The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Update on NHANES Dietary Data: Focus on Collection, Release, Analytical Considerations, and Uses to Inform Public Policy
Open accessAbstract
NHANES is the cornerstone for national nutrition monitoring to inform nutrition and health policy. Nutritional assessment in NHANES is described with a focus on dietary data collection, analysis, and uses in nutrition monitoring. NHANES has been collecting thorough data on diet, nutritional status, and chronic disease in cross-sectional surveys with nationally representative samples since the early 1970s. Continuous data collection began in 1999 with public data release in 2-y cycles on ∼10,000 participants. In 2002, the Continuing Survey of Food Intakes by Individuals and the NHANES dietary component were merged, forming a consolidated dietary data collection known as What We Eat in America; since then, 24-h recalls have been collected on 2 d using the USDA's Automated Multiple-Pass Method. Detailed and targeted food-frequency questionnaires have been collected in some NHANES cycles. Dietary supplement use data have been collected (in detail since 2007) so that total nutrient intakes can be described for the population. The continuous NHANES can adapt its content to address emerging public health needs and reflect federal priorities. Changes in data collection methods are made after expert input and validation/crossover studies. NHANES dietary data are used to describe intake of foods, nutrients, food groups, and dietary patterns by the US population and large sociodemographic groups to plan and evaluate nutrition programs and policies. Usual dietary intake distributions can be estimated after adjusting for day-to-day variation. NHANES remains open and flexible to incorporate improvements while maintaining data quality and providing timely data to track the nation's nutrition and health status. In summary, NHANES collects dietary data in the context of its broad, multipurpose goals; the strengths and limitations of these data are also discussed in this review.
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Cites
Willett, W. C. (1998) · doi:10.1093/acprof:oso/9780195122978.001.0001 · Cited by 4,541
Principles Of Nutritional Assessment
Gibson, R. S. (2005) · doi:10.1093/oso/9780195171693.001.0001 · Cited by 1,887
The Effect of Social Desirability and Social Approval on Self-Reports of Physical Activity
Adams, S. A. (2005) · American Journal of Epidemiology · doi:10.1093/aje/kwi054 · Cited by 1,160 · cited 1×
“Overall, there is always some error associated with selfreported dietary intakes, as is the case for self-reported data on any variable (44).”
BackgroundPresent Knowledge in Nutrition
(2012) · doi:10.1002/9781119946045 · Cited by 907
Freedman, L. S., Commins, J. M., Moler, J. E., Arab, L., Baer, D. J., Kipnis, V., Midthune, D., Moshfegh, A. J., Neuhouser, M. L., Prentice, R. L., et al. (2014) · American Journal of Epidemiology · doi:10.1093/aje/kwu116 · Cited by 528
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Merli, M., Berzigotti, A., Zelber-Sagi, S., Dasarathy, S., Montagnese, S., Genton, L., Plauth, M., & Parés, A. (2019) · Journal of Hepatology · doi:10.1016/j.jhep.2018.06.024 · Cited by 1,130
Dietary Supplements: Regulatory Challenges and Research Resources
Dwyer, J., Coates, P., & Smith, M. (2018) · Nutrients · doi:10.3390/nu10010041 · Cited by 494
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Chazelas, E., Srour, B., Desmetz, E., Kesse-Guyot, E., Julia, C., Deschamps, V., Druesne-Pecollo, N., Galan, P., Hercberg, S., Latino-Martel, P., et al. (2019) · BMJ · doi:10.1136/bmj.l2408 · Cited by 225
The Development and Evaluation of a Literature-Based Dietary Index for Gut Microbiota
Kase, B. E., Liese, A. D., Zhang, J., Murphy, E. A., Zhao, L., & Steck, S. E. (2024) · Nutrients · doi:10.3390/nu16071045 · Cited by 221
Sun, Y., Liu, B., Rong, S., Du, Y., Xu, G., Snetselaar, L. G., Wallace, R. B., & Bao, W. (2020) · Journal of the American Heart Association · doi:10.1161/jaha.119.014629 · Cited by 210
Neri, D., Steele, E. M., Khandpur, N., Cediel, G., Zapata, M. E., Rauber, F., Marrón‐Ponce, J. A., Machado, P., da Costa Louzada, M. L., Andrade, G. C., et al. (2022) · Obesity Reviews · doi:10.1111/obr.13387 · Cited by 172
Leung, C. W., Fulay, A. P., Parnarouskis, L., Martinez-Steele, E., Gearhardt, A. N., & Wolfson, J. A. (2022) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/nqac049 · Cited by 141
Archer, E., Marlow, M. L., & Lavie, C. J. (2018) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2018.08.003 · Cited by 115
Shostrom, D. C. V., Sun, Y., Oleson, J. J., Snetselaar, L. G., & Bao, W. (2017) · Frontiers in Endocrinology · doi:10.3389/fendo.2017.00144 · Cited by 96
Dietary creatine intake and depression risk among U.S. adults
Bakian, A. V., Huber, R. S., Scholl, L., Renshaw, P. F., & Kondo, D. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0741-x · Cited by 90
Amoutzopoulos, B., Steer, T., Roberts, C., Cade, J. E., Boushey, C. J., Collins, C. E., Trolle, E., Boer, E. J. D., Ziauddeen, N., van Rossum, C., et al. (2018) · Journal of Nutritional Science · doi:10.1017/jns.2018.4 · Cited by 62
Liu, Z., Huang, H., Zeng, Y., Chen, Y., & Xu, C. (2023) · British Journal Of Nutrition · doi:10.1017/s0007114522003956 · Cited by 32
Singleton, C. R., Young, S. K., Kessee, N., Springfield, S. E., & Sen, B. P. (2020) · Preventive Medicine Reports · doi:10.1016/j.pmedr.2020.101134 · Cited by 31
Jiang, N., Zhang, S., Chu, J., Yang, N., & Lu, M. (2023) · Journal of Clinical Laboratory Analysis · doi:10.1002/jcla.24973 · Cited by 20
Metadata
- Authors
- Ahluwalia, N., Dwyer, J., Terry, A., Moshfegh, A., & Johnson, C.
- Venue
- Advances in Nutrition
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 7
- Issue
- 1
- Pages
- 121-134
- ISSN
- 2156-5376 (ISSN-L)
- 2161-8313
- OpenAlex
- W2269476273
- Cited by
- 1,055
- References
- 5
- FWCI
- 42.02
- Type
- journal article
- Language
- en
- Open access
- hybrid
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