5.40) were all independently associated risk factors of hypertension, irrespective of sex. The study concluded that anthropometric markers such as BMI, WC, WHR, and WHtR could predict hypertension risk among the Phalee Tangkhul. Lifestyle factors such as physical activity, smoking, alcohol consumption, salt intake, age, and anxiety are independent risk factors for high blood pressure.

Background: High blood pressure is a major global health issue, particularly in low and middle-income countries, where it contributes 45% of heart-related deaths. The researcher aimed to explore the extent of HBP by assessing the prevalence and contributing factors of high blood pressure among outpatients aged between 30 and 65 years at Kabutare district hospital in Rwanda. Objectives: To determine the prevalence of high blood pressure in this age group, identifying its contributing factors, and to examine the relationship between these factors and high blood pressure. High blood pressure often asymptomatic until significant damage occurs, is a key risk factor for various health issues. Despite effective treatments, many remain unaware of their condition, especially in resource-limited settings. Methods: The study used a cross-sectional design, collecting data through surveys that measured blood pressure and gathered information on socio-economic status, lifestyle habits, and demographic characteristics. Statistical analysis was conducted using SPSS version 20 to identify correlations between high blood pressure and socio-economic, lifestyle, and demographic factors. Results: The prevalence of high blood pressure was found to be 28.1% among respondents. Bivariate analysis showed significant associations between high blood pressure and variables such as income level (p < 0.001), frequency of alcohol consumption (p < 0.001), number of cigarettes smoked (p < 0.001), physical activity (p < 0.001), walking to work (p < 0.001), and salt intake (p = 0.021). In multivariate analysis, the strongest independent predictors of high blood pressure were high income (AOR = 15.8; 95% CI: 3.66–68.20), alcohol intake more than 3 times per week (AOR = 84.07; 95% CI: 18.04–391.83), smoking ≥5 cigarettes per day (AOR = 2.47×10⁹), and not walking to work (AOR = 5.33; 95% CI: 2.38–11.94). Age and salt consumption showed weaker and non-significant associations after adjustment. The model explained 53.4% of the variance in high blood pressure status (Nagelkerke R² = 0.534) and correctly classified 85% of cases. Conclusions: Hypertension is highly prevalent among Rwandan adults and is significantly associated with modifiable risk factors such as alcohol consumption, smoking, sedentary behavior, and higher income. These findings highlight the need for integrated community-level interventions focused on health education, behavior modification, and early screening. Strengthening primary healthcare services and promoting active lifestyles should be prioritized in national strategies to curb the growing burden of high blood pressure. Keywords: Factors associated, High blood pressure, Outpatient

Background: High blood pressure is a major global health issue, particularly in low and middle-income countries, where it contributes 45% of heart-related deaths. The researcher aimed to explore the extent of HBP by assessing the prevalence and contributing factors of high blood pressure among outpatients aged between 30 and 65 years at Kabutare district hospital in Rwanda. Objectives: To determine the prevalence of high blood pressure in this age group, identifying its contributing factors, and to examine the relationship between these factors and high blood pressure. High blood pressure often asymptomatic until significant damage occurs, is a key risk factor for various health issues. Despite effective treatments, many remain unaware of their condition, especially in resource-limited settings. Methods: The study used a cross-sectional design, collecting data through surveys that measured blood pressure and gathered information on socio-economic status, lifestyle habits, and demographic characteristics. Statistical analysis was conducted using SPSS version 20 to identify correlations between high blood pressure and socioeconomic, lifestyle, and demographic factors. Results: The prevalence of high blood pressure was found to be 28.1% among respondents. Bivariate analysis showed significant associations between high blood pressure and variables such as income level (p < 0.001), frequency of alcohol consumption (p < 0.001), number of cigarettes smoked (p < 0.001), physical activity (p < 0.001), walking to work (p < 0.001), and salt intake (p = 0.021). In multivariate analysis, the strongest independent predictors of high blood pressure were high income (AOR = 15.8; 95% CI: 3.66–68.20), alcohol intake more than 3 times per week (AOR = 84.07; 95% CI: 18.04–391.83), smoking ≥5 cigarettes per day (AOR = 2.47×10⁹), and not walking to work (AOR = 5.33; 95% CI: 2.38–11.94). Age and salt consumption showed weaker and non significant associations after adjustment. The model explained 53.4% of the variance in high blood pressure status (Nagelkerke R² = 0.534) and correctly classified 85% of cases. Conclusions: Hypertension is highly prevalent among Rwandan adults and is significantly associated with modifiable risk factors such as alcohol consumption, smoking, sedentary behavior, and higher income. These findings highlight the need for integrated community-level interventions focused on health education, behavior modification, and early screening. Strengthening primary healthcare services and promoting active lifestyles should be prioritized in national strategies to curb the growing burden of high blood pressure. Keywords: Factors associated, High blood pressure, Out-patient

Low-and middle-income countries account for over 80% of the global burden of cardiovascular disease (CVD). The Sub-Saharan African region is the most affected by CVD. Hypertensive Heart Disease (HHD) is a common complication of hypertension which is prevalent in the Democratic Republic of Congo (DRC). Our study aimed to identify the comorbidities associated with and the management of HHD in the DRC. This cross-sectional analysis was done at a 200-bed tertiary hospital in Kinshasa, DRC from January to December 2019. Data were collected retrospectively from patient records and missing values were generated by multiple imputations and the pooled values were used for data analysis. Bivariate and multiple correlation regression were used and odds ratios were generated. 34 (56.7%) of the 60 patients were male. The mean age was 63.2±9.7years, the mean BMI was 25.5±5.0 kg/m2, and 90.0% of patients were unemployed. Patients had dyslipidemia (43.3%), stroke (31.7%), and diabetes (10.0%). Mean serum creatinine (1.4±0.1 mg/dL), HDL (56.7±18.4 mg/dL), LDL (119.3±30.5 mg/dL), and median urea (24.0, IQR: 63.5 mg/dL) levels were abnormal. HDL was a predictor of high blood pressure (P <0.01). 83.3% of patients took statins, 78.3% took ACE inhibitors, and 70.0% took aspirin. Congolese HHD patients have multiple comorbidities. Efforts should be focused on increasing access to care through early diagnosis, early referral, and low-resource appropriate management.

EPH153 A Systematic Review of Risk Factors in Adolescents’ Predictors of High Blood Pressure in Adulthood

Abstract Background Hypertension is an important cardiovascular disease (CVD) in Brazil that affects approximately 30% of the adult population and accounts for nearly 50% of CVD-related deaths in the country. Identifying the main predictors of high blood pressure (BP) during childhood will help prevent the development of other CVDs in adulthood and deaths. This study aimed to estimate the effect of biological, demographic, and socioeconomic characteristics on the child’s BP at 6, 9 and 11 years of age. Methods Cohort study conducted with 181 children in Joinville city, southeastern Brazil. Individual data were collected during three follow-ups (2016, 2021, and 2023) in a private room of the family’s home. BP was measured by the auscultatory method. Poisson regression analysis adjusted for important covariates was used to estimate the relative risk (RR) of maternal and child weight status, demographic, and socioeconomic characteristics on the child’s BP at ages 6, 9 and 11. Results The prevalence of high BP in children at ages 6, 9 and 11 was 26.5%, 20.4% and 3.0%, respectively. Pre-pregnancy body mass index (BMI) and the child’s BMI were associated with high BP over the period investigated. The risk of children having high diastolic BP from 6 to 11 years of age was 6% higher (RR = 1.06; 95%CI 1.01, 1.11) when mothers had pre-pregnancy BMI ≥25 kg/m2, even after adjusting for child BMI. For each one kg/m2 increase in child BMI, the risk of children having high systolic BP pressure increased by 14% (RR = 1.14; 95%CI 1.05, 1.23), even after adjusting for pre-pregnancy BMI. Conclusions Pre-pregnancy excess body weight and increased child BMI were associated with high BP in children from 6 to 11 years of age. Addressing pre-pregnancy excess body weight and overweight in childhood, combined with BP monitoring from the age of six, are actions that can prevent the development of CVDs in adulthood, thus reducing a serious global public health problem. Key messages • Encouraging parents to monitor their children’s BP is essential to prevent associated chronic diseases throughout life. • Identifying children with altered blood pressure is an important public health indicator.

Emerging evidence indicates an association between blood pressure and inflammation, yet this relationship remains unclear in older adults, despite the elevated prevalence of hypertension. We investigated the association between blood pressure, high sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and white blood cell (WBC) count in a cohort of 3571 older adults aged 65 and above, and 587 middle-aged participants (55–59 years old). In women aged 65 and above, the relationship between inflammatory markers and blood pressure was consistent, with hs-CRP and WBC emerging as predictors of high blood pressure. For hs-CRP, the adjusted odds ratio (OR) was 1.5 (95% CI, 1.07 to 2.10, P = 0.02), and for WBC, the adjusted OR was 1.41 (95% CI, 1.02 to 1.94, P = 0.04), comparing the highest to the lowest quartiles. In men, only the WBC count was significantly associated with an increased OR for high BP (adjusted OR 1.49, 95% CI, 1.09 to 2.02, P = 0.01) across quartiles. Across the entire study population, in a fully adjusted model, all inflammatory markers were modestly associated with blood pressure levels, while the effect of being over 65 years was the most significant predictor of high blood pressure (OR 1.84, 95% CI, 1.50 to 2.25, P < 0.001). The link between key inflammation markers and blood pressure in older adults varies by sex and biomarker type and may differ from the relationship observed in younger individuals. These relationships are likely to be affected by factors linked to age.

Prediction of high blood pressure using machine learning techniques

Abstract Background Hypertension is considered not only a disease belonging to the large group of cardiovascular conditions, but also a risk factor that impacts at an economic, social, environmental, and cultural level, among others. Worldwide, it is recognized that arterial hypertension is increasing, with projections that estimate a 30% increase in prevalence by the year 2025. Objective. To develop a mathematical model for the prediction of high blood pressure in young people through digital dermatoglyphics. Methods This study was carried out in a sequence of three activities, which included in the first instance the collection and analysis of all the fingerprints of the upper limbs of each study participant with an image recognition device, to later carry out a characterization. in terms of number and type of footprint on each of the participants’ fingers. Subsequently, a multiple linear regression model was carried out for the right and left hand, which includes information on the type of footprint, number of relevant characteristics and other physical characteristics of everyone with which it is possible to determine an expected value of the pressure. diastolic and systolic arterial pressure, a model that was validated through the estimation of different types of error, the correlation coefficient, and the tracking signal, in a contrast between predicted and observed blood pressure in a second control sample with different participants. those used in the formulation of the mathematical model. Results The model had a significant R-square, allowing to establish a relationship of similarity and explanation of the blood pressure values, from the quantification of the characteristics of the fingerprints of the right and left hand with a significance level of 95%. Conclusions An important advance is presented for the prediction of high blood pressure through genetic markers with a non-invasive and low-cost method. Key messages • This type of research allows progress in the establishment of relationships between the subject's genetic conditions and the potential risk for the development of diseases. • Biotechnology is currently presented as a tool that contributes to the challenges that are generated in different areas such as the health sector.

High blood pressure (HBP) and obesity are major public health issues globally. The aim of the study was to evaluate the associations between tri-ponderal mass index (TMI) and body mass index (BMI) and HBP and to determine which anthropometric parameters may best predict HBP among Lithuanian children and adolescents aged 7–18 years. This cross-sectional study included 3710 Lithuanian children and adolescents aged 7–18 (52.7% boys and 47.3% girls). Each subject’s height, weight, and other anthropometric parameters, as well as blood pressure were measured according to standardized protocols; subsequently, TMI and BMI were calculated. The prevalence of HBP was 27% (the prevalence of elevated BP and hypertension was 13.7% and 13.3%, respectively), significantly higher for boys than for girls. The Pearson correlation coefficients between the BMI z-score and BP were higher than those between the TMI z-score and BP. In both sexes combined, the adjusted odds ratios (aOR) for HBP were increased significantly with increasing quartiles of TMI and BMI as compared to the first quartile (Q1) (Q2: aOR = 1.37 and aOR = 1.69; Q3: aOR = 2.10 and aOR = 2.27; Q4: aOR = 3.95 and aOR = 4.91, respectively). Significant associations also were observed between overweight and obesity (defined according to two methods: age- and sex-specific TMI percentiles and IOTF criteria) among boys and girls separately. BMI presented a higher area under the curve value than TMI for predicting HBP in children and adolescents. The findings of the study suggest that BMI and TMI are significantly associated with HBP. However, BMI is a better predictor for HBP than TMI among Lithuanian children and adolescents aged 7–18 years.

Although it is generally known that the type A behavior pattern (TABP) is associated with high blood pressure, recent studies have not consistently supported this association. Therefore, it is important to determine which factors moderate and mediate this relationship. The purpose of this study was to verify the moderated mediation effect of age and relaxation in the relationship between TABP and high blood pressure among middle-aged adults in South Korea. This study utilized data from the Korea Health and Genome Study (KHGS) supported by the Korea National Institute of Health. The participants in the present study were 10,022 Korean adults aged 40 to 69. To identify the conditional indirect effect of TABP on blood pressure through relaxation, with a consideration of age, a moderated mediation model using SPSS PROCESS macro 3.10 was applied. As is generally known, TABP was associated with high blood pressure, but its relevance was reversed through relaxation. Moreover, this relationship was moderated by age, which is known to be the most powerful predictor of high blood pressure. The lower age group with TABP exhibited a higher relaxation, whereas the higher age group with TABP demonstrated a lower relaxation. The findings demonstrate the need for relaxation education, stress management, or counseling to help individuals recognize their behavior patterns and strengthen the willingness and motivation for relaxation, especially among elderly people with TABP, in order to manage their blood pressure effectively.

Blood cardiometabolic impairments are associated to high blood pressure which is a pivot cardiovascular risk factor. The objective of this study was to assess cardiometabolic risk factors rates in subjects with high blood pressure in the steady state. A total of 292subjects, 107 cases and 185 controls were enrolled in cross-sectional study. Clinical and biological data were assessed during visits and after overnight fasting. Data were analyzed on R. A p-value &amp;#60; 0.05 was considered for statistical significance.Univariate analysis showed thatage &amp;#62; 50 years, visceral obesity, metabolic syndrome and hs- CRP ≥ 3 mg/L were significant predictors of high blood pressure: OR = 2.1, 95% CI [1.3-3.5], p = 0.003; OR = 1.6, 95% CI [1.0-2.6], p = 0.05; OR = 3.3; 95% CI [2.0-5.4], p &amp;#60; 0.001; OR = 16.8; 95% CI [9.4-31.4], p &amp;#60; 0.001, respectively. Multivariate analysis showed a positive association between obesity, metabolic syndrome, hs-CRP and high blood pressure: aOR = 2.29; 95% CI [1.14-4.69], p = 0.02; aOR = 3.47; 95% CI [1.64-7.61], p = 0.001; aOR = 18.10; CI, 2.5% to 95% [9.40-36.99], p &amp;#60; 0.001, respectively. In contrast, female sex was negatively associated with high blood pressure aOR = 0.31; CI, 95% CI [0.13-0.72], p &amp;#60; 0.008. Prevention policiesshould take into account blood cardiometabolic level for subjects with high blood pressure even though in the steady sate.

This study focus on utilizing the strength of Decision Tree Algorithm to develop a High Blood Pressure prediction model with the help of RapidMiner studio. A dataset containing 2000 records of patients with high blood pressure was collected from National Health and Nutrition Examination Survey (NHANES). The dataset was properly prepared and feature selection algorithms where used to determine the most relevant feature from the dataset. The features used in the course of the study are chronic kidney disease, adrenal and thyroid disorder, level of hemoglobin, genetic pedigree coefficient, age, alcohol conception, sex, BMI, and salt conception. The data set was split into two parts, training data set and testing data set. The training data set consist of 80% of the data while the testing data set contains 20% of the data. The decision tree model was trained with the training dataset and the developed model was applied to the test dataset. The performance of the model was further evaluated and produced an accuracy of 87% which shows that the Decision Tree algorithm can be effective on the prediction of High Blood Pressure.

IntroductionHypertension is an important cause of morbidity and mortality worldwide. Undiagnosed hypertension is a serious issue that leads to increased morbidity and mortality. In this study, we aim to identify the prevalence of undiagnosed hypertension in the healthy Jordanian population, as well as identify predictors of high blood pressure readings in presumably healthy Jordanians.Materials and MethodsWe recruited healthy visitors accompanying patients at our Jordan University Hospital Clinics ranging from 18 to 80 years of age. We measured each participant’s systolic and diastolic blood pressure at our outpatient clinics on two different days, one week apart. We also obtained demographic data, weight, height, smoking status, and family history of hypertension and cardiovascular diseases.ResultsA total of 896 participants were included in this study with a mean age of 48 years. The median of systolic blood pressure readings was 125 mmHg, and the median of diastolic blood pressure readings was 83 mmHg. 38.5% had undiagnosed stage 1 hypertension and 30.5% had undiagnosed stage 2 hypertension according to the American College of Cardiology/American Heart Association guidelines. On the other hand, 25.4% had undiagnosed grade 1 hypertension and 5.1% had undiagnosed grade 2 hypertension according to the European Society of Hypertension guidelines.ConclusionAccording to the ACC/AHA guidelines, 68.5% of previously healthy Jordanians met the criteria to be diagnosed with hypertension. Predictors of high systolic blood pressure were age, BMI and family history of CAD, while female gender is associated with a lower systolic blood pressure. For diastolic blood pressure, only BMI and family history of CAD were associated with significantly higher diastolic blood pressure, while female gender and exercise were significantly associated with lower diastolic blood pressure.

ObjectivesHypertension is a major risk factor for cardiovascular mortality globally and in Ghana. May Measurement Month (MMM) is a global awareness and screening campaign initiated by the International Society of Hypertension.MethodsParticipants were recruited by opportunist sampling in the Ashanti region of Ghana. The blood pressures of participants were measured three times and the mean of the last two readings was used for the analysis. Simple and multiple logistic regression was used to determine the predictors of hypertension.ResultsThe MMM 2018 awareness and screening campaign enrolled 5054 participants with a mean age of 39.4 ± 14.7 years. There were 2553 (50.6%) males, 987 (20.1%) of respondents had never checked their blood pressure and 676 (13.9%) had a prior history of hypertension. The prevalence of hypertension was 37.4%. We found that 589(66.8%) of 822 respondents with high blood pressure did not have a history of hypertension. Respondents with a known history of hypertension on medication were 442 (65.9%) and 219(68.0%) of 322 respondents on medication had uncontrolled hypertension. The predictors of high blood pressure in a multiple logistic regression were increasing age (OR = 1.05 CI 1.05–1.06, p < 0.001), history of alcohol intake (OR = 1.33 CI 1.04 −1.70, p = 0.02), overweight (OR = 1.4 CI 1.14–1.76, p = 0.001) and obesity (OR = 1.32, CI 1.01–1.74, p = 0.047).ConclusionThere is a high prevalence of hypertension in the Ashanti region in Ghana. Most participants with hypertension were not aware and the majority of those with hypertension on medications were uncontrolled. This calls for more education and screening of hypertension to decrease cardiovascular mortality.

Abstract Background Finger dermatoglyphics has been used as a genetic marker that contributes to the detection of sports talents and the establishment of predisposition to develop physical capacities. Additionally, it has begun to venture as a strategy in the early detection of risk factors for the development of chronic non-communicable diseases (CNCD), with arterial hypertension being one of the least studied factors in athletes; since its prevalence is &amp;lt; 3%, and it has been associated primarily with lifestyle. Therefore, the objective of this study was to know the correlation between the dermatoglyphic characteristics and the increase in blood pressure (BP) in young soccer players. Methods Analytical study. The sample was 86 male soccer players between 18 and 26 years of age; the case definition was soccer players with high blood pressure according to the AHA classification. Controls were those with normal blood pressure. The dermatoglyphic profile was scanned according to the Cummins and Midlo protocol on the 10 fingers of the hands. Statistical analyzes were processed in SPSS 25.0, at a significance level of p ≤ 0.05. The quantitative variables were evaluated with the Shapiro-Wilk test, the non-parametric with Mann-Whitney and the qualitative with the chi-square test. Results The Shapiro-Wilk test detected an abnormal distribution of the crests of the fingers index and atrial of the right hand (RH); of the index and middle fingers of the left hand (LH), and the summation of crests - SQTL of LH. In addition, a significant intergroup difference in all fingerprint patterns (arches, loops and whorls). Finally, a substantial difference for the fifth finger LH; fourth and fifth finger RH, and ulnar loops is more frequent in atrial LH, in annular and atrial RH in the high BP group. Conclusions Dermatoglyphics are suggested as a marker for the early diagnosis of elevated BP in young athletes. Key messages Dermatoglyphic patterns are a marker for the detection of high BP in young soccer players. Early detection of risk factors reduces the incidence of CNCD.

ABSTRACT Background Hypertension is related to increased body fat, which can be evaluated by anthropometric indicators. The aim of this study was to determine the predictive power of anthropometric indicators and to establish their cutoff points as discriminators of high blood pressure. Methods A cross-sectional study was conducted on 793 schoolchildren aged 10–14 years. Six anthropometric indices were used: body mass index-z-score (BMI-z-score), waist circumference (WC), waist-toheight ratio (WHtR), a body shape index (ABSI), body roundness index (BRI) and conicity index (CI). Elevated blood pressure (EBP) and hypertension (HTN) were characterized by values ≥ 90th and <95thpercentile and ≥ 95th percentile for systolic and/or diastolic blood pressure, respectively. The predictive power of anthropometric indices was analyzed by sex using the receiver operating characteristic curve(ROC). Results The prevalence of EBP and HTN was 11.0% and 14.8%, respectively. According to the analyses of the ROC curve, WC provided the largest area under the curve (AUC) value, while CI showed the lowest AUC value in predicting elevated blood pressure in the total sample. The BMI z-score provided the largest area under the curve (AUC) value (0.722), followed by WHtR (0.709) and BRI (0.709), in predicting hypertension in boys. Conclusions BMI z-score and WC may be the best predictors of EBP and BMI z-score for HTN among Jordanian schoolchildren.

High blood pressure (HBP) has been one of the major threats to human health. Lack of early detection and control of high blood pressure can cause severe damages to the heart which may lead to death. Most adults suffering from high blood pressure are unaware of the disease because it may have no warning signs or symptoms. This research focuses on the real time prediction of high blood pressure using a machine learning approach and control of high blood pressure using music. The study synchronizes a machine learning technique with a simulator to predict blood pressure and play low beat music if the blood pressure is high. The research was carried out using a large dataset with the following attributes (education, age, body mass index, current smoker and heart rate). Random forest algorithm was the machine learning technique used to construct and validate the prediction model. The prediction accuracy of the model exceeds 97% and the model was able to accurately predict blood pressure and play low beat music when the blood pressure is high.

PurposeThe aim of this study was to investigate the associations of high blood pressure (BP) and wide pulse pressure (PP) with obesity among common Korean people.Materials and MethodsThis study analyzed data from the Seventh Korean National Health and Nutrition Examination Survey (2017). The associations of BP with body mass index (BMI) and waist-to-height ratio (WHT2R) were investigated using their lump mean values.ResultsThe BPs of males and females increased with BMI, the PP of females increased with BMI and then decreased, and the PP of males is nearly independent of BMI. The BPs of males and females increased to their maximum values with WHT2R and then decreased. The PPs of males and females increased with WHT2R.ConclusionBMI can be used as a useful predictor for high BP, and WHT2R can be used as a useful predictor for wide PP.

In this study, the association between dietary pattern and lifestyle in predicting hypertension (HTN) among 425 overweight and obese children and adolescents aged 6 to 18 years was evaluated. In the current cross-sectional study, the lifestyle-scoring algorithm was developed considering the Iranian Health Reform Plan (HRP) criterion. HTN was defined according to standard protocols. Hierarchical linear regression models were used for the analysis. The prevalence of overweight/obesity was 5.82%. The results showed that systolic and diastolic blood pressure (SBP, DBP) had significant positive correlation with age (p < 0.001 and p < 0.001) and body mass index (BMI) (p < 0.005 and p < 0.007), respectively. Moreover, DBP had a significant correlation with fruit consumption of less than 2 servings per day versus no consumption (p = 0.014, B = 0.444), fruit consumption of more than 2 servings per day versus no consumption (p = 0.014, B = 0.480), and vegetable consumption less than 3 servings per day versus no consumption (p = 0.045, B = −0.374). Moreover, DBP had a significant correlation with fast foods/junk foods consumption of 1–2 items per week versus almost daily consumption (p = 0.047, B = −0.177). The final model could predict 32.1% of HTN by SBP and DBP (R2 = 0.32). According to our findings, lower intake of vegetables and fruits, higher amounts of fast foods, higher age and BMI could be potent predictors of high blood pressure among Iranian children and adolescents.