Actigraphy, Blood Glucose Profile, Chronobiology, Circadian Rhythm, Continuous Glucose Monitoring, Diabetes, Gestational, Diet During Pregnancy, Gestational Diabetes Mellitus in Pregnancy, Glucose Intolerance During Pregnancy, Meal Time, Metabolic Diseases, Mobile Applications, Pilot Study, Pregnancy, Randomized Controlled Trial, Sleep, Wearable Electronic Devices
Conditions
Keywords
Risk factor, Lifestyle, Early pregnancy, Chrono-disruptive behaviours, Maternal health, Lifestyle intervention
Brief summary
The goal of this clinical trial is to examine how daily behavioral patterns in early pregnancy, including sleep, physical activity, and meal timing, influence continuous glucose dynamics and subsequent risk of gestational diabetes mellitus (GDM) in pregnant women without pre-existing diabetes. The main questions it aims to answer are: 1. Do early-pregnancy chronobehavioral patterns (e.g., irregular sleep, night eating, and unstable rest-activity rhythms) relate to continuous glucose patterns measured using continuous glucose monitoring (CGM)? 2. Can early behavioral and CGM-derived measures predict glucose regulation and metabolic outcomes later in pregnancy (24-28 weeks)? 3. Does real-time self-monitoring using wearable devices and food logging improve glycemic outcomes compared to usual care? This study is a prospective, nested randomized pilot trial embedded within the ongoing Towards Optimal Fertility, Fathering and Fatherhood studY (TOFFFY) cohort (NCT06293235) at KK Women's and Children's Hospital, Singapore. A total of 140 pregnant women without pre-existing diabetes, recruited at ≤13 weeks gestation, will be randomized in a 1:1 ratio to either a pilot arm (wearable-based self-monitoring) or a control arm (usual care). Participants in the pilot arm (n=70) will undergo intensive behavioral and metabolic monitoring over a 14-day period in early pregnancy, including continuous glucose monitoring using a CGM device, wrist actigraphy to assess sleep-wake and rest-activity patterns, and an AI-supported mobile application to record meal timing and dietary intake. Participants will have real-time access to their glucose data and behavioral feedback, enabling self-monitoring and potential behavioral adjustments.
Detailed description
Circadian disruption during pregnancy is increasingly recognized as an important, yet understudied, contributor to impaired glucose regulation and gestational diabetes mellitus (GDM). Emerging evidence suggests that nocturnal eating, irregular sleep timing, reduced rest-activity rhythm (RAR) stability, and greater behavioral variability may impair glucose homeostasis through pathways involving reduced insulin sensitivity, altered β-cell stress, and inflammation. Most studies assess chronobehaviors using questionnaires, which are limited by recall bias and poor temporal granularity. Recent technological advances enable high-resolution measurement of circadian and metabolic physiology using wrist actigraphy and continuous glucose monitor (CGM). These tools allow objective quantification of sleep timing, RAR, activity fragmentation, and 24-hour glycaemic patterns. Integrating these data in early pregnancy may enable earlier identification of at-risk women, allowing intervention before the onset of overt hyperglycaemia. The ongoing TOFFFY study (NCT 06293235) provides a unique opportunity to embed such a pilot study among well-phenotyped Singaporean pregnant women. Leveraging this cohort will support mechanistic insights into the interplay between circadian rhythms, meal timing, and glucose regulation, and provide preliminary data to power a larger mother-fetus chronometabolic project. Findings from this pilot will provide high-resolution insight into how early-pregnancy circadian, behavioral, and glycemic patterns interact to shape metabolic physiology. By capturing glucose responses such as glucose AUC, insulin resistance, and C-peptide, the study will identify early mechanistic pathways through which chronobehavioral disruption contributes to dysglycemia.
Interventions
DEVICEContinuous glucose monitor (CGM)
Participants will wear a continuous glucose monitor for 14 days in early pregnancy.
DEVICEWrist actigraphy device
A wrist actigraphy device will be used to assess sleep-wake patterns and physical activity over 14 days.
BEHAVIORALAI-based dietary and meal timing logging mobile application
Participants will record their dietary intake, meal timing logging, and feedback-based self-monitoring using an AI-based food logging mobile application.
Sponsors
KK Women's and Children's Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
SINGLE (Subject)
Eligibility
Sex/Gender
FEMALE
Age
21 Years to 39 Years
Healthy volunteers
Yes
Inclusion criteria
* Enrolled in the Towards Optimal Fertility, Fathering and Fatherhood studY (TOFFFY) (NCT06293235) * Females who are currently pregnant and with viable intrauterine pregnancy at ≤13 weeks gestation at enrolment
Exclusion criteria
* Females with pre-existing diabetes mellitus (Type 1 or Type 2) and/or chronic medical conditions affecting glucose metabolism * Females who are taking medications known to significantly affect glucose metabolism * Females with multiple pregnancy (e.g., twins or higher-order gestation) * Females who are unable to comply with study procedures, including: Inability to use smartphone-based applications and inability to wear wrist actigraphy device
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| 24-hour glucose area under the curve (AUC) | From enrollment in first trimester (≤13 weeks gestation), over 14 days | Continuous glucose monitor (CGM) will be used to assess 24-hour glucose exposure, expressed as area under the curve (AUC) (unit: mmol/L h). Higher AUC values indicate greater overall glucose exposure and poorer glycemic control. |
| Nocturnal glucose levels | From enrollment in first trimester (≤13 weeks gestation), over 14 days | CGM will be used to assess mean nocturnal glucose levels during the sleep period. The ideal nocturnal glucose range is 3.9-10mmol/L). Higher values indicate poorer nocturnal glycemic control. |
| Glycemic variability - standard deviation (SD) | From enrollment in first trimester (≤13 weeks gestation), over 14 days | CGM will be used to assess glycemic variability using the standard deviation (SD) of glucose values (unit: mmol/L), reflecting the dispersion from the average blood glucose level. Higher values indicate greater glycemic variability and poorer glycemic control. |
| Glycemic variability - coefficient of variation (CV) | From enrollment in first trimester (≤13 weeks gestation), over 14 days | CV is an accepted index for evaluating within-day glycemic variability, where CV = (SD) / (mean glucose) × 100%. Higher values indicate greater glycemic variability and poorer glycemic control. A CV of ≥36% is commonly used to define high glycemic variability. |
| Rest-activity rhythm (RAR) - intra-daily variability (IV) | From enrollment in first trimester (≤13 weeks gestation), over 14 days | Wrist actigraphy will be used to derive RAR by calculating the intra-daily variability (IV). IV reflects the degree of fragmentation in circadian activity patterns by assessing fluctuations in activity frequency and intensity within a given time period, capturing the extent of transitions between periods of rest and activity over time. IV values range from 0 to 1. Higher IV scores indicating poorer outcomes with greater disruption and fragmentation of the RAR. |
| Rest-activity rhythm (RAR) - inter-daily stability (IS) | From enrollment in first trimester (≤13 weeks gestation), over 14 days | Wrist actigraphy will be used to derive RAR by calculating the inter-daily variability (IS). IS reflects the stability of 24-hour circadian activity variations and the balance between RAR and the circadian cycle. IV values range from 0 to 1. IS values close to 1 indicating a better RAR outcome with greater rhythm stability. |
| Chrononutrition behavior - meal timing | From enrollment in first trimester (≤13 weeks gestation), over 14 days | AI-based food logging will be used to assess meal timing, defined as the timing of caloric intake, expressed as clock time of energy consumption. Later or more irregular intake timing indicates less favorable chrononutrition alignment. |
| Chrononutrition behavior - eating jetlag | From enrollment in first trimester (≤13 weeks gestation), over 14 days | AI-based food logging will be used to assess eating jetlag, defined as the difference in timing of the caloric midpoint between weekdays and weekends (unit: hours). Higher values indicate greater circadian misalignment in eating behavior. |
| Chrononutrition behavior - frequency of night-eating | From enrollment in first trimester (≤13 weeks gestation), over 14 days | AI-based food logging will be used to assess frequency of night-eating episodes, defined as the number of eating events occurring during the biological night or habitual sleep period. Higher night-eating frequency indicates poorer chrononutrition behavior. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Glucose tolerance status during pregnancy | From 24 weeks till 28 weeks of gestation | Glucose tolerance status will be assessed using a 75 g oral glucose tolerance test (OGTT), which reflects dynamic glucose response at 0, 60, and 120 minutes (unit: mmol/L). Higher values indicate poorer glucose tolerance. The glycemic outcomes will be compared between participants receiving the pilot intervention and those receiving usual care. |
| Total glycemic exposure during pregnancy | From 24 weeks till 28 weeks of gestation | Total glycemic exposure during the 75 g OGTT will be calculated as area under the glucose curve (unit: mmol/L h). Higher values indicate poorer glucose tolerance. The glycemic outcomes will be compared between participants receiving the pilot intervention and those receiving usual care. |
| Glycemic marker - fasting insulin | From 24 weeks till 28 weeks of gestation | Serum insulin concentration measured in blood (unit: pmol/L, SI unit) following the 75 g OGTT at 0, 60, and 120 minutes. Higher values indicate greater circulating insulin levels. The glycemic outcomes will be compared between participants receiving the pilot intervention and those receiving usual care. |
| Glycemic marker - C-peptide | From 24 weeks till 28 weeks of gestation | C-peptide concentration is assessed (unit: pmol/L, SI unit) following the 75 g OGTT at 0, 60, and 120 minutes. Higher values indicate increased endogenous insulin secretion. The glycemic outcomes will be compared between participants receiving the pilot intervention and those receiving usual care. |
| Maternal glycemic control index - Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) | From 24 weeks till 28 weeks of gestation | HOMA-IR is derived from fasting glucose and fasting insulin to measure insulin resistance. Higher values indicate more insulin is needed to maintain glucose levels. The glycemic outcomes will be compared between participants receiving the pilot intervention and those receiving usual care. |
| Glycemic control index - Homeostatic Model Assessment for Beta Cell Function (HOMA-β) | From 24 weeks till 28 weeks of gestation | HOMA-β is derived from fasting glucose and fasting insulin to assess the function of beta cells in the pancreas, which are responsible for producing insulin. Higher value indicates better beta-cell functionality, while a lower value suggests impaired beta-cell function, which can be a sign of insulin resistance or diabetes. The glycemic outcomes will be compared between participants receiving the pilot intervention and those receiving usual care. |
| Sleep timing | From enrollment in first trimester (≤13 weeks gestation), over 14 days | Wrist actigraphy will be used to assess sleep timing, including sleep onset time and wake time (unit: clock time, hh:mm). Later sleep timing indicates delayed circadian phase. Changes across the monitoring period will be evaluated to assess potential behavioral effects of real-time self-monitoring. |
| Physical activity level | From enrollment in first trimester (≤13 weeks gestation), over 14 days | Wrist actigraphy will be used to assess physical activity pattern based on daily step counts. Higher values indicate greater physical activity levels. Changes across the monitoring period will be evaluated to assess potential behavioral effects of real-time self-monitoring. |
Countries
Singapore
Contacts
CONTACTBenjarat Oh
PRINCIPAL_INVESTIGATORSee Ling Loy
KK Women's and Children's Hospital
Outcome results
None listed