Type 2 DiabetesNCT06989008
Enhancing Diabetes Care: Exposome &Amp; Sensors
An observational study of Type 2 Diabetes, run by University of Illinois Chicago at 2 sites in United States.
Trial summary
The study aims to integrate various data types, such as electronic health records, wearable device data, and environmental data, to create a comprehensive, personalized diabetes care model. The study will focus on people with type 2 diabetes living in specified vulnerable zip codes. Read more about this study
- Who is it for?
- Ages 18 to 65 years
- Conditions the study is for
- Type 2 Diabetes
- What is being tested?
- Observational Study: Relationships Among Glucose, Physical Activity and Environmental Influences
- How many people
- 20 participants
- Where
- 2 sitesUnited States
- Study dates
- 25 Mar 2025to 31 Jan 2026
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 65 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: The study aims to enroll participants with type 2 diabetes who reside in an urban area that is associated with poor health outcomes as characterized by vulnerable zip codes.
Who may be able to join
- People with diabetes in the 18-65 years of age range
- Diagnosed with type 2 diabetes
- Resides in the specified high social vulnerability zip codes - 60619, 60620, 60621, 60636, 60644, 60624, 60609, 60612, 60617, 60623, 60628, 60629, 60639, 60645, 60649, 60651, 60652, 60653
- Speak and understand the English language
- Willing to wear various devices (CGM and sports wristband)
- Own a smartphone Exclusion Criteria
Show all 9Show fewer
- Subjects will be excluded from the study for the following reasons:
- Any concern of not understanding informed consent
- Unable to understand or unwilling to follow research protocol
Who cannot join
None listed.
Trial locations and contacts
2 sites in 1 country. Contact the study team or a site near you to ask about taking part.
United States2 sites, 2 recruiting
- Recruiting
University of Illinois - Chicago
Chicago, Illinois, 60612
Laurie Quinn, PhD RN, 312-996-7906, lquinn1@uic.edu
- Recruiting
University of Illinois College of Nursing
Chicago, Illinois, 60612
Laurie Quinn Clinical Professor, PhD, 312-771-6497, lquinn1@uic.edu
Andy Boyd, MD, 312-996-8339, boyda@uic.edu
About this study
Official title: Leveraging the Exposome and Patient Sensor Data to Enhance Personalized Diabetes Care Across Diverse Communities
The study aims to integrate various data types, such as electronic health records, wearable device data, and environmental data, to create a comprehensive, personalized diabetes care model. The study will focus on people with type 2 diabetes living in specified vulnerable zip codes.
Read the detailed description
The study procedures will commence with an initial screening to confirm participants' eligibility based on the inclusion criteria, followed by the signing of Informed Consent forms. Baseline data including medical records and quality of life questionnaires will be collected. A continuous glucose monitoring (CGM - Dexcom 7) will be inserted; a sport wristband (Fitbit Sense 2) will be provided; and environmental sensor for home data collection, will be distributed and set up in the home setting by the participant. The study will require two CGMs (10 days for each CGM). The 1st CGM will be inserted during the initial visit to the clinic. After 10 days, participants will return to the clinic, and the 2nd CGM will be inserted. The investigators will also send text reminders two days before the scheduled 2nd CGM insertion. Communication with participants will be maintained via text messages, and for those who request it, virtual meetings can be arranged (via HIPAA-protected Zoom). The subjects will be provided with a mailing envelope with postage to return the 2nd CGM, Fitbit Sense 2 and environmental sensors. If the subject is returning to clinic within the next week, they can instead return the devices during their visit, and a member of the study team will meet them in the clinic.
Throughout the study, there will be integration of real-time data from various sources, including electronic health records, wearables, and environmental sensor. The environmental sensor is a climate sensor called Airthings. The Airthings View Plus is an advanced indoor air quality monitor that tracks various environmental parameters to ensure healthy indoor air conditions. It features sensors for radon, particulate matter (PM2.5), carbon dioxide (CO2), volatile organic compounds (VOCs), humidity, temperature, and air pressure. This monitor is connected to Wi-Fi, allowing real-time access to air quality data via a smartphone app. The device is designed for ease of use with an eInk display for clear visibility of air quality readings and simple setup instructions. The Airthings View Plus is battery-operated with an option for USB power, providing flexibility in how and where the device can be used within a home.
- Conditions
- Type 2 Diabetes
- Being tested
- Observational Study: Relationships Among Glucose, Physical Activity and Environmental Influences
- Keywords
- physical activity, continuous glucose monitoring, Environmental
- Medical subject headings
- Diabetes Mellitus, Type 2, Motor Activity
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Observational Study: Relationships Among Glucose, Physical Activity and Environmental InfluencesOther
This is a single group observational study with no interventions.
| Study group | Role | What they receive |
|---|---|---|
| Type 2 Diabetes | The study will include adults with Type 2 Diabetes living in an urban setting characterized by poor health outcomes. Receives: Other: Observational Study: Relationships Among Glucose, Physical Activity and Environmental Influences |
What is being measured
The primary outcome is the main question the study is designed to answer.
The primary outcome is to collect and analyze continuous interstitial glucose measurements in 20 individuals with type 2 diabetes over a period of 20 days using a DEXCOM G7 continuous glucose monitor (CGM).
The primary outcomes will include the following CGM metrics: mean glucose "Glucose Management Indicator" which is an estimate of A1C (%); Coefficient of Variation which is an estimate of glycemic variability; Very High Time Above Range which is the percent of time above range including the % of readings and time > 250 mg/dl; High Time Above Range which is the percent of time above range including the % of readings and time 181-250 mg/dl; Time in Range which is the % of readings and time 70-180 mg/dl; Low Time Below Range which is the percent of time below range including the % of readings and time 54 - 69 mg/dl; and Very Low Time Below Range which is the percent of time below range including the % of readings and time < 54 mg/dl.
Measured: 20 days
Secondary outcomes (3)
The subject's perception of their "Quality of Life" will be measured at the start of the study.
Quality of Life will be measured by scores on the Diabetes Quality of Life (DQOL) questionnaire.
Measured: 1 time
The subject's physical activity and sleep will be measured continuously throughout the study.
The subjects activity and sleep will be measured continuously throughout the study using a FitbitSense 2 Smartwatch. Physical activity will be quantified as time spent in sedentary, low, moderate and vigorous activity; sleep will be quantified by time spent awake, light sleep, deep sleep, and REM sleep.
Measured: 20 days
The subject's air quality will be measured continuously throughout the study.
The air quality will be measured by an environmental sensor called an Airthing's View Plus that will monitor radon, particulate matter (PM2.5), carbon dioxide (CO2), volatile organic compounds (VOCs), humidity, temperature, and air pressure.
Measured: 20 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 May 2025
- Study start25 Mar 2025
- Primary completion1 Jan 2026 (estimated)
- Study completion31 Jan 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Type 2 DiabetesStudies of the same condition, open and under way.
- More trials run by University of Illinois ChicagoThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 20 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Illinois Chicago
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Andy Boyd, MD, Principal investigator, University of Illinois Chicago
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06989008
- Sponsor's protocol ID
- 2024-0372
- Status last verified
- May 2025
- First submitted
- 28 Apr 2025
- Last updated
- 25 May 2025
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Data obtained through this study may be provided to qualified researchers with academic interest in type 2 diabetes. Data or samples shared will be coded, with no PHI included. Approval of the request and execution of all applicable agreements (i.e. a material transfer agreement) are prerequisites to the sharing of data with the requesting party.
Publications
Sarker IH. Machine Learning: Algorithms, Real-World Applications and Research Directions. SN Comput Sci. 2021;2(3):160. doi: 10.1007/s42979-021-00592-x. Epub 2021 Mar 22.
PubMed 33778771Wu Y, Ding Y, Tanaka Y, Zhang W. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int J Med Sci. 2014 Sep 6;11(11):1185-200. doi: 10.7150/ijms.10001. eCollection 2014.
PubMed 25249787Vrijheid M, Slama R, Robinson O, Chatzi L, Coen M, van den Hazel P, Thomsen C, Wright J, Athersuch TJ, Avellana N, Basagana X, Brochot C, Bucchini L, Bustamante M, Carracedo A, Casas M, Estivill X, Fairley L, van Gent D, Gonzalez JR, Granum B, Grazuleviciene R, Gutzkow KB, Julvez J, Keun HC, Kogevinas M, McEachan RR, Meltzer HM, Sabido E, Schwarze PE, Siroux V, Sunyer J, Want EJ, Zeman F, Nieuwenhuijsen MJ. The human early-life exposome (HELIX): project rationale and design. Environ Health Perspect. 2014 Jun;122(6):535-44. doi: 10.1289/ehp.1307204. Epub 2014 Mar 7.
PubMed 24610234Sevil M, Rashid M, Maloney Z, Hajizadeh I, Samadi S, Askari MR, Hobbs N, Brandt R, Park M, Quinn L, Cinar A. Determining Physical Activity Characteristics from Wristband Data for Use in Automated Insulin Delivery Systems. IEEE Sens J. 2020 Nov;20(21):12859-12870. doi: 10.1109/jsen.2020.3000772. Epub 2020 Jun 8.
PubMed 33100923Li X, Dunn J, Salins D, Zhou G, Zhou W, Schussler-Fiorenza Rose SM, Perelman D, Colbert E, Runge R, Rego S, Sonecha R, Datta S, McLaughlin T, Snyder MP. Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. PLoS Biol. 2017 Jan 12;15(1):e2001402. doi: 10.1371/journal.pbio.2001402. eCollection 2017 Jan.
PubMed 28081144Sevil M, Rashid M, Hajizadeh I, Askari MR, Hobbs N, Brandt R, Park M, Quinn L, Cinar A. Discrimination of simultaneous psychological and physical stressors using wristband biosignals. Comput Methods Programs Biomed. 2021 Feb;199:105898. doi: 10.1016/j.cmpb.2020.105898. Epub 2020 Dec 17.
PubMed 33360529
Study at a glance
From the registry record, last updated by the sponsor on 25 May 2025. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Leveraging the Exposome and Patient Sensor Data to Enhance Personalized Diabetes Care Across Diverse Communities
- ClinicalTrials.gov ID
- NCT06989008
- Acronym / sponsor ID
- 2024-0372
- Conditions
- Type 2 Diabetes
- Keywords
- physical activity, continuous glucose monitoring, Environmental
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 20 participants (estimated)
- Lead sponsor
- University of Illinois ChicagoUniversity, hospital or other
- Study start
- 25 Mar 2025 (actual)
- Primary completion
- 1 Jan 2026 (estimated)
- Study completion
- 31 Jan 2026 (estimated)
- First posted
- 25 May 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The study aims to integrate various data types, such as electronic health records, wearable device data, and environmental data, to create a comprehensive, personalized diabetes care model. The study will focus on people with type 2 diabetes living in specified vulnerable zip codes.
Detailed description
The study procedures will commence with an initial screening to confirm participants' eligibility based on the inclusion criteria, followed by the signing of Informed Consent forms. Baseline data including medical records and quality of life questionnaires will be collected. A continuous glucose monitoring (CGM - Dexcom 7) will be inserted; a sport wristband (Fitbit Sense 2) will be provided; and environmental sensor for home data collection, will be distributed and set up in the home setting by the participant. The study will require two CGMs (10 days for each CGM). The 1st CGM will be inserted during the initial visit to the clinic. After 10 days, participants will return to the clinic, and the 2nd CGM will be inserted. The investigators will also send text reminders two days before the scheduled 2nd CGM insertion. Communication with participants will be maintained via text messages, and for those who request it, virtual meetings can be arranged (via HIPAA-protected Zoom). The subjects will be provided with a mailing envelope with postage to return the 2nd CGM, Fitbit Sense 2 and environmental sensors. If the subject is returning to clinic within the next week, they can instead return the devices during their visit, and a member of the study team will meet them in the clinic.
Throughout the study, there will be integration of real-time data from various sources, including electronic health records, wearables, and environmental sensor. The environmental sensor is a climate sensor called Airthings. The Airthings View Plus is an advanced indoor air quality monitor that tracks various environmental parameters to ensure healthy indoor air conditions. It features sensors for radon, particulate matter (PM2.5), carbon dioxide (CO2), volatile organic compounds (VOCs), humidity, temperature, and air pressure. This monitor is connected to Wi-Fi, allowing real-time access to air quality data via a smartphone app. The device is designed for ease of use with an eInk display for clear visibility of air quality readings and simple setup instructions. The Airthings View Plus is battery-operated with an option for USB power, providing flexibility in how and where the device can be used within a home.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Type 2 Diabetes | – | Other: Observational Study: Relationships Among Glucose, Physical Activity and Environmental InfluencesThe study will include adults with Type 2 Diabetes living in an urban setting characterized by poor health outcomes. |
Who may qualify
- Ages
- 18 to 65 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The study aims to enroll participants with type 2 diabetes who reside in an urban area that is associated with poor health outcomes as characterized by vulnerable zip codes.
Key inclusion criteria (9 listed)
- People with diabetes in the 18-65 years of age range
- Diagnosed with type 2 diabetes
- Resides in the specified high social vulnerability zip codes - 60619, 60620, 60621, 60636, 60644, 60624, 60609, 60612, 60617, 60623, 60628, 60629, 60639, 60645, 60649, 60651, 60652, 60653
- Speak and understand the English language
- Willing to wear various devices (CGM and sports wristband)
Key exclusion criteria (0 listed)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Observational Study: Relationships Among Glucose, Physical Activity and Environmental InfluencesThis is a single group observational study with no interventions. | Other | Type 2 Diabetes |
Primary outcome
The primary outcome is to collect and analyze continuous interstitial glucose measurements in 20 individuals with type 2 diabetes over a period of 20 days using a DEXCOM G7 continuous glucose monitor (CGM).
Time frame: 20 days
The primary outcomes will include the following CGM metrics: mean glucose "Glucose Management Indicator" which is an estimate of A1C (%); Coefficient of Variation which is an estimate of glycemic variability; Very High Time Above Range which is the percent of time above range including the % of readings and time > 250 mg/dl; High Time Above Range which is the percent of time above range including the % of readings and time 181-250 mg/dl; Time in Range which is the % of readings and time 70-180 mg/dl; Low Time Below Range which is the percent of time below range including the % of readings and time 54 - 69 mg/dl; and Very Low Time Below Range which is the percent of time below range including the % of readings and time < 54 mg/dl.
3 secondary outcomes
The subject's perception of their "Quality of Life" will be measured at the start of the study.
Time frame: 1 time
The subject's physical activity and sleep will be measured continuously throughout the study.
Time frame: 20 days
The subject's air quality will be measured continuously throughout the study.
Time frame: 20 days
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 25 May 2025.
- Background: PubMed 33778771Sarker IH. Machine Learning: Algorithms, Real-World Applications and Research Directions. SN Comput Sci. 2021;2(3):160. doi: 10.1007/s42979-021-00592-x. Epub 2021 Mar 22.
- Background: PubMed 25249787Wu Y, Ding Y, Tanaka Y, Zhang W. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int J Med Sci. 2014 Sep 6;11(11):1185-200. doi: 10.7150/ijms.10001. eCollection 2014.
- Background: PubMed 24610234Vrijheid M, Slama R, Robinson O, Chatzi L, Coen M, van den Hazel P, Thomsen C, Wright J, Athersuch TJ, Avellana N, Basagana X, Brochot C, Bucchini L, Bustamante M, Carracedo A, Casas M, Estivill X, Fairley L, van Gent D, Gonzalez JR, Granum B, Grazuleviciene R, Gutzkow KB, Julvez J, Keun HC, Kogevinas M, McEachan RR, Meltzer HM, Sabido E, Schwarze PE, Siroux V, Sunyer J, Want EJ, Zeman F, Nieuwenhuijsen MJ. The human early-life exposome (HELIX): project rationale and design. Environ Health Perspect. 2014 Jun;122(6):535-44. doi: 10.1289/ehp.1307204. Epub 2014 Mar 7.
- Background: PubMed 33100923Sevil M, Rashid M, Maloney Z, Hajizadeh I, Samadi S, Askari MR, Hobbs N, Brandt R, Park M, Quinn L, Cinar A. Determining Physical Activity Characteristics from Wristband Data for Use in Automated Insulin Delivery Systems. IEEE Sens J. 2020 Nov;20(21):12859-12870. doi: 10.1109/jsen.2020.3000772. Epub 2020 Jun 8.
- Background: PubMed 28081144Li X, Dunn J, Salins D, Zhou G, Zhou W, Schussler-Fiorenza Rose SM, Perelman D, Colbert E, Runge R, Rego S, Sonecha R, Datta S, McLaughlin T, Snyder MP. Digital Health: Tracking Physiomes and Activity Using Wearable Biosensors Reveals Useful Health-Related Information. PLoS Biol. 2017 Jan 12;15(1):e2001402. doi: 10.1371/journal.pbio.2001402. eCollection 2017 Jan.
- Background: PubMed 33360529Sevil M, Rashid M, Hajizadeh I, Askari MR, Hobbs N, Brandt R, Park M, Quinn L, Cinar A. Discrimination of simultaneous psychological and physical stressors using wristband biosignals. Comput Methods Programs Biomed. 2021 Feb;199:105898. doi: 10.1016/j.cmpb.2020.105898. Epub 2020 Dec 17.
- Individual participant dataSharing planned: Yes. Data obtained through this study may be provided to qualified researchers with academic interest in type 2 diabetes. Data or samples shared will be coded, with no PHI included. Approval of the request and execution of all applicable agreements (i.e. a material transfer agreement) are prerequisites to the sharing of data with the requesting party.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Andy Boyd, MD principal investigator
University of Illinois Chicago
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Type 2 Diabetes, run by University of Illinois Chicago at 2 sites in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 9 inclusion and 0 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 25 May 2025. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Laurie Quinn, PhD (312 771 6497, lquinn1@uic.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The primary outcome is to collect and analyze continuous interstitial glucose measurements in 20 individuals with type 2 diabetes over a period of 20 days using a DEXCOM G7 continuous glucose monitor (CGM). (time frame: 20 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06989008, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 25 May 2025; AzTrials last refreshed its copy on 7 Nov 2026.