Background: Women with a history of gestational diabetes mellitus (GDM) are at an increased risk of developing type 2 diabetes mellitus (T2DM). Lifestyle interventions aimed at postpartum weight loss to reduce T2DM risk have been reported, but poor compliance remains a barrier. Smartphone-based interventions may improve compliance, but data on its use in women with recent GDM are limited.
Objective: This trial aimed to investigate the efficacy of a smartphone app in restoring optimal weight following delivery in women with GDM, in the setting of a population with high rates of GDM and type 2 diabetes.
Methods: In this unblinded randomized controlled trial, 200 women with GDM were randomized to receive the intervention or standard care following delivery. The intervention enabled logging of weight, meals, and activity, with web-based interaction with a team comprising dieticians, a physiotherapist, and an occupational therapist. The primary outcome was an achievement of optimal weight (defined as the restoration of first trimester weight if first trimester BMI≤23 kg/m or weight loss of at least 5% from first trimester weight if first trimester BMI>23 kg/m) at 4 months post partum. Secondary outcome measures included absolute weight loss, serum metabolic markers, self-reported nutritional intake, health education, and quality of life via questionnaires and user engagement in the intervention group.
Results: In total, 40% (38/96) of women in the intervention group achieved optimal weight at 4 months post delivery compared with 32% (28/93) in the control group (P=.27). Compared with the control group, women in the intervention group reported significantly reduced caloric intake at 4 months after delivery (P<.001) and higher health-directed behavior scores (P=.045). The intervention group also reported increased emotional distress scores (P=.01). At 4 months, participant engagement with the intervention was maintained at 60.8% (SD 33.9%).
Conclusions: Although a statistically significant increase in women achieving healthy weight was not observed, this app remains promising, as women in the intervention group reported improved health behaviors and lower caloric intake. Importantly, the high retention rates suggest that a larger study with a longer follow-up period might confirm the effectiveness of this app for weight management.
Trial Registration: ClinicalTrials.gov NCT03324737; https://clinicaltrials.gov/ct2/show/NCT03324737.
International Registered Report Identifier (irrid): RR2-10.1186/s12889-019-7691-3.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088857 | PMC |
http://dx.doi.org/10.2196/22147 | DOI Listing |
J Health Popul Nutr
January 2025
Department of Gastroenterology and Hepatology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, No. 55 Zhenhai Road, Xiamen, 361003, China.
Purpose: Evidence concerning the effect of cardiovascular health (CVH) on the risk of metabolic dysfunctional-associated steatotic liver disease (MASLD) is scarce. This study aimed to investigate the association between CVH and MASLD.
Methods: 5680 adults aged ≥ 20 years from the National Health and Nutrition Examination Survey 2017-March 2020 were included.
J Transl Med
January 2025
Department of Medical Oncology, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, University of Science and Technology of China, Anhui Provincial Cancer Hospital, Hefei, 230031, Anhui, China.
Background: Agonistic monoclonal antibodies targeting 4-1BB/CD137 have shown preclinical promise, but their clinical development has been limited by severe liver toxicity or limited efficacy. Therefore, a safe and efficient immunostimulatory molecule is urgently needed for cancer immunotherapy.
Methods: A novel anti-MSLN×4-1BB bispecific antibody (bsAb) was generated via antibody engineering, and its affinity and activity were detected via enzyme-linked immunosorbent assay (ELISA), flow cytometry, and T-cell activation and luciferase reporter assays.
BMC Med Imaging
January 2025
Department of Magnetic Resonance Imaging, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, 450052, China.
Background: Conventional hip joint MRI scans necessitate lengthy scan durations, posing challenges for patient comfort and clinical efficiency. Previously, accelerated imaging techniques were constrained by a trade-off between noise and resolution. Leveraging deep learning-based reconstruction (DLR) holds the potential to mitigate scan time without compromising image quality.
View Article and Find Full Text PDFObes Surg
January 2025
Hamad Medical Corporation, Doha, Qatar.
Background: Acute pancreatitis (AP) is a rare but serious complication of intragastric balloon (IGB) therapy. Despite the popularity of IGBs for weight loss, the incidence and risk factors of AP post-IGB insertion are not well understood. This study aimed to identify potential predictors and risk factors of AP in IGB patients.
View Article and Find Full Text PDFEnvironmental degradation due to the rapid increase in CO₂ emissions is a pressing global challenge, necessitating innovative solutions for accurate prediction and policy development. Machine learning (ML) techniques offer a robust approach to modeling complex relationships between various factors influencing emissions. Furthermore, ML models can learn and interpret the significance of each factor's contribution to the rise of CO.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!