相关实验视频
Updated: Jun 13, 2025

09:36
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
27.0K
与肥胖相关的指数和高血压之间的相关性
Guangyi Zhao1,2, Zhiyi Zhou1,2
1Chongqing Medical University Chongqing 401121, China.
American journal of translational research
|September 12, 2024
概括
像身体形状指数 (ABSI) 和身体圆度指数 (BRI) 这样的肥胖指数与高血压有关. 这些,以及腰围与BRI比率 (WC/BRI),可以帮助预测高血压风险.
科学领域:
- 心血管健康 心血管健康
- 代谢综合征研究 代谢综合征研究
- 临床流行病学临床流行病学
背景情况:
- 高血压是全球主要的健康问题.
- 肥胖是高血压的已知危险因素之一.
- 新的肥胖指数可能提供更好的预测价值.
研究的目的:
- 调查肥胖指数和高血压之间的相关性.
- 评估这些指标对高血压的预测能力.
- 为高血压预防和治疗策略提供信息.
主要方法:
- 160名成年参与者的回顾性研究 (2023年1月至2024年1月).
- 参与者分为高血压 (n=83) 和非高血压 (n=77) 组.
- 对人口和肥胖相关指数的分析,包括腰围 (WC),身体形状指数 (ABSI) 和身体圆度指数 (BRI).
主要成果:
- 在高血压组中,平均ABSI,BRI和WC显著更高 (P<0.05).
- 后勤回归确定了ABSI,BRI和WC/BRI作为显著的高血压风险因素 (P<0.05).
- 对于ABSI,BRI和WC/BRI的综合预测值 (曲线下的面积=0.731) 超过了个别指数.
结论:
- ABSI,BRI和WC/BRI是高血压的潜在独立危险因素.
- 这些指数,单独或组合,可以帮助高血压风险预测.
- 进一步的研究可以验证这些发现的临床应用.
更多相关视频
相关概念视频
Obesity
411
The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
411
Factors affecting Blood pressure
3.0K
Several physiological and lifestyle factors influence blood pressure (BP). Understanding these factors is crucial as they are significant in patient education and blood pressure management.
Physiological Factors:
Physiological Factors:
3.0K
Hypertension and Regulation of Blood Pressure
1.9K
Hypertension, the most common cardiovascular disease, is diagnosed through repeated measurements of elevated blood pressure. Its risks, including damage to the kidney, heart, and brain, are directly proportional to blood pressure levels. Starting from 115/75 mm Hg, the risk of cardiovascular disease doubles with each increment of 20/10 mm Hg. The diagnosis relies on blood pressure measurements, not on patient symptoms, as hypertension is often asymptomatic until end-organ damage is imminent or...
1.9K
Correlations
32.7K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
32.7K
Hormonal Regulation of Blood Pressure
2.5K
Endocrinal or hormonal intervention in the cardiovascular system is predominantly exerted by the catecholamines - epinephrine and norepinephrine, as well as a slew of hormones that interact with renal function to modulate blood volume.
Epinephrine and Norepinephrine
The adrenal medulla releases epinephrine and norepinephrine, catecholamines that enhance and extend the sympathetic or "fight or flight" physiological response. These hormones escalate heart rate and the force of contraction...
Epinephrine and Norepinephrine
The adrenal medulla releases epinephrine and norepinephrine, catecholamines that enhance and extend the sympathetic or "fight or flight" physiological response. These hormones escalate heart rate and the force of contraction...
2.5K
Coefficient of Correlation
6.1K
The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable x and the dependent variable y.
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the...
6.1K

