Hypertension-Related Status and Influencing Factors among Chinese Children and Adolescents Aged 6~17 Years: Data from China Nutrition and Health Surveillance (2015-2017).
Yuxiang YangYuge LiHongtao YuanZengxu TangMulei ChenShuya CaiWei PiaoJing NanFusheng LiDongmei YuXiang GaoPublished in: Nutrients (2024)
Hypertension is currently highly prevalent worldwide and serves as one of the significant risk factors for chronic diseases and mortality. Adult hypertension can be traced back to, as well as prevented starting in, childhood and adolescence. However, due to the lack of surveillance among children and adolescents, the prevalence and influencing factors of hypertension-related conditions have not been well described. Hence, a total of 67,947 children and adolescents aged 6 to 17 from China Nutrition and Health Surveillance (2015-2017) were enrolled to describe the weighted average blood pressure level and the weighted prevalence of hypertension, pre-hypertension, and their distribution and to analyze the risk factors for hypertension and pre-hypertension among Chinese children and adolescents at a nationwide level. In summary, the weighted mean values of systolic blood pressure and diastolic blood pressure were 111.8 (95% CI, 111.2-112.5) mmHg and 66.5 (95% CI, 66.0-67.0) mmHg, respectively. The weighted prevalence of hypertension and pre-hypertension was 24.9% and 17.1%, respectively. Moreover, general obesity, overweight, and central obesity served as risk factors for hypertension and pre-hypertension among Chinese children and adolescents. The current study indicated that the prevalence of hypertension and pre-hypertension in Chinese children and adolescents was at a high level. Moreover, blood pressure screening should be further intensified for children and adolescents at a high risk of being overweight or obese.
Keyphrases
- blood pressure
- hypertensive patients
- heart rate
- type diabetes
- public health
- weight loss
- blood glucose
- metabolic syndrome
- risk factors
- insulin resistance
- physical activity
- magnetic resonance
- depressive symptoms
- mental health
- left ventricular
- skeletal muscle
- adipose tissue
- cardiovascular disease
- computed tomography
- machine learning
- artificial intelligence
- network analysis
- climate change
- ejection fraction
- data analysis