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RecruitingNCT07400549Updated Feb 10, 2026

Prospective Exploratory Study on the Comprehensive Application Effectiveness of Exercise Prescription Decision Support Tools in the Management of Patients With "Four Highs" (Hypertension, Hyperglycemia, Hyperlipidemia, Hyperuricemia)

An interventional study of Enhanced Mini-Program Intervention and Enhanced Control in Hypertension, Hyperglycemia and Hyperlipidemia, sponsored by China National Center for Cardiovascular Diseases. Recruiting at 1 site in China. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2026-02-10.

Sponsored by China National Center for Cardiovascular Diseases · Not applicable, Interventional, and Treatment

Phase
Not applicable
Study type
Interventional
Enrollment
100
Allocation
Randomized
Ages
18 Years and older
Sex
All
01

Study summary

This study conducted a six-month exploratory clinical trial to evaluate the impact of an exercise prescription mini-program, based on the "Exercise Guidelines for the 'Four Highs'", on the physical activity levels and related health indicators of patients with hypertension, hyperglycemia, hyperlipidemia, and hyperuricemia in primary healthcare settings in China.

02

Conditions studied

  • Hypertension
  • Hyperglycemia
  • Hyperlipidemia
  • Hyperuricemia
  • Digital Intervention

Keywords

  • Digitally-Enabled Health
  • Chronic Disease Prevention and Control
  • Sports prescription
  • Primary health care (PHC)
03

Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No

Inclusion criteria

  1. Aged 18 years or older.
  2. Willing to participate in the study and able to provide written informed consent.
  3. Diagnosed with at least one of the following "Four Highs" conditions:

    Hypertension: Diagnosed primary hypertension, defined as seated office SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg on at least three non-consecutive days, or currently taking antihypertensive medication. Blood pressure must be controlled while on four or more antihypertensive agents. Diabetes Mellitus: Diagnosed diabetes, defined as having typical symptoms plus random plasma glucose ≥ 11.1 mmol/L, or fasting plasma glucose ≥ 7.0 mmol/L, or 2-hour plasma glucose during OGTT

    ≥ 11.1 mmol/L, or HbA1c ≥ 6.5%, or currently taking glucose-lowering medication. HbA1c level must be between 6.5% and 13.0%. Hyperlipidemia: Diagnosed hyperlipidemia, defined as total cholesterol (TC) ≥ 6.22 mmol/L, or LDL-C ≥ 4.14 mmol/L, or HDL-C \< 1.04 mmol/ L, or triglycerides (TG) > 2.26 mmol/L, or currently taking lipid-lowering medication. Hyperuricemia: Diagnosed hyperuricemia, defined as a fasting serum uric acid level > 420 μmol/L (7 mg/dL) in men and postmenopausal women, or > 360 μmol/L (6 mg/dL) in premenopausal women, on two non-consecutive days under a normal purine diet, or currently taking urate-lowering medication.

  4. Capable of using a smartphone.
  5. A local permanent resident who receives basic public health service management at the designated community health center/station or township hospital.
  6. Has not engaged in regular moderate- to vigorous-intensity physical activity (defined as at least 30 minutes per session, on at least 3 days per week) in the past three months.

Exclusion criteria

Exclusion Criteria:

Patients meeting any of the following criteria will be excluded:

  1. History or acute episode of cardiovascular or cerebrovascular disease, including: angina pectoris, myocardial infarction, coronary revascularization surgery, stroke (ischemic or hemorrhagic, including transient ischemic attack), symptomatic peripheral arterial disease requiring surgery or diagnosed by vascular imaging, ventricular arrhythmia, uncontrolled atrial fibrillation, congestive heart failure (New York Heart Association Class III or IV), hypertrophic cardiomyopathy, history of aneurysm with diameter ≥ 5.5 cm or prior aneurysm surgery.
  2. Current malignant tumor or history of malignant tumor within the past five years.
  3. Contraindications to exercise, such as bone and joint diseases.
  4. Severe respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), restricted lung volume (due to obesity, pregnancy, or spinal deformity), or cystic fibrosis.
  5. Neuromuscular and degenerative diseases, such as muscular dystrophy, poliomyelitis, and dementia.
  6. Severe mental illness, including schizophrenia, bipolar disorder, eating disorders, or depression (with hospitalization for the condition within the past 6 months).
  7. Movement and other neurological disorders, such as Huntington's disease, torsion dystonia, Parkinson's disease, and certain epileptic disorders.
  8. Severe comorbidities with a life expectancy of less than 24 months.
  9. Plans to relocate from the area within the next three months.
  10. Participation in other physical activity level intervention programs within the six months prior to the screening visit.
  11. Current participation in another randomized clinical trial.
  12. Any other condition that, in the investigator's judgment, may interfere with adherence to the trial protocol.
04

Study design

Phase
Not applicable
Primary purpose
Treatment
Allocation
Randomized
Intervention model
Parallel assignment
Masking
None (open label)
Enrollment
100 participants (estimated)

Study arms

  • Experimental
    The Enhanced Mini-Program Intervention Group

    Behavioral: Enhanced Mini-Program Intervention

  • Active comparator
    The Enhanced Control Group

    Behavioral: Enhanced Control

Interventions

  • BehavioralEnhanced Mini-Program Intervention

    physician training/assessment + patient exercise guidance via the mini-program + patient social support group activities

  • BehavioralEnhanced Control

    physicians receiving training/assessment in addition to conducting patient exercise guidance autonomously

05

What researchers measure

Primary outcomes

  1. Change in mean daily step count

    The calculation of changes in average daily step count is defined as the difference between the average daily step count during the 7-day period prior to intervention (hereafter referred to as "the pre-intervention week") and the average daily step count during the final 7-day period of the third intervention month (hereafter referred to as "the final intervention week")

    Time frame: from baseline to Month 3

Secondary outcomes

  1. Change from Baseline in Average Daily Moderate-to-Vigorous Physical Activity (MVPA) Time (minutes/day) Measured by HLWH005 Accelerometer-Based Wearable

    Average daily time (minutes/day) spent in MVPA, defined as activity intensity \>100 steps/min, assessed using the HLWH005 accelerometer-based wearable device. MVPA will be calculated as the mean MVPA minutes per day over a 7-day monitoring period. The outcome is the change from the baseline 7-day period (pre-intervention week) to the final 7-day period of Month 3 (last week of intervention).

    Time frame: from baseline to Month 3

  2. Change from Baseline in Maximum Handgrip Strength (kg) Measured by CAMRY EH101 Hand Dynamometer

    Maximum handgrip strength (kg) assessed using the CAMRY EH101 hand dynamometer. Grip strength will be measured in a standing position with the elbow extended and wrist in neutral position. Both hands will be assessed; each hand will be measured 3 times and the maximum value will be recorded. The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  3. Change from Baseline in Body Mass Index (BMI) (kg/m²) Based on Measured Height and Weight

    BMI (kg/m²) calculated as weight (kg) / height (m)², using standard clinical measurements of body weight (calibrated digital scale) and height (stadiometer). The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  4. Change from Baseline in Waist-to-Height Ratio (unitless) Based on Measured Waist Circumference and Height

    Waist-to-height ratio (unitless) calculated as waist circumference (cm) / height (cm). Waist circumference will be measured using a non-stretch measuring tape following standard clinical procedures; height will be measured using a stadiometer. The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  5. Change from Baseline in Waist-to-Hip Ratio (unitless) Based on Measured Waist and Hip Circumference

    Waist-to-hip ratio (unitless) calculated as waist circumference (cm) / hip circumference (cm). Waist and hip circumference will be measured using a non-stretch measuring tape following standard clinical procedures. The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  6. Change from Baseline in Resting Systolic Blood Pressure (mmHg) Measured by HELOWIN TE-7003Y-C Automated Arm Cuff

    Resting systolic blood pressure (mmHg) measured using the HELOWIN TE-7003Y-C automated upper-arm blood pressure monitor. After 5 minutes of seated rest, blood pressure will be measured 3 times at 5-minute intervals; the average of the 3 readings will be used. The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  7. Change from Baseline in Glycated Hemoglobin (HbA1c) (%) Measured by Laboratory Assay

    HbA1c (%) measured from fasting venous blood samples analyzed at the local clinical laboratory using standard laboratory assay methods. The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  8. Change from Baseline in Low-Density Lipoprotein Cholesterol (LDL-C) Concentration (mmol/L) Measured by Laboratory Assay

    LDL-C concentration (mmol/L) measured from fasting venous blood samples analyzed at the local clinical laboratory using standard laboratory assay methods. The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  9. Change from Baseline in Serum Uric Acid Concentration (µmol/L) Measured by Laboratory Assay

    Serum uric acid concentration (µmol/L) measured from fasting venous blood samples analyzed at the local clinical laboratory using standard laboratory assay methods. The outcome is the change from baseline to Month 3.

    Time frame: from baseline to Month 3

  10. High Adherence Rate to the Mini-Program-Based Exercise Plan (%) Assessed by Mini-Program Check-in Logs and Social-Support Attendance Records (Intervention Group Only)

    High adherence rate, defined as the percentage of participants in the mini-program intervention group who meet the pre-specified adherence criteria during the 3-month intervention period: (1) average weekly completion rate ≥70% for each of the three check-in modules ("aerobic exercise", "resistance exercise", and "step count") recorded in the mini-program logs; and (2) attendance at ≥2 monthly social-support group sessions recorded by attendance logs.

    Time frame: from baseline to Month 3

06

Study locations

1 of 1 sites recruiting
  • Fuwai Hospital, Chinese Academy of MedicL Sciences
    Beijing, 100061, China
    Recruiting
07

References and documents

Publications

  • Egan BM. Physical Activity and Hypertension: Knowing Is Not Enough; We Must Apply. Willing Is Not Enough; We Must Do-von Goethe. Hypertension. 2017 Mar;69(3):404-406. doi: 10.1161/HYPERTENSIONAHA.116.08508. Epub 2017 Jan 30. No abstract available. PubMed 28137989 ↗
  • Colberg SR, Sigal RJ, Yardley JE, Riddell MC, Dunstan DW, Dempsey PC, Horton ES, Castorino K, Tate DF. Physical Activity/Exercise and Diabetes: A Position Statement of the American Diabetes Association. Diabetes Care. 2016 Nov;39(11):2065-2079. doi: 10.2337/dc16-1728. No abstract available. PubMed 27926890 ↗
  • Sacks FM, Lichtenstein AH, Wu JHY, Appel LJ, Creager MA, Kris-Etherton PM, Miller M, Rimm EB, Rudel LL, Robinson JG, Stone NJ, Van Horn LV; American Heart Association. Dietary Fats and Cardiovascular Disease: A Presidential Advisory From the American Heart Association. Circulation. 2017 Jul 18;136(3):e1-e23. doi: 10.1161/CIR.0000000000000510. Epub 2017 Jun 15. PubMed 28620111 ↗
  • Piao W, Zhao L, Yang Y, Fang H, Ju L, Cai S, Yu D. The Prevalence of Hyperuricemia and Its Correlates among Adults in China: Results from CNHS 2015-2017. Nutrients. 2022 Oct 2;14(19):4095. doi: 10.3390/nu14194095. PubMed 36235748 ↗
  • Strain T, Flaxman S, Guthold R, Semenova E, Cowan M, Riley LM, Bull FC, Stevens GA; Country Data Author Group. National, regional, and global trends in insufficient physical activity among adults from 2000 to 2022: a pooled analysis of 507 population-based surveys with 5.7 million participants. Lancet Glob Health. 2024 Aug;12(8):e1232-e1243. doi: 10.1016/S2214-109X(24)00150-5. Epub 2024 Jun 25. PubMed 38942042 ↗
  • Smart NA, Downes D, van der Touw T, Hada S, Dieberg G, Pearson MJ, Wolden M, King N, Goodman SPJ. The Effect of Exercise Training on Blood Lipids: A Systematic Review and Meta-analysis. Sports Med. 2025 Jan;55(1):67-78. doi: 10.1007/s40279-024-02115-z. Epub 2024 Sep 27. PubMed 39331324 ↗
  • Wu J, Feng Y, Zhao Y, Guo Z, Liu R, Zeng X, Yang F, Liu B, Gu J, Tarimo CS, Shao W, Guo X, Li Q, Zhao L, Ma M, Shen Z, Zhao Q, Miao Y. Lifestyle behaviors and risk of cardiovascular disease and prognosis among individuals with cardiovascular disease: a systematic review and meta-analysis of 71 prospective cohort studies. Int J Behav Nutr Phys Act. 2024 Apr 22;21(1):42. doi: 10.1186/s12966-024-01586-7. PubMed 38650004 ↗
  • Hegde SM, Solomon SD. Influence of Physical Activity on Hypertension and Cardiac Structure and Function. Curr Hypertens Rep. 2015 Oct;17(10):77. doi: 10.1007/s11906-015-0588-3. PubMed 26277725 ↗
  • Heath L, Stevens R, Nicholson BD, Wherton J, Gao M, Callan C, Haasova S, Aveyard P. Strategies to improve the implementation of preventive care in primary care: a systematic review and meta-analysis. BMC Med. 2024 Sep 27;22(1):412. doi: 10.1186/s12916-024-03588-5. PubMed 39334345 ↗
  • Singh B, Ahmed M, Staiano AE, Gough C, Petersen J, Vandelanotte C, Kracht C, Huong C, Yin Z, Vasiloglou MF, Pan CC, Short CE, Mclaughlin M, von Klinggraeff L, Pfledderer CD, Moran LJ, Button AM, Maher CA. A systematic umbrella review and meta-meta-analysis of eHealth and mHealth interventions for improving lifestyle behaviours. NPJ Digit Med. 2024 Jul 5;7(1):179. doi: 10.1038/s41746-024-01172-y. PubMed 38969775 ↗
  • Kickbusch I, Piselli D, Agrawal A, Balicer R, Banner O, Adelhardt M, Capobianco E, Fabian C, Singh Gill A, Lupton D, Medhora RP, Ndili N, Rys A, Sambuli N, Settle D, Swaminathan S, Morales JV, Wolpert M, Wyckoff AW, Xue L; Secretariat of the Lancet and Financial Times Commission. The Lancet and Financial Times Commission on governing health futures 2030: growing up in a digital world. Lancet. 2021 Nov 6;398(10312):1727-1776. doi: 10.1016/S0140-6736(21)01824-9. Epub 2021 Oct 24. No abstract available. PubMed 34706260 ↗
  • Zangger G, Bricca A, Liaghat B, Juhl CB, Mortensen SR, Andersen RM, Damsted C, Hamborg TG, Ried-Larsen M, Tang LH, Thygesen LC, Skou ST. Benefits and Harms of Digital Health Interventions Promoting Physical Activity in People With Chronic Conditions: Systematic Review and Meta-Analysis. J Med Internet Res. 2023 Jul 6;25:e46439. doi: 10.2196/46439. PubMed 37410534 ↗
  • Kart O, Mevsim V, Kut A, Yurek I, Altin AO, Yilmaz O. A mobile and web-based clinical decision support and monitoring system for diabetes mellitus patients in primary care: a study protocol for a randomized controlled trial. BMC Med Inform Decis Mak. 2017 Nov 29;17(1):154. doi: 10.1186/s12911-017-0558-6. PubMed 29187186 ↗
  • Raghu A, Praveen D, Peiris D, Tarassenko L, Clifford G. Engineering a mobile health tool for resource-poor settings to assess and manage cardiovascular disease risk: SMARThealth study. BMC Med Inform Decis Mak. 2015 Apr 29;15:36. doi: 10.1186/s12911-015-0148-4. PubMed 25924825 ↗
  • Chen D, Zhang H, Wu J, Xue E, Guo P, Tang L, Shao J, Cui N, Wang X, Chen L, Ye Z. Effects of an Individualized mHealth-Based Intervention on Health Behavior Change and Cardiovascular Risk Among People With Metabolic Syndrome Based on the Behavior Change Wheel: Quasi-Experimental Study. J Med Internet Res. 2023 Nov 29;25:e49257. doi: 10.2196/49257. PubMed 38019579 ↗
  • Zhang N, Zhou M, Li M, Ma G. Effects of Smartphone-Based Remote Interventions on Dietary Intake, Physical Activity, Weight Control, and Related Health Benefits Among the Older Population With Overweight and Obesity in China: Randomized Controlled Trial. J Med Internet Res. 2023 Apr 28;25:e41926. doi: 10.2196/41926. PubMed 37115608 ↗

Individual participant data

Plan to share: Undecided

08

Registry details

Key details

Study ID
NCT07400549
Lead sponsor
China National Center for Cardiovascular Diseases
Responsible party
Sponsor
First posted
Feb 10, 2026
Start date
Jun 1, 2025
Primary completion
Feb 1, 2026 (estimated)
Completion
Mar 1, 2026 (estimated)
Last update
Feb 10, 2026

Study contacts

Tian
Contact
sigaoresearch@163.com
86+ 88319206

Oversight

Data monitoring committee
Yes
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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