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However, on an individual level, BMI can be less accurate, and it is best used in conjunction with other data (e.g., body composition tests) in the full assessment of an individual’s weight status. Furthermore, it is a good tool for estimating risk for specific outcomes (e.g., mortality, cardiovascular disease, diabetes). As such, on a population level, BMI can approximate levels of adiposity to a useful degree. However, it is a tool based on large sample sizes and is primarily used as a risk prediction tool over large numbers of people. It is important to understand that BMI does not discriminate between fat mass and lean mass and does not directly address adiposity (i.e., body fat percentage). However, oftentimes these discussions fail to understand exactly what BMI is and how best to utilize it as a tool. Those with a BMI of 30 or higher have reported a roughly 2-fold increase in the risk of stroke (Kurth et al., 2002).īMI is often debated as not being a useful tool. Stroke: Stroke is the fifth leading cause of disease among adults in the United States.Some evidence shows that for every unit increase in BMI, there is a 1-2 mmHg increase in blood pressure (Linderman et al., 2018).
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This is especially true when BMI is utilized to predict the risk of chronic diseases and many of the leading causes of death. When we look at human health data, BMI is one of the most effective risk prediction tools we have in modern medicine. BMI is an incredibly useful tool for risk prediction.