Guangzhou Nutrition and Health Study (GNHS)

NCT ID: NCT03179657

Last Updated: 2022-12-27

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

5118 participants

Study Classification

OBSERVATIONAL

Study Start Date

2008-07-01

Study Completion Date

2027-12-31

Brief Summary

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Purpose: The Guangzhou Nutrition and Health Study (GNHS) project aims to assess the determinants of metabolic disease in nutritional aspects, as well as other environmental and genetic factors, and explore possible mechanisms with multi-omics integration.

Study design: GNHS is a community-based prospective cohort study. Participants: In this cohort, the original GNHS and another cohort study (the controls of a case-control study of hip fractures, CCFH) have been integrated into the one GNHS project. After completing the baseline examination, a total of 5118 participants were recruited during 2008-2015 in the GNHS project.

Visits and Data Collection: Participants were/will be visited every three years by invited to the School of Public Health, Sun Yat-sen University. At each visit, face-to-face interviews, specimen collection, anthropometric measurements, dual-energy x-ray absorptiometry (DXA) scanning, ultrasonography evaluation, vascular endothelial function evaluation, cardiopulmonary exercise testing, magnetic resonance imaging (MRI), 14-d real-time continuous glucose monitoring tests, laboratory tests, and multi-omics data were/will be conducted. Up to December 2022, 3442 and 2895 subjects completed the 2nd and 3rd visits.

Key variables:

1. Questionnaire interviews.
2. Physical examinations: Anthropometric measurements, blood pressure tests, handgrip strength, muscle function and bracelet motion monitoring.
3. DXA scanning: To determine bone density, bone mineral content, bone geometry information, fat mass, and muscle mass.
4. Ultrasonography evaluations: To determine carotid artery intima-media thickness and plaque, and fatty liver.
5. Vascular endothelial function evaluation.
6. Cardiopulmonary exercise testing: Lung function.
7. MRI: Brain and upper-abdomen MRI.
8. 14-d Real-time continuous glucose monitoring tests.
9. Specimen collections: Overnight fasting blood, early morning first-void urine, faces, and saliva samples.
10. Laboratory tests: Metabolic syndrome-related indices; Diabetes-related indices; Uric acid; Nutritional indices; Inflammatory cytokines; Index of oxidative stress; Adipocytes; Sexual hormones; Liver and renal function-related markers; Routine blood test.
11. Multi-omics data: Genotyping data; Gut microbiota; Untargeted serum and fecal proteomics; Targeted serum and fecal metabolomics.
12. Morbidity and mortality: Relevant data were/will be also retrieved via local multiple health information systems.

Detailed Description

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Purpose: The Guangzhou Nutrition and Health Study (GNHS) aims to assess the determinants of risk of metabolic diseases and changes in their relevant indices (e.g., osteoporosis, atherosclerosis, type 2 diabetes, hypertension, metabolic syndrome, non-alcoholic fatty liver disease, cardiovascular diseases, chronic kidney disease, body composition, lung function, cognition function, etc.) in nutritional aspects, as well as other environmental and genetic factors.

Study design: GNHS is a community-based prospective cohort study. Participants: In this cohort, the original GNHS and another cohort study (the controls of a case-control study of hip fractures, CCFH) have been integrated into the one GNHS project. About 4048 apparently healthy residents (aged 40-80 years) in the original GNHS were recruited between 2008 and 2013, and 1070 participants in the CCFH baseline (52-83 years old) were recruited from 2009 to 2015, all living in Guangzhou city (South China) for \>5 years. After completing the baseline examination, a total of 5118 participants were recruited during 2008-2015 in the GNHS project.

Visits and Data Collection: Participants were/will be visited every three years by invited to the School of Public Health, Sun Yat-sen University. At each visit, face-to-face interviews, specimen collection, anthropometric measurements, DXA scanning, ultrasonography evaluation, vascular endothelial function evaluation, cardiopulmonary exercise testing, MRI, 14-d real-time continuous glucose monitoring tests, laboratory tests, and multi-omics data were/will be conducted. Up to December 2022, 3442 and 2895 subjects completed the 2nd and 3rd visits. The 4th visit began in 2017 and has been ongoing, and 2243 participants have been revisited so far. About 1500 participants responded in 2020-now at the 5th visit. It is planned to follow up the participant in person for at least 15 years.

Key variables:

1. Questionnaire interviews: Structured questionnaires were/will be used to collect the participants' socio-demographic characteristics (e.g., age, sex and household income), lifestyle factors (smoking, passive smoking, alcohol drinking, tea drinking, physical activity), menstruation and reproductive history (women only), sleep quality (Pittsburgh Sleep Quality Index, PSQI), family history, psychological health (Self-Rating Anxiety Scale, SAS), Simplified Geriatric Depression Scale (GDS), social support and participation, cognitive function (Mini-Mental State Examinations (MMSE), and Addenbrooke's cognitive examination (ACE)), habitual dietary intake (a validated 79-item quantitative food frequency questionnaire), use of supplements and history of chronic diseases.
2. Physical examinations: Anthropometric measurements (weight, height, waist, hip and neck circumference, etc.), blood pressure tests, handgrip strength, muscle function and bracelet motion monitoring.
3. DXA scanning: A dual-energy x-ray absorptiometry (DXA, Discovery W; Hologic Inc.) was/will be used to determine bone density and bone mineral content at the whole body, lumbar spine (L1-L4), left hip sites, bone geometry information at the hip, fat mass and muscle mass at total body and its sub-regions.
4. Ultrasonography evaluations: Ultrasonography evaluation of the carotid artery and upper abdominal organs (e.g., liver and kidney) was/will be performed to determine carotid artery intima-media thickness and plaque, fatty liver.
5. Vascular endothelial function evaluation: Blood flow-mediated vasodilation.
6. Cardiopulmonary exercise testing: Lung function.
7. MRI: Magnetic resonance imaging in the brain was/will be used to study brain tissue's microstructure and investigate brain function. Upper-abdomen MRI was/will be conducted to assess the structure and contents of fat and iron of the liver, fat and muscle mass, and vertebral bone marrow fat, and help to identify renal angiomyolipoma and malignant renal tumours.
8. 14-d Real-time continuous glucose monitoring tests: A 14-d continuous glucose monitoring was used to determine glycemic responses to various usual daily foods (by a 7-d image-based food diary) using 3-type standard breakfast as internal calibrators.
9. Specimen collections: Overnight fasting blood sample was/will be collected and separated into serum, plasma, erythrocyte and leukocyte within two hours. Early morning first-void urine, faces, and saliva samples were/will be collected, separated and stored at -80°C till tests.
10. Laboratory tests:

1. Fasting serum lipid profile.
2. Diabetes-related indices; fasting glucose, insulin, HbA1c, and fructosamine.
3. Uric acid.
4. Nutritional indices: fatty acids, vitamins, minerals, alkaloids, carotenoids, flavonoids, sulfur-containing amino acids and so on.
5. Inflammatory cytokines.
6. Index of oxidative stress.
7. Adipocytes.
8. Sexual hormones.
9. Liver and renal function-related markers.
10. Routine blood test.
11. Multi-omics data:

1. Genotyping data (Illumina Asian Screening-750000 arrays).
2. Gut microbiota: 16S ribosomal RNA, metagenome, and internal transcribed spacer 2 (ITS2) sequencing.
3. Untargeted serum and fecal proteomics: about 430 unique human protein groups in serum, 1253 human protein and 83683 microbial proteins in feces.
4. Targeted serum and fecal metabolomics: amino acids, benzenoid, bile acids, carbohydrates, carnitines, fatty acids, indoles, nucleosides, organic acids, organooxygen compounds, phenylpropanoic acids, pyridines and so on. Approximately 200 metabolites have been quantified so far.
12. Morbidity and mortality: Relevant data were/will be also retrieved via local multiple health information systems.
13. Others: Many other laboratory tests or instrument tests will be developed depending on needs and resources in future.

Data analysis: Analyses of variance and covariance, or mixed effects model were/will be used to compare the mean differences in continuous outcomes (e.g., changes of bone mineral density, body fat mass, or intima-media thickness) among the quartiles. Cox proportional hazards or logistic regression models were/will be used to assess the risk of exposures (e.g., nutrition intakes and physical activity) on categorical outcomes. Path analysis was/will be used to assess the potential mediating effects in the causal pathway between exposures and outcomes.

Conditions

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Cardiovascular Diseases Osteoporosis Diabetes Mellitus, Type 2 Metabolic Syndrome Obesity Hypertension Non-Alcoholic Fatty Liver Disease Chronic Kidney Diseases Cancer Death Nutrition Disorders Sarcopenia

Keywords

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Prospective Cohort study Nutrition Diet Multi-omics Metabolic diseases Guangzhou Chinese

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Age: 40-80 years (the original GNHS) and 40-85 years (CCFH) at baseline;
* Living in Guangzhou for at least five years;
* Chinese.

Exclusion Criteria

* Had a history of hospital-confirmed diabetes, failure(s) of heart, liver, or kidney, cancer, cardiovascular events, metabolic bone diseases, glucocorticoid use (over 3 mo.) or sexual hormone use (over 6 mo.), spine or hip fractures;

On special diet due to a disease or weight control;

* Mental and physical disability;
* Likely to move to other city within 5 years;
* Did not want to attend any one item of the survey or sample collection.
Minimum Eligible Age

40 Years

Maximum Eligible Age

83 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Sun Yat-sen University

OTHER

Sponsor Role lead

Responsible Party

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Yu-ming Chen

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Yuming Chen

Role: PRINCIPAL_INVESTIGATOR

Sun Yat-sen University

References

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Li Z, Huang BX, Huang ZH, Li MC, Chen YM, Zhu HL. Exploring the link between serum betaine levels and hyperuricemia risk in middle-aged and older adults: insights from a prospective cohort study. Eur J Nutr. 2025 Feb 1;64(2):77. doi: 10.1007/s00394-025-03594-0.

Reference Type DERIVED
PMID: 39891737 (View on PubMed)

Xie K, Xiao C, Lin L, Li F, Hu W, Yang Y, Chen D, Miao Z, Sun TY, Yan Y, Zheng JS, Chen YM. Erythrocyte Very Long-Chain Saturated Fatty Acids, Gut Microbiota-Bile Acid Axis, and Incident Coronary Artery Disease in Adults: A Prospective Cohort Study. J Nutr. 2024 Oct;154(10):3019-3030. doi: 10.1016/j.tjnut.2024.08.005. Epub 2024 Aug 10.

Reference Type DERIVED
PMID: 39128547 (View on PubMed)

Chen S, Chen XY, Huang ZH, Fang AP, Li SY, Huang RZ, Chen YM, Huang BX, Zhu HL. Correlation between serum trimethylamine-N-oxide and body fat distribution in middle-aged and older adults: a prospective cohort study. Nutr J. 2024 Jul 9;23(1):70. doi: 10.1186/s12937-024-00974-w.

Reference Type DERIVED
PMID: 38982486 (View on PubMed)

Chen S, Lin X, Ma J, Li M, Chen Y, Fang AP, Zhu HL. Dietary protein intake and changes in muscle mass measurements in community-dwelling middle-aged and older adults: A prospective cohort study. Clin Nutr. 2023 Dec;42(12):2503-2511. doi: 10.1016/j.clnu.2023.10.017. Epub 2023 Oct 22.

Reference Type DERIVED
PMID: 37922694 (View on PubMed)

Wu YY, Gou W, Yan Y, Liu CY, Yang Y, Chen D, Xie K, Jiang Z, Fu Y, Zhu HL, Zheng JS, Chen YM. Gut microbiota and acylcarnitine metabolites connect the beneficial association between equol and adiposity in adults: a prospective cohort study. Am J Clin Nutr. 2022 Dec 19;116(6):1831-1841. doi: 10.1093/ajcn/nqac252.

Reference Type DERIVED
PMID: 36095141 (View on PubMed)

Li SY, Chen S, Lu XT, Fang AP, Chen YM, Huang RZ, Lin XL, Huang ZH, Ma JF, Huang BX, Zhu HL. Serum trimethylamine-N-oxide is associated with incident type 2 diabetes in middle-aged and older adults: a prospective cohort study. J Transl Med. 2022 Aug 18;20(1):374. doi: 10.1186/s12967-022-03581-7.

Reference Type DERIVED
PMID: 35982495 (View on PubMed)

Gu Y, Luo J, Chen Q, Qiu Y, Zhou Y, Wang X, Qian X, Liu Y, Xie J, Xu Z, Ling W, Chen Y, Yang L. Inverse Association of Serum Adipsin with the Remission of Nonalcoholic Fatty-Liver Disease: A 3-Year Community-Based Cohort Study. Ann Nutr Metab. 2022;78(1):21-32. doi: 10.1159/000520368. Epub 2021 Nov 23.

Reference Type DERIVED
PMID: 34814152 (View on PubMed)

Deng YY, Zhong QW, Zhong HL, Xiong F, Ke YB, Chen YM. Higher Healthy Lifestyle Score is associated with lower presence of non-alcoholic fatty liver disease in middle-aged and older Chinese adults: a community-based cross-sectional study. Public Health Nutr. 2021 Oct;24(15):5081-5089. doi: 10.1017/S1368980021000902. Epub 2021 Feb 26.

Reference Type DERIVED
PMID: 33634772 (View on PubMed)

Xiao ML, Lin JS, Li YH, Liu M, Deng YY, Wang CY, Chen YM. Adherence to the Dietary Approaches to Stop Hypertension (DASH) diet is associated with lower presence of non-alcoholic fatty liver disease in middle-aged and elderly adults. Public Health Nutr. 2020 Mar;23(4):674-682. doi: 10.1017/S1368980019002568. Epub 2019 Sep 30.

Reference Type DERIVED
PMID: 31566148 (View on PubMed)

Dong HL, Tang XY, Deng YY, Zhong QW, Wang C, Zhang ZQ, Chen YM. Urinary equol, but not daidzein and genistein, was inversely associated with the risk of type 2 diabetes in Chinese adults. Eur J Nutr. 2020 Mar;59(2):719-728. doi: 10.1007/s00394-019-01939-0. Epub 2019 Apr 5.

Reference Type DERIVED
PMID: 30953148 (View on PubMed)

Chen ZY, Liu M, Jing LP, Xiao ML, Dong HL, Chen GD, Chen YM. Erythrocyte membrane n-3 polyunsaturated fatty acids are inversely associated with the presence and progression of nonalcoholic fatty liver disease in Chinese adults: a prospective study. Eur J Nutr. 2020 Apr;59(3):941-951. doi: 10.1007/s00394-019-01953-2. Epub 2019 Apr 1.

Reference Type DERIVED
PMID: 30937580 (View on PubMed)

Xiao ML, Chen GD, Zeng FF, Qiu R, Shi WQ, Lin JS, Cao Y, Li HB, Ling WH, Chen YM. Higher serum carotenoids associated with improvement of non-alcoholic fatty liver disease in adults: a prospective study. Eur J Nutr. 2019 Mar;58(2):721-730. doi: 10.1007/s00394-018-1678-1. Epub 2018 Mar 29.

Reference Type DERIVED
PMID: 29594435 (View on PubMed)

Other Identifiers

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2007032

Identifier Type: -

Identifier Source: org_study_id