A randomized controlled trial to evaluate "mami-educ", a mHealth intervention to reduce gestational obesity: Towards personalized prevention. (Preprint)

Abstract

The World Federation of Obesity (WOF) warns that the main health problem of the next decade will be childhood obesity. It is known that factors such as gestational obesity produce profound effects of fetal programming and is a strong predictor of overweight and obesity in children. Therefore, establishing healthy eating behaviors during pregnancy is key to the primary prevention of the intergenerational transmission of obesity. Mobile health programs (mHealth) are potentially more effective than face-to-face interventions, especially during a public health emergency such as the COVID-19 outbreak.

to evaluate the effectiveness of an mHealth intervention to reduce excessive weight gain in pregnant women who attend family health care centers.

The design of the intervention corresponds to a classic randomized clinical trial (RCT). The participants are pregnant women in the first trimester of pregnancy who live in urban and semi-urban areas. Before starting the intervention, a survey will be applied to identify the barriers and facilitators perceived by pregnant women to adopt healthy eating behaviors. The dietary intake will be estimated in the same way. The intervention will last 12 weeks and consists of sending messages through multimedia messaging service with food education, addressing the three domains of learning (cognitive, affective and psychomotor). Descriptive statistics will be used to analyze the demographic, socioeconomic, and obstetric characteristics of the respondents. The analysis strategy follows the intention-to-treat principle. Logistic regression analysis will be used to compare the intervention with routine care on maternal pregnancy outcome and perinatal outcome.

Recruitment of study participants began in June 2022 and is still ongoing. Until now, 40 participants have responded to the diagnostic survey, of which 21 were admitted to the intervention group and 19 as the control group. The expected timeframe for completing recruitment and data analysis is around November 2023.

We hope that the findings of this study will generate knowledge to design and implement personalized prevention strategies to reduce excessive gestational weight gain.

NCT05114174