Introduction to the application of NHANES data weights: implementation in R programming language_Chinese Journal of Evidence-Based Medicine

Authors：

WANG Yang , YANG Zhongli , LI Daiping ,  DONG Birong

National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu 610041, P. R. China;

Corresponding author：

DONG Birong, Email: birongdong123@outlook.com

Keywords：

National health and nutrition; NHANES; Weights; Statistical analysis; R programming language

DOI：

10.7507/1672-2531.202407143

Video：

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The National Health and Nutrition Examination Survey (NHANES) in the United States is a research program designed to assess the health and nutritional status of adults and children in the country. Due to its adoption of a complex sampling design, it is imperative to correctly apply the weights provided by NHANES to ensure the accuracy and external validity of research results. This article first introduces the relevant concepts of the NHANES database and its weights, followed by a practical demonstration of weight selection, calculation, and implementation in the R programming language. It further discusses the significance of using weights in NHANES data and systematically showcases how to perform weighted analysis based on R, providing a valuable reference for relevant researchers.

Citation： WANG Yang, YANG Zhongli, LI Daiping, DONG Birong. Introduction to the application of NHANES data weights: implementation in R programming language. Chinese Journal of Evidence-Based Medicine, 2025, 25(6): 732-738. doi: 10.7507/1672-2531.202407143 Copy

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2.	Kabbany MN, Conjeevaram Selvakumar PK, Watt K, et al. Prevalence of nonalcoholic steatohepatitis-associated cirrhosis in the United States: an analysis of national health and nutrition examination survey data. Am J Gastroenterol, 2017, 112(4): 581-587.
3.	Ahluwalia N, Dwyer J, Terry A, et al. Update on NHANES dietary data: focus on collection, release, analytical considerations, and uses to inform public policy. Adv Nutr, 2016, 7(1): 121-134.
4.	涂吉, 何慧婧, 胡耀达, 等. 美国国家健康与营养调查中的信息化系统应用及启示. 中华流行病学杂志, 2022, 43(7): 1127-1133.
5.	韦葵葵, 巩浩雯, 刘玉秀, 等. 中美韩健康与营养调查数据库建设与应用研究. 中国全科医学, 2024, 27(3): 375-380.
6.	Bin Zarah A, Andrade JM. Elevated inflammation and poor diet quality associated with lower eGFR in United States adults: an NHANES 2015-2018 analysis. Nutrients, 2024, 16(4): 528.
7.	Wang X, Han X, Guo S, et al. Associations between patterns of blood heavy metal exposure and health outcomes: insights from NHANES 2011-2016. BMC Public Health, 2024, 24(1): 558.
8.	Wang K, Deng M, Wu J, et al. Associations of oxidative balance score with total abdominal fat mass and visceral adipose tissue mass percentages among young and middle-aged adults: findings from NHANES 2011-2018. Front Nutr, 2023, 10: 1306428.
9.	Tattersall MC, Karmali KN, Gangnon RE, et al. The population effects of the global cardiovascular risk model in United States adults: findings from the national health and nutrition surveys, 2005-2006. J Clin Lipidol, 2011, 5(3): 166-172.
10.	Paulose-Ram R, Burt V, Broitman L, et al. Overview of Asian American data collection, release, and analysis: national health and nutrition examination survey 2011-2018. Am J Public Health, 2017, 107(6): 916-921.
11.	Liao J, Hu M, Imm K, et al. Association of daily sitting time and leisure-time physical activity with body fat among U. S. adults. J Sport Health Sci, 2024, 13(2): 195-203.
12.	Wang L, Li X, Wang Z, et al. Trends in prevalence of diabetes and control of risk factors in diabetes among US adults, 1999-2018. JAMA, 2021, 326(8): 1-13.
13.	Akinbami LJ, Chen TC, Davy O, et al. National health and nutrition examination survey, 2017-march 2020 prepandemic file: sample design, estimation, and analytic guidelines. Vital Health Stat 1, 2022, 190: 1-36.
14.	Johnson CL, Paulose-Ram R, Ogden CL, et al. National health and nutrition examination survey: analytic guidelines, 1999-2010. Vital Health Stat 2, 2013, 161: 1-24.
15.	Zipf G, Chiappa M, Porter KS, et al. National health and nutrition examination survey: plan and operations, 1999-2010. Vital Health Stat 1, 2013, 56: 1-37.
16.	Liu C, Liang D, Xiao K, et al. Association between the triglyceride-glucose index and all-cause and CVD mortality in the young population with diabetes. Cardiovasc Diabetol, 2024, 23(1): 171.
17.	郭亚军. 综合评价理论、方法与拓展. 北京: 科学出版社, 2012: 77.
18.	杜栋, 庞庆华. 现代综合评价方法与案例精选. 第4版. 北京: 清华大学出版社, 2021: 8-9.
19.	郭梓鑫, 冯雨嘉, 王清华, 等. 应用R软件 metaplus 程序包实现Meta分析. 中国循证医学杂志, 2018, 18(7): 763-768.
20.	胡建雄, 陈思齐, 刘涛, 等. R语言在公共卫生领域的应用: 基本数据处理. 华南预防医学, 2020, 46(2): 183-184, 188.
21.	Wu M, Si J, Liu Y, et al. Association between composite dietary antioxidant index and hypertension: insights from NHANES. Clin Exp Hypertens, 2023, 45(1): 2233712.
22.	Fryar CD, Kit B, Carroll MD, et al. Hypertension prevalence, awareness, treatment, and control among adults age 18 and older: United States, August 2021–August 2023. NCHS data brief, No. 511. Hyattsville, MD: National Center for Health Statistics. 2024.
23.	Ward ZJ, Gortmaker SL. A rigorous evaluation of a method to adjust BMI for self-report bias. Obesity, 2022, 30(2): 284-285.
24.	Leroux A, Di J, Smirnova E, et al. Organizing and analyzing the activity data in NHANES. Stat Biosci, 2019, 11(2): 262-287.
25.	Yuan M, He J, Hu X, et al. Hypertension and NAFLD risk: insights from the NHANES 2017-2018 and Mendelian randomization analyses. Chin Med J (Engl), 2024, 137(4): 457-464.
26.	李洛华, 蒋红樱. 基于NHANES调查分析慢性肾脏病患者血清25(OH)D与全因死亡和心血管疾病死亡的相关性. 现代预防医学, 2024, 51(9): 1555-1561.
27.	黄宇婷, 王妤, 李雅琴, 等. 膳食氧化平衡评分与慢性肾脏病患者骨质疏松症患病风险的关系. 现代预防医学, 2024, 51(8): 1420-1424, 1446.

1. 郭晓娟, 田国祥, 潘振宇, 等. NHANES项目介绍及数据提取流程. 中国循证心血管医学杂志, 2019, 11(6): 654-657.
2. Kabbany MN, Conjeevaram Selvakumar PK, Watt K, et al. Prevalence of nonalcoholic steatohepatitis-associated cirrhosis in the United States: an analysis of national health and nutrition examination survey data. Am J Gastroenterol, 2017, 112(4): 581-587.
3. Ahluwalia N, Dwyer J, Terry A, et al. Update on NHANES dietary data: focus on collection, release, analytical considerations, and uses to inform public policy. Adv Nutr, 2016, 7(1): 121-134.
4. 涂吉, 何慧婧, 胡耀达, 等. 美国国家健康与营养调查中的信息化系统应用及启示. 中华流行病学杂志, 2022, 43(7): 1127-1133.
5. 韦葵葵, 巩浩雯, 刘玉秀, 等. 中美韩健康与营养调查数据库建设与应用研究. 中国全科医学, 2024, 27(3): 375-380.
6. Bin Zarah A, Andrade JM. Elevated inflammation and poor diet quality associated with lower eGFR in United States adults: an NHANES 2015-2018 analysis. Nutrients, 2024, 16(4): 528.
7. Wang X, Han X, Guo S, et al. Associations between patterns of blood heavy metal exposure and health outcomes: insights from NHANES 2011-2016. BMC Public Health, 2024, 24(1): 558.
8. Wang K, Deng M, Wu J, et al. Associations of oxidative balance score with total abdominal fat mass and visceral adipose tissue mass percentages among young and middle-aged adults: findings from NHANES 2011-2018. Front Nutr, 2023, 10: 1306428.
9. Tattersall MC, Karmali KN, Gangnon RE, et al. The population effects of the global cardiovascular risk model in United States adults: findings from the national health and nutrition surveys, 2005-2006. J Clin Lipidol, 2011, 5(3): 166-172.
10. Paulose-Ram R, Burt V, Broitman L, et al. Overview of Asian American data collection, release, and analysis: national health and nutrition examination survey 2011-2018. Am J Public Health, 2017, 107(6): 916-921.
11. Liao J, Hu M, Imm K, et al. Association of daily sitting time and leisure-time physical activity with body fat among U. S. adults. J Sport Health Sci, 2024, 13(2): 195-203.
12. Wang L, Li X, Wang Z, et al. Trends in prevalence of diabetes and control of risk factors in diabetes among US adults, 1999-2018. JAMA, 2021, 326(8): 1-13.
13. Akinbami LJ, Chen TC, Davy O, et al. National health and nutrition examination survey, 2017-march 2020 prepandemic file: sample design, estimation, and analytic guidelines. Vital Health Stat 1, 2022, 190: 1-36.
14. Johnson CL, Paulose-Ram R, Ogden CL, et al. National health and nutrition examination survey: analytic guidelines, 1999-2010. Vital Health Stat 2, 2013, 161: 1-24.
15. Zipf G, Chiappa M, Porter KS, et al. National health and nutrition examination survey: plan and operations, 1999-2010. Vital Health Stat 1, 2013, 56: 1-37.
16. Liu C, Liang D, Xiao K, et al. Association between the triglyceride-glucose index and all-cause and CVD mortality in the young population with diabetes. Cardiovasc Diabetol, 2024, 23(1): 171.
17. 郭亚军. 综合评价理论、方法与拓展. 北京: 科学出版社, 2012: 77.
18. 杜栋, 庞庆华. 现代综合评价方法与案例精选. 第4版. 北京: 清华大学出版社, 2021: 8-9.
19. 郭梓鑫, 冯雨嘉, 王清华, 等. 应用R软件 metaplus 程序包实现Meta分析. 中国循证医学杂志, 2018, 18(7): 763-768.
20. 胡建雄, 陈思齐, 刘涛, 等. R语言在公共卫生领域的应用: 基本数据处理. 华南预防医学, 2020, 46(2): 183-184, 188.
21. Wu M, Si J, Liu Y, et al. Association between composite dietary antioxidant index and hypertension: insights from NHANES. Clin Exp Hypertens, 2023, 45(1): 2233712.
22. Fryar CD, Kit B, Carroll MD, et al. Hypertension prevalence, awareness, treatment, and control among adults age 18 and older: United States, August 2021–August 2023. NCHS data brief, No. 511. Hyattsville, MD: National Center for Health Statistics. 2024.
23. Ward ZJ, Gortmaker SL. A rigorous evaluation of a method to adjust BMI for self-report bias. Obesity, 2022, 30(2): 284-285.
24. Leroux A, Di J, Smirnova E, et al. Organizing and analyzing the activity data in NHANES. Stat Biosci, 2019, 11(2): 262-287.
25. Yuan M, He J, Hu X, et al. Hypertension and NAFLD risk: insights from the NHANES 2017-2018 and Mendelian randomization analyses. Chin Med J (Engl), 2024, 137(4): 457-464.
26. 李洛华, 蒋红樱. 基于NHANES调查分析慢性肾脏病患者血清25(OH)D与全因死亡和心血管疾病死亡的相关性. 现代预防医学, 2024, 51(9): 1555-1561.
27. 黄宇婷, 王妤, 李雅琴, 等. 膳食氧化平衡评分与慢性肾脏病患者骨质疏松症患病风险的关系. 现代预防医学, 2024, 51(8): 1420-1424, 1446.

Chinese Journal of Evidence-Based Medicine

Introduction to the application of NHANES data weights: implementation in R programming language

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