Diabetes In Asians at Risk in Youth (DIARY)

Diabetes in Asians at Risk in Youth

This observational study aims to develop novel contemporary risk factor tools for detecting young onset diabetes (under 40y) in young Asians in Singapore. The investigators aim to recruit 3000 people not currently known to have diabetes, selected across age and Body Mass Index categories, and perform formal diagnostic tests for diabetes (oral glucose tolerance test and HbA1c). The participants will also undergo continuous glucose monitoring sensor, keep a food diary, and undergo body composition analysis using bioimpedance analysis, handgrip measurements for muscle strength, and sociobehavioural profiling through download of a curated list of social media interactions. The participants will also have a blood sample retrieved and stored for subsequent comparison between people with normal glucose versus abnormal glucose levels. The whole group will also have another blood sample stored for whole gene analysis.

Study Overview

• Status: Not yet recruiting
• Conditions: Young Onset Asian Diabetes (Under 40 Years)
• Intervention / Treatment: Diagnostic test: Oral glucose tolerance test and HbA1c; Other: Anthropometric measurements; Diagnostic test: Body impedance Analysis; Diagnostic test: Handgrip measurement; Diagnostic test: Continuous glucose monitoring; Other: Food diary recording over days 2 and 3 of continuous glucose monitoring; Other: Survey; Other: Skin reaction information; Other: Download of social media data; Diagnostic test: Whole genome sequencing

Detailed Description

Overarching aim: To improve the case detection rate of T2D in young Singaporeans adults aged 21-40y.

Specific Aim 1: To conduct a case-finding study for T2D and prediabetes through age- and BMI-stratified sampling in a contemporary population of young Singaporean adults aged 21-40y.

Specific Aim 2: To identify novel risk factors and develop a composite score to improve the detection rate for Asian YOD and prediabetes. These include non-traditional predictors such as glucometrics from continuous glucose monitoring (CGM), body composition measures, and socio-behavioural analyses.

Specific Aim 3: To identify the contribution of genomic differences to the risk of Asian Young Onset Diabetes

To fulfil Aim 1 within the first 1 to 2 years, the investigators plan to perform island-wide screening for diabetes or prediabetes amongst people aged 21-40y (n=3000). Recruitment will be stratified firstly by age categories (21-25y, 25-30y, 30-35y, 35-40y), aiming for n=750 per age category, followed by BMI categories of normal, overweight or obese by Asian thresholds (<23kgm2, 23-27.5kg/m2 and >=27.5kg/m2) within each age group. Participants will be recruited through online and print media including social media advertisements, word of mouth and /or referrals. A study poster advert will be posted online and in print, which will then direct participants to a webpage www.thdiary.sg which will explain the study design further and eligibility requirements and additional study details. The partiipants can proceed to register themselves via FORMSG on this webpage and if they meet the criteria they will be directed to CALSG to book an appointment with the study team.

Upon consent and recruitment, the following will be done:

1. Anthropometric measurements alongside traditional risk factors including blood pressure (BP), and waist-hip-ratio.
2. Body Impedance Analysis. This is a painless way to measure what the body is made of and involves standing on a special scale and holding onto handles.
3. Venipuncture will be conducted for an oral glucose tolerance test (OGTT) for 0 min, 1h and 2h glucose readings and HbA1c and storage.
4. Download of selected social media data (not directly containing personal data or posts) for up to 1 year preceding the visit from facebook, instagram and tiktok.
5. Continuous glucose monitor (CGM) sensor insertion. On the day of CGM insertion, a pre-insertion questionnaire (using form.sg, DIARY skin reaction form 1 before sensor wear) will be filled in which includes a picture of the site before sensor insertion.
6. A survey will also be conducted to ascertain sociodemographic (employment, type of residence) and educational status, family history of diabetes and comorbid conditions (if any), the individual's dietary intake, physical activity levels, and health-seeking behaviour. This survey will also include a section to fill in their average daily step count for 7/30 days. The participant will be guided to look for their step count data over 7 or 30 days (depending on what is available) from their smartphone activity tracker (this includes Apple Health, Samsung Health or Google Fit or any other activity tracker). This information will then be entered into the survey form on form.sg. No screenshots or data export is required.
7. Handgrip measurements
8. Second and third venipunctures for second part of OGTT.
9. Collection of dietary data via a digital food log

In Aim 2, the investigators aim to identify novel contemporary risk markers associated with T2D or prediabetes in young adults. This aim will not require another study visit from participants. Stored samples from Aim 1 baseline OGTT venipuncture will be used as well as the data retrieved from the study procedures in aim 1. Those who are diagnosed with T2D and prediabetes (estimated n=200 each), together with a normoglycaemic group (n=200) from Aim 1 will have the following done to enable diabetes subtyping: lipids, C-peptide, Insulin levels, Glutamic Acid Decarboxylase (GAD), Islet Antigen 2 (IA-2) Antibodies (Ab) and Zinc Transport 8 (ZnT8) Ab.

A composite score will then be developed for the diagnosis of prediabetes and diabetes. The dataset will be split into development and validation sets. Logistic regression modelling and Receiver Operating Characteristics (ROC) curve analysis will be employed to develop a composite score in identifying people with T2D or prediabetes, based on the sample with 200 newly diagnosed T2D, 200 prediabetes and 200 normoglycaemic participants. With the development set, two models will be fitted to predict a subject belongs to T2D, prediabetes or normoglycaemia: (a) candidate predictor variables of all abovementioned indicators and their derivatives, including sociodemographic, family history of diabetes and comorbid conditions, dietary intake, physical activity levels, body composition metrics, health-seeking behaviours, as well as CGM biomarkers, and (b) candidate predictor variables of all these variables except those extracted / derived from CGM. Variable selection methods will be employed to determine final models with optimal predictability, parsimony and model fit indices. Two composite scores, including and not including CGM biomarkers, will then be defined by the final selected models.

To fulfil aim 3, stored blood from participants will be used in ongoing large scale genomic studies such as the National Precision Medicine's Phase 3 programme. In this program, participants will have whole genome sequencing performed under research, with a cluster specific centralized genomics team made up of clinical geneticists, bioinformaticians, variant curators, and genetic counsellors available to process the genetic specimens end to end (genomics innovation hub). This would involve curating genes relevant to the disease subtype, in this case, diabetes, but also returning incidental findings that are Tier 1 American College of Medical Genetics and Genomics (ACMG) conditions. VCF files from the participants of this study will be returned to this study team so that further research can be done to determine if genomic information can further help risk stratify Asian YOD.

• Study Type: Observational
• Enrollment (Estimated): 3000

Contacts and Locations

• Study Contact: Name: Daphne SL Gardner, BA, BMBCh (Oxon), MRCP (UK); Phone Number: +6563214654; Email: daphne.gardner@singhealth.com.sg
• Study Contact Backup: Name: Navreen Kaur; Email: navreen.k.g.singh@singhealth.com.sg

Participation Criteria

Eligibility Criteria

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

• Sampling Method: Probability Sample

Study Population

Islandwide across Singapore

Description

Inclusion Criteria:

• Asian/Part Asian ethnicity living in Singapore, not known to have diabetes

Exclusion Criteria:

• Pregnancy women
• Non-Asian ethnicity
• On active cancer/steroid therapy
• Haemoglobinopathies or haemolytic anaemia
• Previous bariatric surgery
• Previous partial/total pancreatectomy

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

Intervention / Treatment

Singaporeans of Asian ethnicity under 40 years; Not previously known to have diabetes

Diagnostic test: Oral glucose tolerance test and HbA1c; Following overnight fasting for 8 hours; Other: Anthropometric measurements; Body Mass Index, Waist-Hip ratio, Blood pressure; Diagnostic test: Body impedance Analysis; Body composition analysis; Diagnostic test: Handgrip measurement; Handgrip strength measured using Jamar Dynanometer; Diagnostic test: Continuous glucose monitoring; Use of Retrospective continuous glucose monitoring sensor (Freestyle Libre Pro IQ); Other: Food diary recording over days 2 and 3 of continuous glucose monitoring; Including written food records and photographs for all food and drink intake; Other: Survey; Retrieval of sociodemographic details, family history of diabetes and comorbid conditions, information on dietary intake, physical activity levels, and health seeking behaviour. This includes average daily step count for 7/30 days.; Other: Skin reaction information; Form to feedback on any sensor skin reactions; Other: Download of social media data; This will involve a highly curated list of information to be retrieved from Facebook, Instagram and TikTok to enable AI-led sociobehavioural profiling. This will not retrieve any information on posts, photos, likes, comments, reactions or any item that will express intent.; Diagnostic test: Whole genome sequencing; Whole blood sample will be retrieved and stored before being sent for whole genome sequencing at a later stage.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnosis of diabetes	Fasting glucose >/=7mmol/l or 2-hour glucose >/=11.1 mmol/l on oral glucose tolerance test or HbA1c >/=7%.	Baseline

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Diagnosis of pre-diabetes	Fasting glucose >/=5.7mmol/l or 2-hour glucose >/=7,8 mmol/l on oral glucose tolerance test or HbA1c >/= 5.7%.	Baseline

Collaborators and Investigators

• Sponsor: Singapore General Hospital
• Collaborators: Duke-NUS Centre of Quantitative Medicine; SingHealth Duke-NUS Academic Medical Centre; Data Science and Artificial intelligence Laboratory, SGH; Translational Research and Innovation Lab, SingHealth
• Investigators: Principal Investigator: Daphne SL Gardner, BA, BMBCh(Oxon), MRCP (UK), Singapore Health

Publications and helpful links

General Publications

• Tan JK, Salim NNM, Lim GH, Chia SY, Thumboo J, Bee YM. Trends in diabetes-related complications in Singapore, 2013-2020: A registry-based study. PLoS One. 2022 Oct 11;17(10):e0275920. doi: 10.1371/journal.pone.0275920. eCollection 2022.
• Zahalka SJ, Galindo RJ, Shah VN, Low Wang CC. Continuous Glucose Monitoring for Prediabetes: What Are the Best Metrics? J Diabetes Sci Technol. 2024 Jul;18(4):835-846. doi: 10.1177/19322968241242487. Epub 2024 Apr 17.
• Deurenberg P, Deurenberg-Yap M, Guricci S. Asians are different from Caucasians and from each other in their body mass index/body fat per cent relationship. Obes Rev. 2002 Aug;3(3):141-6. doi: 10.1046/j.1467-789x.2002.00065.x.
• Kuang M, Lu S, Yang R, Chen H, Zhang S, Sheng G, Zou Y. Association of predicted fat mass and lean body mass with diabetes: a longitudinal cohort study in an Asian population. Front Nutr. 2023 May 9;10:1093438. doi: 10.3389/fnut.2023.1093438. eCollection 2023.
• Yeung RO, Zhang Y, Luk A, Yang W, Sobrepena L, Yoon KH, Aravind SR, Sheu W, Nguyen TK, Ozaki R, Deerochanawong C, Tsang CC, Chan WB, Hong EG, Do TQ, Cheung Y, Brown N, Goh SY, Ma RC, Mukhopadhyay M, Ojha AK, Chakraborty S, Kong AP, Lau W, Jia W, Li W, Guo X, Bian R, Weng J, Ji L, Reyes-dela Rosa M, Toledo RM, Himathongkam T, Yoo SJ, Chow CC, Ho LL, Chuang LM, Tutino G, Tong PC, So WY, Wolthers T, Ko G, Lyubomirsky G, Chan JC. Metabolic profiles and treatment gaps in young-onset type 2 diabetes in Asia (the JADE programme): a cross-sectional study of a prospective cohort. Lancet Diabetes Endocrinol. 2014 Dec;2(12):935-43. doi: 10.1016/S2213-8587(14)70137-8. Epub 2014 Jul 28.
• Rama Chandran S, Sng GGR, Wong CYH, Ang WM, Gardner D. Continuous Glucose Monitoring Metrics in Asians Without Diabetes: Differentiating Prediabetes From Normoglycemia. J Diabetes Sci Technol. 2025 Oct 21:19322968251384682. doi: 10.1177/19322968251384682. Online ahead of print.

Helpful Links

• This is the study page which was created by the investigators to provide information to participants on the background, aims, and procedures of the study. They can also sign up and choose a data to participate in the study.

Study record dates

Study Major Dates

• Study Start (Estimated): March 18, 2026
• Primary Completion (Estimated): January 2, 2029
• Study Completion (Estimated): January 2, 2029

Study Registration Dates

• First Submitted: December 1, 2025
• First Submitted That Met QC Criteria: March 1, 2026
• First Posted (Actual): March 5, 2026

Study Record Updates

• Last Update Posted (Actual): March 5, 2026
• Last Update Submitted That Met QC Criteria: March 1, 2026
• Last Verified: February 1, 2026

More Information

Terms related to this study

• Keywords: Risk factors; Asian; Young onset diabetes; contemporary
• Additional Relevant MeSH Terms: Health Care Quality, Access, and Evaluation; Investigative Techniques; Epidemiologic Methods; Clinical Laboratory Techniques; Diagnostic Techniques and Procedures; Diagnosis; Data Collection; Health Care Evaluation Mechanisms; Quality of Health Care; Public Health; Environment and Public Health; Blood Chemical Analysis; Clinical Chemistry Tests; Diagnostic Techniques, Endocrine; Monitoring, Physiologic; Surveys and Questionnaires; Continuous Glucose Monitoring; Glucose Tolerance Test
• Other Study ID Numbers: DIARY : CIRB 2025-0719; Tanoto Foundation MRF (Other Identifier: Tanoto)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: This is an observational study, only aggregated data will be provided. In addition, there is a part of the study that retrieves information social media activity. There is a potential that individual level data can lead to sensitive personal information being revealed.

Drug and device information, study documents

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