PROJECT SUMMARY
Pregnant women with overweight/obesity (PW-OW/OB) and high gestational weight gain (GWG) are at increased
risk for adverse maternal-infant outcomes. Given this high risk and the rapidly changing landscape of healthcare
delivery due to the COVID-19 pandemic, there is a timely need for automated, scalable approaches relying on
remote delivery to regulate GWG. Our team addressed this need and developed the Healthy Mom Zone (HMZ)
intervention with adapted dosages to regulate GWG. Adaptations give less treatment (e.g., education) to women
who can self-regulate GWG within recommendations and more treatment (physical activity/energy intake
activities) to women who need more support to regulate GWG. Theory-based components were designed with a
multiphase, translational science framework and control systems methodology with the long-term goal to scale-
up future use by prenatal clinicians. With R01HL119245, we randomized PW-OW/OB to intervention and control
groups and examined feasibility and initial impact of HMZ on GWG. A control system driven by decision rules
and a woman’s observed GWG informed when to adapt dosages (GWG within goals, dosage was maintained;
GWG above goals, dosage was adapted). Trial feasibility markers showed high compliance, low subject burden
and attrition; compliance was better with remove vs. in-person delivery. The HMZ group had 21% lower mean
GWG and were more likely to have GWG within goals than controls. Exploratory analyses also showed promise
for HMZ to impact secondary maternal-infant outcomes. Given these initial findings, we made refinements to
increase efficacy and scalability (e.g., added sleep/eating behavior content, modified all components for remote
delivery). We replaced the initial control system with a new automated, model-based predictive control system
that forecasts a woman’s future GWG under different possible values of activity/intake behaviors and
determinants. We found that it made more efficient decisions to adapt dosages and regulated GWG better than
the initial system. With a Penn State seed grant, we built an architecture for a novel digital platform with a web
interface that automates the linkage of subject data to the new control system, computes optimized dosage
changes across multiple maternal variables, and produces a host of behavior strategies to regulate GWG. The
goal of the proposed research is to examine efficacy of the enhanced HMZ 2.0 intervention with new control
system/digital platform to regulate GWG and impact maternal-infant outcomes while collecting implementation
data to inform future scalability. N=144 PW-OW/OB will be randomized to HMZ 2.0 intervention or attention
control groups from ~8-36 weeks gestation. Aim 1 will examine efficacy of HMZ 2.0 on GWG (primary outcome)
and activity/intake behaviors and social cognitive determinants between intervention and control groups. Aim 2
will measure pre- to post-intervention differences in secondary maternal sleep/eating behaviors and infant birth
weight. Aim 3 will examine impact of implementation markers on HMZ 2.0 efficacy on study outcomes to inform
future scalability. Impact of this novel research is an optimized and highly scalable intervention to regulate GWG.