相关实验视频
Updated: Jun 7, 2025

09:36
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
27.0K
青少年的屏幕时间和肥胖患病率:一种同时代替代分析分析
Dohyun Byun1, Yujin Kim1, Hajin Jang1,2
1Interdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, Republic of Korea.
BMC public health
|November 13, 2024
概括
减少青少年的屏幕时间和增加非屏幕活动,如体育活动,可以降低肥胖患病率. 这项研究强调了预防青少年肥胖的有效策略.
科学领域:
- 青少年健康 青少年健康
- 预防肥胖 预防肥胖
- 公共卫生战略 公共卫生战略
背景情况:
- 检查了屏幕时间和青少年肥胖之间的关联.
- 通过同时代替代模型,研究了将屏幕时间重新分配给其他活动.
- 旨在提供对青少年有效的肥胖预防策略的见解.
研究的目的:
- 为了分析屏幕时间和青少年肥胖之间的关系.
- 评估用其他活动代替屏幕时间对肥胖的影响.
- 为了告知青少年肥胖的公共卫生干预措施.
主要方法:
- 对5,180名韩国青少年 (4年级和7年级) 的横截面分析.
- 收集关于身高,体重,屏幕时间 (电视,电脑,智能手机) 和其他活动的数据.
- 用于评估肥胖患病率的多变量逻辑回归,调整为混因素.
主要成果:
- 长时间使用智能手机与更高的肥胖患病率有显著的关联.
- 电视观看与四年级学生的肥胖有关,而不是七年级学生.
- 用身体活动,睡眠,社交,阅读,学习或父母互动取代屏幕时间,可以降低肥胖风险.
结论:
- 减少屏幕时间和增加非屏幕活动是降低青少年肥胖的有效公共卫生策略.
- 身体活动,充足的睡眠和社交互动是预防肥胖的关键因素.
- 同时代替代模型为设计干预提供了有价值的见解.
相关概念视频
Obesity
381
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...
381
Bias in Epidemiological Studies
158
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
158
Regression Toward the Mean
6.3K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
6.3K

