TY - JOUR
T1 - Protocol for an interventional study to reduce postpartum weight retention in obese mothers using the internet of things and a mobile application
T2 - a randomized controlled trial (SpringMom)
AU - Kawasaki, Maki
AU - Mito, Asako
AU - Waguri, Masako
AU - Sato, Yuichi
AU - Abe, Emiko
AU - Shimada, Mayumi
AU - Fukuda, Sayuri
AU - Sasaki, Yuki
AU - Fujikawa, Kei
AU - Sugiyama, Takashi
AU - Ota, Erika
AU - Nakazawa, Jin
AU - Okoshi, Tadashi
AU - Takimoto, Hidemi
AU - Honda, Yuka
AU - Inoue, Eisuke
AU - Hiramatsu, Yuji
AU - Arata, Naoko
N1 - Funding Information:
This work is supported by AMED (project code 20le0110014h0002) to Naoko Arata. The study protocol underwent peer review by the funding body. The funding body will have no role in the design of this study, data collection, data analysis, interpretation of result, or writing the manuscript.
Funding Information:
The authors thank Dr. Toru Kobayashi and Mr. Kenji Takehara, National Center for Child Health and Development, for advice regarding the study design. The authors thank Ms. Sie Saito and Ms. Yoko Kawachi, National Center for Child Health and Development, for helping with the study. The authors thank Editage (https://www.editage.com/) for English language review. The authors thank Mr. Shun Coney, Doctor Course, Japan Advanced Institute of Science and Technology Lecturer, Digital Hollywood University for creating the manga comics.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - Background: Obese pregnant women are known to experience poorer pregnancy outcomes and are at higher risk of postnatal arteriosclerosis. Hence, weight control during and after pregnancy is important for reducing these risks. The objective of our planned randomized controlled trial is to evaluate whether the rate of change in body weight in obese women before pregnancy to 12 months postpartum would be lower with the use of an intervention consisting of Internet of Things (IoT) devices and mobile applications during pregnancy to 1 year postpartum compared to a non-intervention group. Methods: Women will be recruited during outpatient maternity checkups at four perinatal care institutions in Japan. We will recruit women at less than 30 weeks of gestation with a pre-pregnancy body mass index ≥ 25 kg/m2. The women will be randomly assigned to an intervention or non-intervention group. The intervention will involve using data (weight, body composition, activity, sleep) measured with IoT devices (weight and body composition monitor, activity, and sleep tracker), meal records, and photographs acquired using a mobile application to automatically generate advice, alongside the use of a mobile application to provide articles and videos related to obesity and pregnancy. The primary outcome will be the ratio of change in body weight (%) from pre-pregnancy to 12 months postpartum compared to before pregnancy. Discussion: This study will examine whether behavioral changes occurring during pregnancy, a period that provides a good opportunity to reexamine one's habits, lead to lifestyle improvements during the busy postpartum period. We aim to determine whether a lifestyle intervention that is initiated during pregnancy can suppress weight gain during pregnancy and encourage weight loss after delivery. Trial registration: UMIN: UMIN (University hospital Medical Information Network) 000,041,460. Resisted on 18th August 2020. https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047278.
AB - Background: Obese pregnant women are known to experience poorer pregnancy outcomes and are at higher risk of postnatal arteriosclerosis. Hence, weight control during and after pregnancy is important for reducing these risks. The objective of our planned randomized controlled trial is to evaluate whether the rate of change in body weight in obese women before pregnancy to 12 months postpartum would be lower with the use of an intervention consisting of Internet of Things (IoT) devices and mobile applications during pregnancy to 1 year postpartum compared to a non-intervention group. Methods: Women will be recruited during outpatient maternity checkups at four perinatal care institutions in Japan. We will recruit women at less than 30 weeks of gestation with a pre-pregnancy body mass index ≥ 25 kg/m2. The women will be randomly assigned to an intervention or non-intervention group. The intervention will involve using data (weight, body composition, activity, sleep) measured with IoT devices (weight and body composition monitor, activity, and sleep tracker), meal records, and photographs acquired using a mobile application to automatically generate advice, alongside the use of a mobile application to provide articles and videos related to obesity and pregnancy. The primary outcome will be the ratio of change in body weight (%) from pre-pregnancy to 12 months postpartum compared to before pregnancy. Discussion: This study will examine whether behavioral changes occurring during pregnancy, a period that provides a good opportunity to reexamine one's habits, lead to lifestyle improvements during the busy postpartum period. We aim to determine whether a lifestyle intervention that is initiated during pregnancy can suppress weight gain during pregnancy and encourage weight loss after delivery. Trial registration: UMIN: UMIN (University hospital Medical Information Network) 000,041,460. Resisted on 18th August 2020. https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000047278.
KW - Internet of Things
KW - Mobile phone
KW - Obesity
KW - Pregnancy
KW - Weight
UR - http://www.scopus.com/inward/record.url?scp=85113742020&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85113742020&partnerID=8YFLogxK
U2 - 10.1186/s12884-021-03998-w
DO - 10.1186/s12884-021-03998-w
M3 - Article
C2 - 34425784
AN - SCOPUS:85113742020
SN - 1471-2393
VL - 21
JO - BMC Pregnancy and Childbirth
JF - BMC Pregnancy and Childbirth
IS - 1
M1 - 582
ER -
