fitbit device use in overweight pregnancy

Conditions: Pregnancy Weight Gain; Overweight and Obesity

Summary: there are set guidelines for weight gain developed by the institute of medicine in pregnancy but about three quarters of women gain an inappropriate weight during pregnancy. many studies have assessed ways to decrease weight gain in these women who gain excess weight, usually through a combination of diet and exercise. still, often these interventions are difficult to implement, expensive, or have low acceptability. wearable fitbit devices have been on the market for years and slowly becoming more inexpensive and easier to use. previous studies on non-pregnant women have shown that using the device can help reduce weight gain. in addition, small studies in pregnant women have shown they are accurate for measuring steps and have high acceptability and retention rates. the ability of the fitbit to assess metrics of sleep including sleep duration and quality will also be assessed. this project aims to provide overweight and obese pregnant women at the beginning of their pregnancy with the fitbit device and with regular follow-up to assess if there is effectiveness in increasing the rate of women who meet weight gain guidelines compared to women without the device along with measuring aspects of sleep.

this is a prospective randomized control trial study. this study aims to assess the relationship between physical activity and sleep metrics in pregnant women as measured using the fitbit device and the ability to meet institute of medicine weight gain guidelines during pregnancy. the hypothesis of the study is that self-realization and monitoring of activity using the fitbit will encourage the wearer to be increasingly physically active and assist in meeting weight gain guidelines. this study is performed in conjunction with the university of arizona sensor lab utilizing the mydatahelps platform which will assist with collection of data from each participant's fitbit device and subsequent analysis. mydatahelps is an easily customizable data collection platform that helps researchers collect participant data in a secure hipaa compliant manner. they are an external company but have no input in the construction of the project this study will have two arms: one with fitbit wearers and a control arm for routine prenatal care. compared to control participants who will not have a fitbit device, we hypothesize that utilization of the fitbit device will be effective in helping overweight and obese pregnant women meet institute of medicine weight gain guidelines. the primary endpoint is gestational weight gain throughout pregnancy. weight will be measured pre-pregnancy, at recruitment, 28 weeks, delivery, and 6 weeks postpartum. secondary endpoints will also be measured and include: 1. acceptability of device and loss to follow-up 2. obstetrical outcomes include rate of developing gestational diabetes, gestational hypertension and preeclampsia, preterm delivery, cesarean delivery rate, intrauterine growth restriction, and macrosomia 3. neonatal outcomes, including birth weight and admission to nicu 4. fitbit outcome data, including steps taken, calories burned, sleep duration and fitbit derived sleep quality 5. questionnaire data: global physical activity questionnaire (gpaq), cambridge worry scale and pittsburgh sleep quality index at baseline, 28 weeks and delivery

Eligibility criteria:
inclusion criteria: * at least 18 years old * currently pregnant with a singleton pregnancy * pre-pregnancy body mass index over 25 * owns and uses a smartphone * agreeable to participate in the study by wearing a fitbit device consistently (day and night) for the duration of pregnancy exclusion criteria: * multiple gestations * beyond the first trimester at time of initial enrollment * known maternal cardiac disease * pre-gestational diabetes * high risk of preterm labor * any contraindications to exercise * unwilling to wear device consistently or share tracked data

Keywords: pregnancy overweight or obese physical activity sleep in pregnancy