Associations Between Tea and Sweetened Beverage Consumptions and Hyperuricemia: The China Health and Nutrition Survey

NCT03235336 | Unknown DMC

• 1 other identifier: N1706-3431
• Study Type: observational
• Target: 5,547
• Locations: 1 country
• Sites: 1

Brief Summary

The China Health and Nutrition Survey (CHNS), an ongoing open cohort, international collaborative project between the Carolina Population Center at the University of North Carolina at Chapel Hill and the National Institute for Nutrition and Health (NINH, former National Institute of Nutrition and Food Safety) at the Chinese Center for Disease Control and Prevention (CCDC), was designed to examine the effects of the health, nutrition, and family planning policies and programs implemented by national and local governments and to see how the social and economic transformation of Chinese society is affecting the health and nutritional status of its population. The impact on nutrition and health behaviors and outcomes is gauged by changes in community organizations and programs as well as by changes in sets of household and individual economic, demographic, and social factors. The survey was conducted by an international team of researchers whose backgrounds include nutrition, public health, economics, sociology, Chinese studies, and demography. The survey took place over a 7-day period using a multistage, random cluster process to draw a sample of about 7,200 households with over 30,000 individuals in 15 provinces and municipal cities that vary substantially in geography, economic development, public resources, and health indicators. In addition, detailed community data were collected in surveys of food markets, health facilities, family planning officials, and other social services and community leaders.

Conditions

Nutrition Poor

Outcome Measures

Primary Outcomes (1)

• Hyperuricemia

  Serum uric acid level ≥420 μmol/L in males and ≥360 μmol/L in females

  1997-2009

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

This study analyzed the participant data from the Chinese Health and Nutrition Survey (CHNS, http://www.cpc.unc.edu/projects/china), which covered nine Chinese provinces (Heilongjiang, Liaoning, Shandong, Henan, Jiangsu, Hubei, Hunan, Guizhou, and Guangxi). The CHNS used a multistage random cluster sampling method.

You may qualify if:

• reported no endocrinal and rheumatological disease at baseline
• provided valid responses regarding tea consumption, soft drink consumption, and sweetened fruit drink consumption,
• provided blood samples with valid serum uric acid data

Sponsors & Collaborators

• The Hong Kong Polytechnic University: lead
• Fogarty International Center of the National Institute of Health: collaborator
• China-Japan Friendship Hospital: collaborator
• Beijing Center for Disease Control and Prevention: collaborator
• University of North Carolina, Chapel Hill: collaborator

Study Sites (1)

Sichuan Hospital

Chengdu, Sichuan, China

RECRUITING

Related Publications (1)

• Popkin BM, Du S, Zhai F, Zhang B. Cohort Profile: The China Health and Nutrition Survey--monitoring and understanding socio-economic and health change in China, 1989-2011. Int J Epidemiol. 2010 Dec;39(6):1435-40. doi: 10.1093/ije/dyp322. Epub 2009 Nov 3. No abstract available.

  PMID: 19887509 RESULT

Related Links

• Related Info

MeSH Terms

Conditions

Malnutrition

Condition Hierarchy (Ancestors)

Nutrition Disorders; Nutritional and Metabolic Diseases

Central Study Contacts

Paul H Lee, PhD

CONTACT

34008275; paul.h.lee@polyu.edu.hk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 27, 2017
• First Posted: August 1, 2017
• Study Start: January 1, 1989
• Primary Completion: December 1, 2020
• Study Completion: December 1, 2020
• Last Updated: February 22, 2019

Record last verified: 2019-02

Data Sharing

• IPD Sharing: Will share

Locations

CN (1)