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Every Thursday, Laboratory Equipment features a Scientist of the Week, chosen from the science industry’s latest headlines. This week’s scientist is Nir Krakauer from the City College of New York. He worked with his father and found that a technique, known as A Body Shape Index (ABSI), is a more effective predictor of mortality than Body Mass Index (BMI), the most common measure used to define obesity.

Q: What made you interested in studying how body shape could be an indicator of mortality risk?

A: Most of my research relates to climate change and water supplies, but I'm also interested in public health. My father, a physician, treats patients with a variety of metabolic conditions, and has long explored whether body composition can factor into making better treatment decisions. In looking at whether body composition helps predict life expectancy, we first examined well-studied indicators like body mass index and waist circumference, and found that combining the two mathematically gives a measure of body shape that is a strong predictor of life expectancy.

Q: What are the future implications of your research and findings?

A: Our body shape index (ABSI) is easy to monitor by individuals and their physicians. ABSI may be able to provide a criterion to identify people at elevated risk that could benefit from treatments, and ABSI change could provide a measure of the effect of lifestyle changes on health.

Q: What was the most surprising thing you found in your research?

A: The large elevation in mortality rates seen in those with below-average weight was surprising. Public health campaigns frequently target overweight as a problem, but not underweight.

Q: What is the take home message of your research and results?

A: Excessive waist circumference, as quantified by ABSI, is a risk factor for premature death for people of any weight.

Q: What new technologies did you use in your lab during your research?

A: The body composition measurements we looked at were done with dual-energy X-ray absorptiometry. Our mathematical transformations and statistical analyses used the computer languages Octave and R.

Q: What is next for you and your research?

A: We hope to relate the body measurements that feature in ABSI to variability in body composition and metabolic indicators, and so help unravel the causes and effects of differences in body shape.

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