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NIH awards funds for study of weight loss predictors after bariatric surgery

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Miriam Hospital in Rhode Island and Beth Israel Deaconess Medical Center in New York have been awarded $1.3 million from the National Institute of Diabetes and Digestive Kidney Diseases to study predictors of weight loss following bariatric surgery, according to a press release.

“Very little is known about why some people are more successful than others at keeping weight off after having bariatric surgery,” Dale Bond, PhD, of The Miriam Hospital’s Weight Control and Diabetes Research Center, said in a the release. “Behavioral factors are thought to be very influential, but guidelines for behavior changes among bariatric surgery patients are often vague and not well supported by scientific research. Our goal is to collect data to improve behavioral guidelines and help increase weight loss after bariatric surgery.”

In the study, approximately 100 bariatric surgery patients will be followed before surgery and four times throughout the year after surgery. They will wear wristwatch-like sensor devices and use smartphones to monitor eating, physical activity behavior, mood, hunger and cravings. Recruitment is set to begin in early 2016.

“This study is exciting because this could lead to improve behavioral guidelines and new behavioral treatments, strategies and tools to maximize weight loss after bariatric surgery,” Graham Thomas, PhD, also of The Miriam Hospital’s Weight Control and Diabetes Research Center, said in the release.

The study is an extension of one being conducted by Bond and Thomas that uses real-time data to analyze weight-related behaviors linked with bariatric surgery.

“Not enough research has been conducted on behavioral, psychological and environmental predictors of weight loss after bariatric surgery,” Bond said. “This study will help to fill the gap using a unique and highly innovative mobile health platform combining sensor technology with a smartphone-based, self-reporting tool to measure behavioral, psychological and environmental predictors of weight loss continuously — in real time — in the patient’s natural environment.”