Mobile Intervention Helps Moms With Obesity Reduce Gestational Weight Gain

A mobile health intervention helped pregnant patients with overweight or obesity reduce gestational weight gain (GWG), a cluster-randomized trial showed.

The weekly rate of GWG was significantly lower in the intervention group versus the standard care group (mean 0.25 vs 0.28 kg/week; mean between-group difference -0.03, 95% CI -0.05 to -0.01), reported Monique M. Hedderson, PhD, of Kaiser Permanente Northern California in Pleasanton, and colleagues.

Total GWG was also significantly lower in the intervention group, at a mean of 9.7 kg compared with 10.6 kg in the standard care group (mean between-group difference -0.87, 95% CI -1.40 to -0.34), they wrote in JAMA Network Open.

Additionally, there were fewer patients in the intervention group who exceeded Institute of Medicine (IOM) guidelines for the weekly rate of GWG compared with the standard care group (51.9% vs 60.2%; relative risk [RR] 0.86, 95% CI 0.78-0.95) and fewer who exceeded IOM guidelines for total GWG (44.1% vs 51.2%; RR 0.87, 95% CI 0.77-0.98).

The proportion below the guidelines for weekly rate of GWG was higher in the intervention group versus the standard care group (21.8% vs 17.2%; RR 1.27, 95% CI 1.01-1.61), and the same was true for the proportion below the guidelines for total GWG (26.8% vs 21.5%; RR 1.23, 95% CI 1.04-1.45).

“Even modest reductions in weight gain translated into fewer patients exceeding recommended guidelines, which has important implications for maternal and infant health at a population level,” Hedderson told MedPage Today.

Excessive GWG elevates risks of adverse perinatal and maternal complications. In the U.S., more than 60% of pregnant people enter pregnancy with overweight or obesity and more than half exceed IOM guidelines for GWG. The U.S. Preventive Services Task Force has advised that intensive behavioral counseling interventions reduce GWG, but those interventions can be resource-intensive and hard to roll out.

The Lifestyle, Eating, and Activity in Pregnancy (LEAP) intervention utilizes a smartphone app, wireless scale, and activity tracker to promote healthy eating and increased activity. As a stepped intervention, more intensity is reserved for those on track to gain more weight. All participants are given a personalized calorie target and weekly education topics, and are encouraged to track weight, activity, and diet. Step two adds two weekly personalized chat messages with a lifestyle coach/registered dietitian and step three adds biweekly telephone sessions.

LEAP shows “that combining clinician engagement with patient‑facing digital tools can improve gestational weight outcomes in real‑world care settings,” Hedderson said.

In an accompanying editorial, Elizabeth Stevens, PhD, MPH, and Devin M. Mann, MD, MS, both of the New York University Grossman School of Medicine in New York City, noted that LEAP “demonstrates both the promise and the ceiling of the current digital behavioral health paradigm.”

While LEAP is both pragmatic and scalable, it highlights “the bottleneck that keeps evidence-based counseling from reaching everyone who could benefit, including the reliance on human coaches for personalized care,” they wrote. They proposed that generative artificial intelligence (AI) could further bolster these types of interventions by reducing the reliance on human labor, potentially eliminating barriers to scalability.

The trial was conducted at four Kaiser Permanente Northern California medical centers. Clinicians with at least five patients with overweight or obesity were randomized 1:1 to either standard care or the intervention. Patients were eligible if they were between 8 and 15 weeks’ gestation with a singleton pregnancy, at least 21 years old, spoke English, had a smartphone and WiFi, planned to deliver at one of the four centers, and had a body mass index (BMI) of 25 to less than 40.

The standard care group included 29 obstetric clinicians and 588 pregnant patients and the intervention group included 29 obstetric clinicians and 677 patients. Mean patient age was 33.4, and mean prepregnancy BMI was 29.8. Overall, 34% were white, 26.2% were Hispanic, 23.2% were Asian, 5.9% were Black, and 10.8% were other races and ethnicities.

Usual care involved standard prenatal care visits and a chat about healthy eating habits at the first visit.

About half of participants in the intervention group downloaded the app and less than 20% sustained high engagement throughout the intervention, which Stevens and Mann noted is a persistent problem in digital and behavioral health interventions.

An exploratory analysis showed that the intervention patients most adherent to self-weighing were estimated to have the largest improvements in GWG.

As for limitations, Hedderson and team noted that weight data from electronic health records may not be precise and that they relied on self-reported physical activity and diet assessments. In addition, enrolled patients were less likely to be Hispanic and more likely to be more educated than non-enrolled patients. The app was only offered in English due to resource constraints.

Hedderson said her team hopes to explore ways to increase engagement and examine longer‑term outcomes, like postpartum weight retention and child growth, in hopes of adapting the program for broader populations and settings.

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