Taining Golden Lake Comprehensive Chronic Disease Management Initiative

Overview

This study aims to establish the first county-level, population-based prospective cohort in Taining County, Fujian Province, China. The cohort will include at least 20,000 residents aged 18 years or older. The project will systematically collect questionnaires, physical measurements, laboratory tests, imaging data, and biological samples to build a multi-dimensional health database and biobank. Through 3-year follow-up, the study seeks to reveal the epidemiological patterns and risk factors of chronic diseases, characterize the natural course of multimorbidity and aging syndromes, and develop a comprehensive chronic disease management model suitable for rural and mountainous regions.

Detailed description

China is undergoing rapid population aging, with chronic non-communicable diseases (NCDs) becoming the leading cause of death and disability. Taining County, located in a mountainous area of Fujian Province, faces a higher-than-average aging population and a growing burden of hypertension, diabetes, dyslipidemia, and cardiovascular diseases. Early detection and standardized management remain insufficient, and healthcare resources are limited. This study will establish a prospective cohort covering ≥20,000 residents, integrating demographic, lifestyle, clinical, laboratory, and imaging data. Active follow-up will be conducted annually, complemented by passive follow-up through local healthcare and death registry systems. The study will (1) identify epidemiological features and risk factors of common chronic diseases, (2) explore multimorbidity and aging trajectories, and (3) develop a replicable "Taining Model" for chronic disease prevention and management at the county level. The results will provide an evidence base for public health decision-making and chronic disease control strategies in similar rural and mountainous regions.

Primary outcome measures

• Incidence of Major Adverse Cardiovascular Events (MACE) [Time frame: Up to 36 months]

Secondary outcome measures (7)

• Incidence of Cardiovascular and Cerebrovascular Events [Time frame: Up to 36 months]
• Heart Failure-Related Rehospitalization Rate [Time frame: Up to 36 months]
• Bleeding Events [Time frame: Up to 36 months]
• Health Economics Outcomes [Time frame: Up to 36 months]
• Cognitive Function Outcomes [Time frame: Baseline and annual follow-up (Year 1-3)]
• Cancer Incidence and Cancer-Related Outcomes [Time frame: Up to 36 months]
• All-Cause Mortality [Time frame: Up to 36 months]

Eligibility criteria

Inclusion criteria

• Age ≥18 years, male or female.
• Resident of Taining County for ≥6 months and expected to remain in the county for at least the next 3 years.
• Full civil capacity and able to understand study procedures.
• Willing to voluntarily participate and provide written informed consent.
• Able to complete baseline survey and follow-up visits.

Exclusion criteria

• Refusal to sign informed consent.
• Severe psychiatric disorders or cognitive impairment preventing participation.
• End-stage disease with expected survival <1 year.
• Long-term migrants (≥6 months per year outside the county), unable to guarantee follow-up.
• Participation in other clinical studies that may interfere with this research.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: Yes

Study design

Observational model

Cohort

Study locations

China · 1 center

• The First Affiliated Hospital of Fujian Medical University — Fuzhou

Publications

• Chen L, Li X, Lv Y, Tan X, Zhong VW, Rong S, Liu G, Liu L. Physical frailty, adherence to ideal cardiovascular health and risk of cardiovascular disease: a prospective cohort study. Age Ageing. 2023 Jan 8;52(1):afac311. doi: 10.1093/ageing/afac311. PMID 36626327
• Hu L, Li J, Tang Z, Gong P, Chang Z, Yang C, Ma T, Jiang S, Yang C, Zhang T. How does biological age acceleration mediate the associations of obesity with cardiovascular disease? Evidence from international multi-cohort studies. Cardiovasc Diabetol. 2025 May 14;24(1):209. doi: 10.1186/s12933-025-02770-0. PMID 40369582
• Global Cardiovascular Risk Consortium; Magnussen C, Ojeda FM, Leong DP, Alegre-Diaz J, Amouyel P, Aviles-Santa L, De Bacquer D, Ballantyne CM, Bernabe-Ortiz A, Bobak M, Brenner H, Carrillo-Larco RM, de Lemos J, Dobson A, Dorr M, Donfrancesco C, Drygas W, Dullaart RP, Engstrom G, Ferrario MM, Ferrieres J, de Gaetano G, Goldbourt U, Gonzalez C, Grassi G, Hodge AM, Hveem K, Iacoviello L, Ikram MK, Ir PMID 37632466
• Moturi S, Ghosh-Choudhary SK, Finkel T. Cardiovascular disease and the biology of aging. J Mol Cell Cardiol. 2022 Jun;167:109-117. doi: 10.1016/j.yjmcc.2022.04.005. Epub 2022 Apr 11. PMID 35421400
• Liberale L, Badimon L, Montecucco F, Luscher TF, Libby P, Camici GG. Inflammation, Aging, and Cardiovascular Disease: JACC Review Topic of the Week. J Am Coll Cardiol. 2022 Mar 1;79(8):837-847. doi: 10.1016/j.jacc.2021.12.017. PMID 35210039
• Hu C. Prevention of cardiovascular disease for healthy aging and longevity: A new scoring system and related "mechanisms-hallmarks-biomarkers". Ageing Res Rev. 2025 May;107:102727. doi: 10.1016/j.arr.2025.102727. Epub 2025 Mar 15. PMID 40096912
• da Silva PFL, Schumacher B. Principles of the Molecular and Cellular Mechanisms of Aging. J Invest Dermatol. 2021 Apr;141(4S):951-960. doi: 10.1016/j.jid.2020.11.018. Epub 2021 Jan 29. PMID 33518357
• Moqri M, Herzog C, Poganik JR; Biomarkers of Aging Consortium; Justice J, Belsky DW, Higgins-Chen A, Moskalev A, Fuellen G, Cohen AA, Bautmans I, Widschwendter M, Ding J, Fleming A, Mannick J, Han JJ, Zhavoronkov A, Barzilai N, Kaeberlein M, Cummings S, Kennedy BK, Ferrucci L, Horvath S, Verdin E, Maier AB, Snyder MP, Sebastiano V, Gladyshev VN. Biomarkers of aging for the identification and evalu PMID 37657418

Identifiers

NCT: NCT07308314 · MRCTA,ECFAH of FMU[2025]950

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗