Early Pregnancy Lifestyle and Glucose Patterns: A Substudy of TOFFFY

Early-Pregnancy Chronobehavioural Profiles and Continuous Glucose Dynamics: A Nested Randomised Pilot Study of TOFFFY

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.

Study Overview

• Status: Not yet recruiting
• Conditions: Metabolic Diseases; Sleep; Pregnancy; Mobile Applications; Circadian Rhythm; Diabetes, Gestational; Randomized Controlled Trial; Gestational Diabetes Mellitus in Pregnancy; Glucose Intolerance During Pregnancy; Continuous Glucose Monitoring; Pilot Study; Actigraphy; Wearable Electronic Devices; Chronobiology; Meal Time; Blood Glucose Profile; Diet During Pregnancy
• Intervention / Treatment: Device: Continuous glucose monitor (CGM); Device: Wrist actigraphy device; Behavioral: AI-based dietary and meal timing logging mobile application

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.

• Study Type: Interventional
• Enrollment (Estimated): 140
• Phase: Not Applicable

Contacts and Locations

• Study Contact: Name: Benjarat Oh; Phone Number: 65 +6563948105; Email: benjarat.oh@kkh.com.sg

Study Locations

• Singapore
  • Singapore
    • Singapore, Singapore, Singapore, 229899
      • KK Women's and Children's Hospital
      • Contact: Benjarat Oh; Phone Number: 65 +6563948105; Email: benjarat.oh@kkh.com.sg
      • Principal Investigator: See Ling Loy

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: Yes

Description

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

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Prevention
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Single

Number of Arms

2

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
Experimental: Pilot arm; Participants in this arm (n=70) will undergo a 14-day monitoring period in early pregnancy (≤13 weeks gestation). Participants will have real-time access to their glucose data and food logging feedback, enabling self-monitoring and potential behavioural adjustments. Participants will also continue to receive routine antenatal care and standard clinical assessments.	Device: Continuous glucose monitor (CGM); Participants will wear a continuous glucose monitor for 14 days in early pregnancy.; Device: Wrist actigraphy device; A wrist actigraphy device will be used to assess sleep-wake patterns and physical activity over 14 days.; Behavioral: AI-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.
No Intervention: Control Arm; Participants (n=70) receive routine antenatal care only, with no additional devices, monitoring, or feedback introduced by the study.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Nocturnal glucose levels	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Glycemic variability - standard deviation (SD)	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Glycemic variability - coefficient of variation (CV)	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Rest-activity rhythm (RAR) - intra-daily variability (IV)	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Rest-activity rhythm (RAR) - inter-daily stability (IS)	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Chrononutrition behavior - meal timing	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Chrononutrition behavior - eating jetlag	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Chrononutrition behavior - frequency of night-eating	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
24-hour glucose area under the curve (AUC)	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Glucose tolerance status during pregnancy	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.	From 24 weeks till 28 weeks of gestation
Total glycemic exposure during pregnancy	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.	From 24 weeks till 28 weeks of gestation
Glycemic marker - fasting insulin	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.	From 24 weeks till 28 weeks of gestation
Glycemic marker - C-peptide	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.	From 24 weeks till 28 weeks of gestation
Maternal glycemic control index - Homeostatic Model Assessment for Insulin Resistance (HOMA-IR)	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.	From 24 weeks till 28 weeks of gestation
Glycemic control index - Homeostatic Model Assessment for Beta Cell Function (HOMA-β)	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.	From 24 weeks till 28 weeks of gestation
Sleep timing	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days
Physical activity level	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.	From enrollment in first trimester (≤13 weeks gestation), over 14 days

Collaborators and Investigators

• Sponsor: KK Women's and Children's Hospital
• Investigators: Principal Investigator: See Ling Loy, KK Women's and Children's Hospital

Study record dates

Study Major Dates

• Study Start (Estimated): May 1, 2026
• Primary Completion (Estimated): April 30, 2027
• Study Completion (Estimated): June 30, 2027

Study Registration Dates

• First Submitted: April 6, 2026
• First Submitted That Met QC Criteria: April 14, 2026
• First Posted (Actual): April 16, 2026

Study Record Updates

• Last Update Posted (Actual): April 27, 2026
• Last Update Submitted That Met QC Criteria: April 22, 2026
• Last Verified: April 1, 2026

More Information

Terms related to this study

• Keywords: Lifestyle intervention; Lifestyle; Maternal health; Risk factor; Early pregnancy; Chrono-disruptive behaviours
• Additional Relevant MeSH Terms: Urogenital Diseases; Endocrine System Diseases; Female Urogenital Diseases and Pregnancy Complications; Pregnancy Complications; Glucose Metabolism Disorders; Diabetes Mellitus; Nutritional and Metabolic Diseases; Diabetes, Gestational; Metabolic Diseases
• Other Study ID Numbers: 2024/2120

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Individual participant data will not be shared due to ethical and privacy considerations, as the dataset contains sensitive health and behavioural information that could potentially allow participant re-identification.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No