Literature DB >> 28298273

Challenges and Lessons Learned in Generating and Interpreting NHANES Nutritional Biomarker Data.

Christine M Pfeiffer1, David A Lacher2, Rosemary L Schleicher3, Clifford L Johnson2, Elizabeth A Yetley4.   

Abstract

For the past 45 y, the National Center for Health Statistics at the CDC has carried out nutrition surveillance of the US population by collecting anthropometric, dietary intake, and nutritional biomarker data, the latter being the focus of this publication. The earliest biomarker testing assessed iron and vitamin A status. With time, a broad spectrum of water- and fat-soluble vitamins was added and biomarkers for other types of nutrients (e.g., fatty acids) and bioactive dietary compounds (e.g., phytoestrogens) were included in NHANES. The cross-sectional survey is flexible in design, and biomarkers may be measured for a short period of time or rotated in and out of surveys depending on scientific needs. Maintaining high-quality laboratory measurements over extended periods of time such that trends in status can be reliably assessed is a major goal of the testing laboratories. Physicians, health scientists, and policy makers rely on the NHANES reference data to compare the nutritional status of population groups, to assess the impact of various interventions, and to explore associations between nutritional status and health promotion or disease prevention. Focusing on the continuous NHANES, which started in 1999, this review uses a "lessons learned" approach to present a series of challenges that are relevant to researchers measuring biomarkers in NHANES and beyond. Some of those challenges are the use of multiple related biomarkers instead of a single biomarker for a specific nutrient (e.g., folate, vitamin B-12, iron), adhering to special needs for specimen collection and handling to ensure optimum specimen quality (e.g., vitamin C, folate, homocysteine, iodine, polyunsaturated fatty acids), the retrospective use of long-term quality-control data to correct for assay shifts (e.g., vitamin D, vitamin B-12), and the proper planning for and interpretation of crossover studies to adjust for systematic method changes (e.g., folate, vitamin D, ferritin).
© 2017 American Society for Nutrition.

Entities:  

Keywords:  biochemical indicator; biological specimen; cutoff; fat-soluble vitamin; iron-status indicator; national nutrition survey; water-soluble vitamin

Mesh:

Substances:

Year:  2017        PMID: 28298273      PMCID: PMC5347107          DOI: 10.3945/an.116.014076

Source DB:  PubMed          Journal:  Adv Nutr        ISSN: 2161-8313            Impact factor:   8.701


  69 in total

1.  Dietary reference intakes: vitamin A, vitamin K, arsenic, boron, chromium, copper, iodine, iron, manganese, molybdenum, nickel, silicon, vanadium, and zinc.

Authors:  P Trumbo; A A Yates; S Schlicker; M Poos
Journal:  J Am Diet Assoc       Date:  2001-03

2.  Biomarkers of nutritional exposure and nutritional status: an overview.

Authors:  Nancy Potischman; Jo L Freudenheim
Journal:  J Nutr       Date:  2003-03       Impact factor: 4.798

Review 3.  Methodologic and statistical considerations regarding use of biomarkers of nutritional exposure in epidemiology.

Authors:  James R Marshall
Journal:  J Nutr       Date:  2003-03       Impact factor: 4.798

Review 4.  Laboratory issues: use of nutritional biomarkers.

Authors:  Heidi Michels Blanck; Barbara A Bowman; Gerald R Cooper; Gary L Myers; Dayton T Miller
Journal:  J Nutr       Date:  2003-03       Impact factor: 4.798

Review 5.  Biologic and methodologic issues for nutritional biomarkers.

Authors:  Nancy Potischman
Journal:  J Nutr       Date:  2003-03       Impact factor: 4.798

6.  Integrated NHANES: uses in national policy.

Authors:  Catherine E Woteki
Journal:  J Nutr       Date:  2003-02       Impact factor: 4.798

7.  Iron deficiency--United States, 1999-2000.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2002-10-11       Impact factor: 17.586

Review 8.  Update on cobalamin, folate, and homocysteine.

Authors:  Ralph Carmel; Ralph Green; David S Rosenblatt; David Watkins
Journal:  Hematology Am Soc Hematol Educ Program       Date:  2003

9.  Nutrition assessment in the National Health And Nutrition Examination Survey 1999-2002.

Authors:  Jacqueline D Wright; Lori G Borrud; Margaret A McDowell; Chia-Yih Wang; Kathy Radimer; Clifford L Johnson
Journal:  J Am Diet Assoc       Date:  2007-05

10.  The quantitative assessment of body iron.

Authors:  James D Cook; Carol H Flowers; Barry S Skikne
Journal:  Blood       Date:  2003-01-09       Impact factor: 22.113

View more
  6 in total

Review 1.  Framework for laboratory harmonization of folate measurements in low- and middle-income countries and regions.

Authors:  Christine M Pfeiffer; Mindy Zhang; Shameem Jabbar
Journal:  Ann N Y Acad Sci       Date:  2018-01-29       Impact factor: 5.691

Review 2.  Dietary Supplements: Regulatory Challenges and Research Resources.

Authors:  Johanna T Dwyer; Paul M Coates; Michael J Smith
Journal:  Nutrients       Date:  2018-01-04       Impact factor: 5.717

3.  Clinical Relevance of Urine Flow Rate and Exposure to Polycyclic Aromatic Hydrocarbons.

Authors:  Po-Hsuan Jeng; Tien-Ru Huang; Chung-Ching Wang; Wei-Liang Chen
Journal:  Int J Environ Res Public Health       Date:  2021-05-18       Impact factor: 3.390

4.  Clinically-diagnosed vitamin deficiencies and disorders in the entire United States military population, 1997-2015.

Authors:  Joseph J Knapik; Emily K Farina; Victor L Fulgoni; Harris R Lieberman
Journal:  Nutr J       Date:  2021-06-15       Impact factor: 3.271

5.  Interpretation of vitamin B-12 and folate concentrations in population-based surveys does not require adjustment for inflammation: Biomarkers Reflecting Inflammation and Nutritional Determinants of Anemia (BRINDA) project.

Authors:  Melissa F Young; Junjie Guo; Anne Williams; Kyly C Whitfield; Sabiha Nasrin; Vijaya Kancherla; Parminder S Suchdev; Krista S Crider; Christine M Pfeiffer; Mary Serdula
Journal:  Am J Clin Nutr       Date:  2020-04-01       Impact factor: 7.045

6.  Associations between elevated kidney and liver biomarker ratios, metabolic syndrome and all-cause and coronary heart disease (CHD) mortality: analysis of the U.S. National Health and Nutrition Examination Survey (NHANES).

Authors:  Akinkunle Oye-Somefun; Jennifer L Kuk; Chris I Ardern
Journal:  BMC Cardiovasc Disord       Date:  2021-07-26       Impact factor: 2.298

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.