A Dynamical Systems Model for Improving Gestational Weight Gain Behavioral Interventions

Abstract

Excessive gestational weight gain (GWG) represents a major public health concern. In this paper, we present a dynamical systems model that describes how a behavioral intervention can influence weight gain during pregnancy. The model relies on the integration of a mechanistic energy balance with a dynamical behavioral model. The behavioral model incorporates some well-accepted concepts from psychology: the Theory of Planned Behavior (TPB) and the principle of self-regulation which describes how internal processes within the individual can serve to reinforce the positive outcomes of an intervention. A hypothetical case study is presented to illustrate the basic workings of the model and demonstrate how the proper design of the intervention can counteract natural trends towards declines in healthy eating and reduced physical activity during the course of pregnancy. The model can be used by behavioral scientists to evaluate decision rules for adaptive time-varying behavioral interventions, or as the open-loop model for hybrid model predictive control algorithms acting as decision frameworks for such interventions.

Fig. 1

Overall schematic representation for an adaptive gestational weight gain (GWG) intervention.

Fig. 2

Path diagram for the TPB, obtained from Structural Equation Modeling [13].

Fig. 3

Fluid Analogy for the TPB.

Fig. 4

Behavior and perception as elements of a feedback loop guiding human action per the self-regulation theory of Carver and Scheier [17].

Fig. 5

Deterministic disturbance signals for behavior inflow ζ₅ in the EI-TPB (left) and PA-TPB (right) models.

Fig. 6

Simulation responses for the energy intake behavior (EI-TPB) and physical activity behavior (PA-TPB) models (top two) and maternal energy balance (bottom). Red lines represent the 2009 IOM guidelines applied on a daily basis; the blue dashed line represent the case with no intervention (self-regulation only) while the black solid line represents the case with the intervention. The brown dashdot line in the TPB model variables (top two) shows the simulation responses in these variables for no self-regulation.