A study published in the *International Journal of Obesity* (2008) evaluated the accuracy of body mass index (BMI) in diagnosing obesity in the US adult population. The study analyzed data from 13,601 participants, including 6,580 men and 7,021 women, from the Third National Health and Nutrition Examination Survey (NHANES III). Body fat percentage (BF%) was measured using bioelectrical impedance analysis, and obesity was defined as BF% > 25% in men and > 35% in women. The study found that BMI-defined obesity (≥30 kg/m²) had poor sensitivity (36% in men, 49% in women) but good specificity (95% in men, 99% in women) to detect BF%-defined obesity. However, BMI's diagnostic performance declined with increasing age. BMI showed a moderate correlation with BF% (R² = 0.44 in men, 0.71 in women) and lean mass (R² = 0.50 in men, 0.55 in women), but it failed to distinguish between BF% and lean mass, especially in intermediate BMI ranges. The study concluded that while BMI correlates well with BF%, its diagnostic accuracy is limited, particularly for individuals with BMI between 25–30 kg/m². A BMI cut-off of ≥30 kg/m² has good specificity but misses more than half of people with excess fat. The U- and J-shaped associations between BMI and health outcomes may be partly explained by BMI's inability to differentiate between fat and lean mass in intermediate BMI ranges. The study highlights the limitations of using BMI as a sole diagnostic tool for obesity, especially in intermediate BMI ranges where it may misclassify individuals. While BMI is useful for identifying extreme obesity (≥30 kg/m²), it is less effective in detecting obesity in those with normal or mild BMI elevations. The study also suggests that BMI may underestimate the true prevalence of obesity, as it misclassifies many obese individuals as normal or overweight. The findings emphasize the need for additional measures to assess body fatness and distribution, particularly in individuals with intermediate BMI. The study underscores the importance of using more accurate methods, such as bioelectrical impedance analysis, to better understand body composition and improve the diagnosis of obesity.A study published in the *International Journal of Obesity* (2008) evaluated the accuracy of body mass index (BMI) in diagnosing obesity in the US adult population. The study analyzed data from 13,601 participants, including 6,580 men and 7,021 women, from the Third National Health and Nutrition Examination Survey (NHANES III). Body fat percentage (BF%) was measured using bioelectrical impedance analysis, and obesity was defined as BF% > 25% in men and > 35% in women. The study found that BMI-defined obesity (≥30 kg/m²) had poor sensitivity (36% in men, 49% in women) but good specificity (95% in men, 99% in women) to detect BF%-defined obesity. However, BMI's diagnostic performance declined with increasing age. BMI showed a moderate correlation with BF% (R² = 0.44 in men, 0.71 in women) and lean mass (R² = 0.50 in men, 0.55 in women), but it failed to distinguish between BF% and lean mass, especially in intermediate BMI ranges. The study concluded that while BMI correlates well with BF%, its diagnostic accuracy is limited, particularly for individuals with BMI between 25–30 kg/m². A BMI cut-off of ≥30 kg/m² has good specificity but misses more than half of people with excess fat. The U- and J-shaped associations between BMI and health outcomes may be partly explained by BMI's inability to differentiate between fat and lean mass in intermediate BMI ranges. The study highlights the limitations of using BMI as a sole diagnostic tool for obesity, especially in intermediate BMI ranges where it may misclassify individuals. While BMI is useful for identifying extreme obesity (≥30 kg/m²), it is less effective in detecting obesity in those with normal or mild BMI elevations. The study also suggests that BMI may underestimate the true prevalence of obesity, as it misclassifies many obese individuals as normal or overweight. The findings emphasize the need for additional measures to assess body fatness and distribution, particularly in individuals with intermediate BMI. The study underscores the importance of using more accurate methods, such as bioelectrical impedance analysis, to better understand body composition and improve the diagnosis of obesity.