评估与身高正常化腹部身体组成指数的健康关联:单中心横截面研究
Yupeng Liu1, Hangqian He1, Keyu Qian1
1Department of Preventive Medicine, School of Public Health and Management, Wenzhou Medical University, Wenzhou, China.
Journal of cachexia, sarcopenia and muscle
|October 7, 2024
概括
新的高度正常化腹部脂肪指数,包括内脏脂肪组织 (VAT) 和腹部总脂肪组织 (TAT),比传统的BMI和腰围 (WC) 在中国人群中更好地预测健康结果.
科学领域:
- 肥胖和代谢健康研究.
- 身体组成的放射性评估.
- 在不同的人口统计数据中进行人口健康研究.
背景情况:
- 像BMI和WC这样的传统指标不足以捕捉与腹部脂肪分布相关的健康风险.
- 在中国人群中,身高正常化的身体组成变异性还未得到充分研究.
- 计算机断层扫描 (CT) 扫描为脂肪组织分布提供了详细的见解.
研究的目的:
- 通过CT扫描引入和验证使用腹部脂肪的新型高度正常化指数.
- 评估这些新指数与大型中国队列中各种健康结果的关联.
- 为了比较高度规范化指数与传统指标的预测能力.
主要方法:
- 利用来自各种健康群体的大型多元化中国人口的CT扫描.
- 应用了全尺度生长模型来导出高度规范化指数 (身体组成/身高).
- 使用后勤回归来分析指数和健康结果之间的关联,控制混因素.
主要成果:
- 对于内脏脂肪组织 (VAT),皮下脂肪组织 (SAT),全腹脂肪组织 (TAT) 和腹直径 (SAD) 确定了不同的缩放能力 (β),性别差异显著.
- 高度正常化的增值税,TAT和SAD指数显示出与不良健康结果的显著积极关联.
- 在控制BMI和WC后,皮下脂肪组织 (SAT) /身高没有保持显著的关联.
结论:
- 高度规范化指数,特别是VAT/高度β,TAT/高度β和SAD/高度β,对于评估健康结果具有显著的临床实用性.
- 与传统方法相比,这些新型指数提供了与肥胖相关的健康风险的更细致的评估.
- 这些发现支持从像BMI这样的传统指标转向更复杂的,高度调整的肥胖度量.
相关概念视频
Applications of Normal Distribution
5.0K
The normal distribution is a useful statistical tool. One of its practical applications is determining the door height after considering the normal distribution of heights of persons, such that many can pass through it easily without striking their heads. The normal distribution can also determine the probability of a person having a height less than a specific height.
The heights of 15 to 18-year-old males from Chile from 1984 to 1985 followed a normal distribution. The mean height is 172.36...
The heights of 15 to 18-year-old males from Chile from 1984 to 1985 followed a normal distribution. The mean height is 172.36...
5.0K
Two-Way ANOVA
2.6K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
2.6K
Obesity
392
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...
392
One-Way ANOVA: Unequal Sample Sizes
5.7K
One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
5.7K
Variation: Normal Distribution, Range, and Standard Deviation
22.2K
In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
22.2K
One-Way ANOVA: Equal Sample Sizes
3.2K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
3.2K


