Reduction seen in mean weight-for-length trajectory for children in the clinic + digital intervention group<\/p>\n<\/h3>\n
By Elana Gotkine HealthDay Reporter<\/b>
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FRIDAY, Nov. 8, 2024 (HealthDay News) — A health literacy-informed digital intervention reduces the incidence of obesity at 24 months of age, according to a study published online Nov. 3 in the Journal of the American Medical Association <\/em>to coincide with the annual meeting of The Obesity Society (ObesityWeek), held from Nov. 3 to 6 in San Antonio.<\/p>\n William J. Heerman, M.D., M.P.H., from the Vanderbilt University Medical Center in Nashville, Tennessee, and colleagues compared the effectiveness of adding a digital childhood obesity prevention intervention to health behavior counseling. Pediatric clinicians used health literacy-informed booklets at well-child visits to promote healthy behaviors in the clinic-based health behavior counseling group; families also received health literacy-informed, individually tailored, responsive text messages to support health behavior goals in the clinic + digital intervention group (451 and 449 participants, respectively).<\/p>\n The researchers found that the mean weight-for-length trajectory was lower for children in the clinic + digital intervention group, with an estimated reduction of 0.33 kg\/m at 24 months. In addition, there was an adjusted mean difference of \u22120.19 for both weight-for-length z score and body mass index z score. At 24 months, 23.2 and 24.5 percent of the clinic + digital intervention group and the clinic-only group, respectively, had overweight or obesity (adjusted risk ratio, 0.91; 95 percent confidence interval, 0.70 to 1.17). At 24 months, 7.4 and 12.7 percent of the clinic + digital intervention group and the clinic-only group, respectively, had obesity (adjusted risk ratio, 0.56; 95 percent confidence interval, 0.36 to 0.88).<\/p>\n “The substantial reduction in risk of childhood obesity observed in this study could have significant population-level impact if implemented at scale,” the authors write.<\/p>\n One author disclosed ties to Medeloop.ai, an artificial intelligence-driven platform that supports clinical research.<\/p>\n Abstract\/Full Text (subscription or payment may be required)<\/a><\/p>\n