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A Comparison of National Estimates from the National Health Interview Survey and the Behavioral Risk Factor Surveillance System

Author

Listed:
  • Nelson, D.E.
  • Powell-Griner, E.
  • Town, M.
  • Kovar, M.G.

Abstract

Objectives. The purpose of this study was to compare national estimates from the National Health Interview Survey (NHIS) and the Behavioral Risk Factor Surveillance System (BRFSS). Methods. The authors compared data from the 2 surveys on smoking, height, weight, body mass index, diabetes, hypertension, immunization, lack of insurance coverage, cost as a barrier to medical care, and health status. Results. Overall national estimates were similar for 13 of the 14 measures examined. Small differences according to demographic characteristics were found for height and body mass index, with larger differences for health status. Conclusions. Although estimates differed within subgroups, the BRFSS provided national estimates comparable to those of the NHIS. BRFSS national data could provide rapidly available information to guide national policy and program decisions.

Suggested Citation

  • Nelson, D.E. & Powell-Griner, E. & Town, M. & Kovar, M.G., 2003. "A Comparison of National Estimates from the National Health Interview Survey and the Behavioral Risk Factor Surveillance System," American Journal of Public Health, American Public Health Association, vol. 93(8), pages 1335-1341.
    • Handle: RePEc:aph:ajpbhl:2003:93:8:1335-1341_0
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    Cited by:

    1. Towne, Samuel D. & Probst, Janice C. & Hardin, James W. & Bell, Bethany A. & Glover, Saundra, 2017. "Health & access to care among working-age lower income adults in the Great Recession: Disparities across race and ethnicity and geospatial factors," Social Science & Medicine, Elsevier, vol. 182(C), pages 30-44.
    2. Chaoyang Li & Earl Ford & Guixiang Zhao & James Tsai & Lina Balluz, 2012. "A comparison of depression prevalence estimates measured by the Patient Health Questionnaire with two administration modes: computer-assisted telephone interviewing versus computer-assisted personal i," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 57(1), pages 225-233, February.
    3. Timothy J. Grigsby & Krista Howard & Jeffrey T. Howard, 2022. "Comparison of Past Year Substance Use Estimates by Age, Sex, and Race/Ethnicity Between Two Representative Samples of the U.S. Adult Population," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(1), pages 401-416, February.
    4. Zhihui Jia & Xiaotong Wen & Feiyu Chen & Hui Zhu & Can Li & Yixiang Lin & Xiaoxu Xie & Zhaokang Yuan, 2020. "Cumulative Exposure to Adverse Childhood Experience: Depressive Symptoms, Suicide Intensions and Suicide Plans among Senior High School Students in Nanchang City of China," IJERPH, MDPI, vol. 17(13), pages 1-13, June.
    5. Tatjana Miljkovic & Saleem Shaik & Dragan Miljkovic, 2017. "Redefining standards for body mass index of the US population based on BRFSS data using mixtures," Journal of Applied Statistics, Taylor & Francis Journals, vol. 44(2), pages 197-211, January.
    6. Connor Sheehan & Anna Zajacova & Dylan Connor & Jennifer Karas Montez, 2022. "State-Level Variation in the Association Between Educational Attainment and Sleep," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 41(3), pages 1137-1160, June.
    7. Riera-Crichton, Daniel & Tefft, Nathan, 2014. "Macronutrients and obesity: Revisiting the calories in, calories out framework," Economics & Human Biology, Elsevier, vol. 14(C), pages 33-49.
    8. Jasmine L Travers & Catherine C Cohen & Andrew W Dick & Patricia W Stone, 2017. "The Great American Recession and forgone healthcare: Do widened disparities between African-Americans and Whites remain?," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-9, December.
    9. Shaoqing Gong & Liang Wang & Zhongliang Zhou & Kesheng Wang & Arsham Alamian, 2022. "Income Disparities in Obesity Trends among U.S. Adults: An Analysis of the 2011–2014 California Health Interview Survey," IJERPH, MDPI, vol. 19(12), pages 1-9, June.
    10. Qiuping (Pearl) Zhou & Kyeung Mi Oh, 2012. "Comparison of lifestyle behaviors and related factors between Asian American and white adults with prediabetes," Nursing & Health Sciences, John Wiley & Sons, vol. 14(1), pages 58-66, March.
    11. Fushing, Hsieh & Chou, Elizabeth P. & Chen, Ting-Li, 2023. "Multiscale major factor selections for complex system data with structural dependency and heterogeneity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    12. Christine L Gray & Lynne C Messer & Kristen M Rappazzo & Jyotsna S Jagai & Shannon C Grabich & Danelle T Lobdell, 2018. "The association between physical inactivity and obesity is modified by five domains of environmental quality in U.S. adults: A cross-sectional study," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-14, August.

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