Effectiveness of a nurse‐led mHealth app to prevent excessive gestational weight gain among overweight and obese women: A randomized controlled trial

Abstract

Objective: To explore the effectiveness of a nurse-led mobile health (mHealth) intervention to prevent excessive gestational weight gain (GWG) in overweight and obese women.Methods: A randomized controlled trial with an experimental study design. Ninetytwo pregnant women with body mass index (BMI) ≥25 kg/m 2 at less than 17 weeks gestation were recruited from two prenatal clinics in northern Taiwan from January to June 2020. The experimental group used the MyHealthyWeight (MHW) app and a wearable activity tracker (WAT), and the controls received standard antenatal treatments with no mHealth-based elements. Two hospital follow-up visits were scheduled at 24-26 weeks in the second trimester and 34-36 weeks in the third trimester.A generalized estimating equation (GEE) was used to examine the trajectories and the effectiveness of mHealth on GWG.Results: No difference in GWG was found between the intervention and control groups at baseline (p > 0.05). The GWG trajectory in the entire cohort of women with obesity exhibited a quadratic pattern (ß = 1.8, 95% confidence interval [CI] = 1.27-2.32), and intervention participants' weekly GWG was gained significantly lower than their controls in the second trimester (p < 0.05). Throughout the pregnancy, the mHealth intervention group had a significantly lower proportion of individuals who exceeded their GWG in both total (21.6% vs. 32.6%) and weekly weight gain (first trimester = 58.7% vs. 65.2%; second trimester = 45% vs. 67.4%; third trimester = 48.6% vs. 55.1%). In particular, among obese women in the third trimester, those in the intervention group gained less gestational weight than their controls. The adjusted body weight difference was 5.44 kg (p = 0.023), signifying the total GWG difference (3.30 vs. 8.74 kg) between the means of the two groups. The GEE model indicated that obese women who were aged 35 years, had prepregnancy exercise habits, perceived self-efficacy of diet, and more physical activity tended to have low GWG (p < 0.05). Conclusions:The nurse-led mHealth-based intervention shows promising results in significantly preventing excessive GWG among high-BMI women. More effectiveness was found among the obese subgroup.

How Wearable Sensors Can Support the Research on Foetal and Pregnancy Outcomes: A Scoping Review

“…Twenty-one studies described the application of wearable sensors to collect information about maternal parameters and activities during pregnancy [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. These studies are described in Table 2 , together with a summary of the design and population, wearable device used, and main findings.…”

“…No significant changes were evident for glucose tolerance testing [ 25 ]. With a similar purpose, Chen and colleagues focused on the effects on gestational weight gain [ 23 ], which seriously affects other pregnancy and neonatal outcomes [ 42 , 43 ]. Their intervention consisted of using a wearable activity tracker and a mobile-health app among overweight and obese women [ 23 ].…”

“…With a similar purpose, Chen and colleagues focused on the effects on gestational weight gain [ 23 ], which seriously affects other pregnancy and neonatal outcomes [ 42 , 43 ]. Their intervention consisted of using a wearable activity tracker and a mobile-health app among overweight and obese women [ 23 ]. The authors showed a significant lower proportion of women who exceeded their GWG in the intervention group, with the greatest effect observed during the second trimester [ 23 ].…”

“…Their intervention consisted of using a wearable activity tracker and a mobile-health app among overweight and obese women [ 23 ]. The authors showed a significant lower proportion of women who exceeded their GWG in the intervention group, with the greatest effect observed during the second trimester [ 23 ].…”

“…For the second domain of application, selected studies reported on wearable devices used to collect maternal parameters and activities during pregnancy, and to investigate their association with maternal and neonatal health [ 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 ]. Devices used were varied, including wristband and finger-based trackers, body-conforming flexible sensors, and more complex systems made of different sensors.…”