Hypertension in Low-Income Adolescents

The Evaluation of Ordinal Regression Model's Performance Through the Implementation of Multilayer Feed-Forward Neural Network: A Case Study of Hypertension

Background Hypertension, or high blood pressure, is a common medical condition that affects a significant portion of the global population. It is a major risk factor for cardiovascular diseases (CVD), stroke, and kidney disorders. Objective The objective of this study is to create and validate a model that combines bootstrapping, ordered logistic regression, and multilayer feed-forward neural networks (MLFFNN) to identify and analyze the factors associated with hypertension patients who also have dyslipidemia. Material and methods A total of 33 participants were enrolled from the Hospital Universiti Sains Malaysia (USM) for this study. In this study, advanced computational statistical modeling techniques were utilized to examine the relationship between hypertension status and several potential predictors. The RStudio (Posit, Boston, MA) software and syntax were implemented to establish the relationship between hypertension status and the predictors. Results The statistical analysis showed that the developed methodology demonstrates good model fitting through the value of predicted mean square error (MSE), mean absolute deviance (MAD), and accuracy. To evaluate model fitting, the data in this study was divided into distinct training and testing datasets. The findings revealed that the results strongly support the superior predictive capability of the hybrid model technique. In this case, five variables are considered: marital status, smoking status, systolic blood pressure, fasting blood sugar levels, and high-density lipoprotein levels. It is important to note that all of them affect the hazard ratio: marital status (β1, -17.12343343; p < 0.25), smoking status (β2, 1.86069121; p < 0.25), systolic blood pressure (β3, 0.05037332; p < 0.25), fasting blood sugar (β4, -0.53880322; p < 0.25), and high-density lipoprotein (β5, 5.38065556; p < 0.25). Conclusion This research aims to develop and extensively evaluate the hybrid approach. The statistical methods employed in this study using R language show that regression modeling surpasses R-squared values in predicting the mean square error. The study's conclusion provides strong evidence for the superiority of the hybrid model technique.

Prevalence and subtypes of hypertension in normal-weight and obese Indian adolescents: a cross-sectional study

This cross-sectional study examined the prevalence, stages, subtypes of hypertension, and the associated risk factors in adolescent school children in Western India. We screened 2,644 adolescents, from 10 different private and government schools in urban and rural areas for hypertension, as defined by the 2017 Clinical Practice Guidelines. The association of stages and subtypes with age, gender, body mass index, type of school, and place of residence was analysed. 197 children (7.5%) had hypertension; 170 (6.4%) had stage I, 27 (1%) had stage II and 76 (2.9%) had elevated blood pressure (EBP). The risk of EBP was higher in children > 15 years of age (p = 0.006). Compared with normal-weight children, obese, and overweight children had a higher risk of hypertension [odds ratio (OR) 9 (5.84, 13.88) and 3.77 (2.59, 5.48) respectively], whereas underweight children had a lower risk [OR 0.39 (0.16, 0.98)]. Normal-weight hypertension was seen in 5.2% and was higher in children from government schools (9.4%). Systolic-diastolic hypertension (SDH) was the most common subtype, seen in 136 (5.1%). SDH was more common in girls, in rural children, and in those with stage II hypertension. Isolated diastolic hypertension, seen in 51 (1.9%), was more common in boys, in urban children, and in those with EBP.

Prevalence and Risk Factors of Childhood Hypertension in Urban-Rural Areas of China: A Cross-Sectional Study

OBJECTIVE

The increased blood pressure level in children and adolescents is recognized as an essential predictor of adulthood cardiovascular disease. This study aimed to ascertain the prevalence and the urban-rural disparity of childhood hypertension in the southwest of China.

METHODS

Using stratified cluster sampling in urban and rural areas, a total of 13597 primary school children aged 6∼12 years living in the Southwest of China were included. The prevalence of hypertension was analyzed. The risk factors were collected by questionnaires, and the risk factors of childhood hypertension were analyzed by the logistic regression model.

RESULTS

The prevalence of hypertension was 13.75%, 9.02%, and 17.47% in total, urban, and rural children, respectively, and the urban-rural difference was 8.44% (95%CI: 7.32%, 9.56%). Children with obesity, maternal gestational hypertension, >10 months of breastfeeding, or low family income had a significantly increased prevalence of hypertension (29.4%, 20.00%, 16.31%, and 16.25%, respectively). Rural residence, intake of more pickle (in rural), maternal gestational hypertension (in urban), low birth weight (in rural), obesity, increased heart rate, and red blood cell counts were the risk factors of childhood hypertension. The adjusted R ² values were 13.61%, 23.25%, 10.88%, 11.12%, 12.23%, and 25.04% in the full models excluding and including serum indexes for total, urban, and rural children, respectively.

CONCLUSIONS

The prevalence of childhood hypertension is significant in the Southwest of China and alarming in rural areas, which requires community intervention. Children living in rural areas combined with obesity, low social economic status, dietary imbalance, and abnormal lipid metabolism were associated with an increased risk of hypertension, and routine care programs should be conducted to prevent childhood hypertension.