Effectiveness of the Internet of Things for improving pregnancy and postpartum women's health in high-income countries: A systematic review and meta-analysis (Preprint)
Authors: Nishimura Etsuko , Yamaji Noyuri , Sasayama Kiriko , Rahman Md. Obaidur , Lopes Katharina da Silva , Mamahit Citra Gabriella , Ninohei Mika , Tun Phyu Phyu , Shoki Rina , Suzuki Daichi , Nitamizu Aya , Yoneoka Daisuke , Saito Eiko , Ota Erika 
Published: September 2024

BACKGROUND

In high-income countries, numerous health issues faced by women during pregnancy and the postpartum period are linked to everyday lifestyle habits such as diet, exercise, and sleep. To enhance women's lifestyle behaviors and health management, there has been an increasing integration of the Internet of Things (IoT) with application software. IoT has been widely used to monitor specific health indicators, including physical activity, sleep patterns, and heart rate, in pregnant and postpartum women. However, there are few reviews evaluating the effectiveness of IoT in improving health outcomes in women during pregnancy and the postpartum period.

OBJECTIVE

The objective of this systematic review and meta-analysis was to evaluate and synthesize the role of IoT in enhancing the health outcomes of pregnant and postpartum women.

METHODS

A systematic search was conducted on February 13, 2023, across CENTRAL, CINAHL, ClinicalTrials.gov, Embase, MEDLINE, PsycINFO, PubMed, and WHO ICTRP to identify all randomized controlled trials. The studies included pregnant or postpartum women in high-income countries and interventions involving the application of data collection and monitoring using sensors in smartphones and wearable devices. Two reviewers independently selected the studies, extracted data, and assessed the risk of bias. The Cochrane Collaboration's risk of bias assessment tool 2.0 was used to evaluate the risk of bias. We performed a pairwise meta-analysis using a fixed effects model when the between-study heterogeneity was low. The Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach was employed to assess the certainty of evidence. The findings were reported according to the preferred reporting items for systematic review and meta-analysis (PRISMA) guidelines.

RESULTS

Eight studies, comprising a total of 2,028 pregnant and postpartum women, were included in this review. Of the eight included studies, half targeted women with gestational diabetes and the other half targeted obese women. A meta-analysis revealed that IoT interventions may limit gestational weight gain in women with obesity. The intervention groups showed 3.27 kg less weight gain during pregnancy than the control groups (mean difference [MD], -3.27; 95% confidence interval [CI], -4.76– -1.79; I² = 36%; two studies; 242 women; moderate certainty of evidence). Body fat percentage in postpartum women was 0.35% lower in the intervention than in the control groups (MD, -0.35; 95% CI, -0.62– -0.07; I² = 53%; three studies; 1511 women; low certainty of evidence).

CONCLUSIONS

This review suggested that IoT interventions may limit gestational weight gain in pregnant women with obesity and reduce postpartum body fat in women with weight issues or gestational diabetes. Future studies should evaluate maternal and newborn health outcomes with IoT interventions.

CLINICALTRIAL

PROSPERO (register number: CRD42022384620)

INTERNATIONAL REGISTERED REPORT

RR2-10.2196/45178