Effectiveness of E‐Health Interventions on Improving Physical Activity in Pregnant Women: A Systematic Review and Meta‐Analysis

ABSTRACT

Aims

This study aimed to (1) evaluate the effectiveness of e-health interventions in improving physical activity and associated health outcomes during pregnancy, (2) compare the e-health functions employed across interventions and (3) systematically identify the behaviour change techniques (BCTs) used and examine their interrelationships.

Design

A systematic review and meta-analysis following the PRISMA 2020 guidelines.

Methods

Randomised controlled trials were included. Meta-analyses and subgroup analyses were performed using RevMan 5.3. Social network analysis was conducted to determine the most central BCTs within the intervention landscape.

Data Sources

Ten databases were searched, including PubMed, Embase, Web of Science, Cochrane Library, ProQuest, Scopus, SinoMed, China National Knowledge Infrastructure, WanFang and the China Science and Technology Journal Database, from inception to April 22, 2024.

Results

Thirty-five studies were included. Pooled analyses indicated that e-health interventions significantly improved both total (SMD: 0.19; 95% CI: 0.10 to 0.27; I ² = 55%) and moderate-to-vigorous physical activity (SMD: 0.16, 95% CI: 0.06 to 0.26; I ² = 53%) in pregnant women. Subgroup analyses revealed that interventions based on theoretical frameworks and those not specifically targeting overweight or obese women demonstrated greater effectiveness. Additionally, e-health interventions were associated with significant reductions in both total and weekly gestational weight gain. Six of the twelve e-health functions were utilised, with ‘client education and behaviour change communication’ being the most prevalent. Thirty unique BCTs were identified; among them, ‘instruction on how to perform the behaviour’, ‘self-monitoring’, ‘problem solving’, and ‘goal setting’ showed the highest degree of interconnectedness.

Conclusion

E-health interventions are effective in enhancing physical activity and reducing gestational weight gain during pregnancy. Incorporating theoretical frameworks and well-integrated BCTs is recommended to optimise intervention outcomes.

Relevant to the Clinical Practice

Integrating e-health interventions into existing perinatal care models holds promise for enhancing physical activity among pregnant women and improving maternal health outcomes.

Reporting Method

This study adhered to the PRISMA checklist.

Patient or Public Contribution

No patient or public involvement.

Trial Registration

The study protocol was preregistered in the International Prospective Register of Systematic Reviews (CRD42024518740)

Multi-omics analysis reveals diagnostic and therapeutic biomarkers for aging phenotypes in ulcerative colitis

by Lei Guo, Jun Ge, Li Cheng, Xinyi Zhang, Zhengzheng Wu, Meili Liu, Hanmei Jiang, Wei Gong, Yi Liu

The incidence of ulcerative colitis (UC) remains high, with an increasing prevalence among elderly patients. Cellular senescence has been widely recognized as a contributor to UC susceptibility; however, the underlying molecular mechanisms remain incompletely understood. This study aimed to identify senescence-associated biomarkers in UC to provide new insight for diagnosis and treatment.

By integrating transcriptomic data from UC patients with established aging-related databases, we identified aging-associated differentially expressed genes (DEGs). Using weighted gene co-expression network analysis (WGCNA) and Cytoscape, we pinpointed the core genes involved. A diagnostic model for UC was then developed based on these core genes, and their expression patterns were characterized at single-cell resolution. The roles of these genes were ultimately validated through in vitro and animal experiments.

We identified 24 aging-related DEGs in UC, which were primarily implicated in inflammatory responses and cytokine-receptor interactions. Further analyses pinpointed three core genes (CXCL1, MMP9, and STAT1) that were predominantly expressed in macrophages. A diagnostic model constructed using these genes exhibited robust predictive performance. Experimental validation confirmed that the expression levels of all three core genes were significantly upregulated in both a UC mouse model and in macrophages compared to controls. Additionally, pathway analyses revealed elevated levels of CXCL12 and VEGFA in the enriched pathways.

Our findings underscore the pivotal roles of CXCL1, MMP9, and STAT1 in UC-associated cellular senescence. The analysis positions these molecules as promising macrophage-mediated diagnostic biomarkers and therapeutic targets. Collectively, this work provides novel insights into UC pathogenesis and lays a foundation for developing precision medicine strategies that target senescence pathways.