A person’s “lifetime dose” of obesity may be a better predictor of their risk of developing type 2 diabetes than a single reading of their body mass index, according to a new study out of the University of Michigan.
The concept refers to both the degree to which a person is overweight and the length of time they have been obese. The findings of the study, which were published in the Archives of Pediatric and Adolescent Medicine, indicate that doctors should consider both factors when they are assessing whether or not a patient needs to make lifestyle changes to prevent type 2 diabetes.
For the study, the researchers tracked the health of 8,000 adolescents and young adults for several years. The results showed that BMI was somewhat correlated with future diabetes risk. However, when the length of time participants were overweight was combined with measurements of BMI, the researchers found the composite number was a much more accurate predictor.
To determine a person’s lifetime obesity dose, they multiplied the number of BMI points a participant was above a healthy weight by the number of years they were at that weight. For example, a person who has had a BMI of 35 (which is 10 points above the healthy weight classification of 25) for 10 years would have a lifetime dose of 100.
The researchers said developing this type of scoring system could play an important role in determining the future type 2 diabetes risk of current adolescents. The obesity rate among this population is significantly higher than at any time prior. This means that more people will have lived with excess weight for longer periods of time. It is unknown exactly what this could mean for their health.
“We know that, due to the childhood obesity epidemic, younger generations of Americans are becoming heavier much earlier in life, and are carrying the extra weight for longer periods over their lifetimes,” said lead researcher Joyce Lee, MD. “When you add the findings from this study, rates of diabetes in the United States may rise even higher than previously predicted.”