Cited by 49Obesity, Physical Activity, DietBody Composition Measurement TechniquesCancer Risks and Factors

Distance and percentage distance from median BMI as alternatives to BMI z score

Open access
Freedman, David S., Woo, Jessica G., Ogden, Cynthia L., Xu, Ji H., Cole, Tim J.·2020·British Journal of Nutrition

Abstract

BMI z (BMIz) score based on the Centers for Disease Control and Prevention growth charts is widely used, but it is inaccurate above the 97th percentile. We explored the performance of alternative metrics based on the absolute distance or % distance of a child’s BMI from the median BMI for sex and age. We used longitudinal data from 5628 children who were first examined <12 years to compare the tracking of three BMI metrics: distance from median, % distance from median and % distance from median on a log scale. We also explored the effects of adjusting these metrics for age differences in the distribution of BMI. The intraclass correlation coefficient (ICC) was used to compare tracking of the metrics. Metrics based on % distance (whether on the original or log scale) yielded higher ICCs compared with distance from median. The ICCs of the age-adjusted metrics were higher than that of the unadjusted metrics, particularly among children who were (1) overweight or had obesity, (2) younger and (3) followed for >3 years. The ICCs of the age-adjusted metrics were also higher compared with that of BMIz among children who were overweight or obese. Unlike BMIz, these alternative metrics do not have an upper limit and can be used for assessing BMI in all children, even those with very high BMIs. The age-adjusted % from median (on a log or linear scale) works well for all ages, while unadjusted % from median is better limited to older children or short follow-up periods.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1017/s0007114519002046

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • BMI is relatively simple to measure in adults and functionally sums a variety of complex body indicators.

    “BMI is relatively simple to measure in adults [4,5,6,7,8,9] and functionally sums a variety of complex body indicators.”

    From Advantages and Limitations of the Body Mass Index (BMI) to Assess Adult Obesity (2024) · cites this paper as [9]

    In Subjects and Methods > BMI Metrics (page unavailable), the paper describes calculating BMI from measured height and weight, supporting the point that it is relatively simple to obtain. The study sample comprises children aged 2–17, however, so it does not establish the claim specifically for adults. The citation is attached to the measurement clause, not the subsequent claim about body indicators. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 38

  1. [1]Kuczmarski RJ, Ogden CL, Guo SS, (2002) 2000 CDC Growth Charts for the United States: methods and development. Vital and health statistics. Series 11, Data from the national health survey 11, 1– 190. 12043359
  2. [2]Ogden CL, Kuczmarski RJ, Flegal KM, (2002) Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics 109, 45– 60. 11773541
  3. [3]Flegal KM & Cole TJ (2013) Construction of LMS parameters for the Centers for Disease Control and Prevention 2000 Growth Charts. National health statistics reports 9, 1– 3. 24992748
  4. [4]Ogden CL & Flegal KM (2010) Changes in terminology for childhood overweight and obesity. National Health Statistics Reports 25, 1– 5. 20939253
  5. [5]Cole TJ (1990) The LMS method for constructing normalized growth standards. European journal of clinical nutrition 44, 45– 60. 2354692
  6. [6]Cole TJ & Green PJ (1992) Smoothing reference centile curves: the LMS method and penalized likelihood. Statistics in medicine 11, 1305– 19. 1518992
  7. [7]Ragland DR (1992) Dichotomizing continuous outcome variables: dependence of the magnitude of association and statistical power on the cutpoint. Epidemiology (Cambridge, Mass.) 3, 434– 40. 1391136
  8. [8]Royston P, Altman DG & Sauerbrei W (2006) Dichotomizing continuous predictors in multiple regression: a bad idea. Statistics in Medicine 25, 127– 141. 16217841
  9. [10]Freedman DS, Butte NF, Taveras EM, (2017) BMI z-Scores are a poor indicator of adiposity among 2- to 19-year-olds with very high BMIs, NHANES 1999–2000 to 2013–2014. Obesity (Silver Spring) 25, 739– 746. 28245098 PMC5373980
  10. [11]Woo JG (2009) Using body mass index Z-score among severely obese adolescents: a cautionary note. International Journal of Pediatric Obesity 4, 405– 410. 19922058
  11. [12]Freedman DS, Butte NF, Taveras EM, (2017) Longitudinal changes in BMI z-scores among 45 414 2–4-year olds with severe obesity. Ann. Hum. Biol 44, 687– 692. 29082754 PMC5765752
  12. [13]Júlíusson PB, Roelants M, Benestad B, (2018) Severe obesity is a limitation for the use of body mass index standard deviation scores in children and adolescents. Acta Paediatr 107, 307– 314. 28992355
  13. [15]Berkey CS & Colditz GA (2007) Adiposity in adolescents: change in actual BMI works better than change in BMI z score for longitudinal studies. Annals of epidemiology 17, 44– 50. 17140812
  14. [16]Cole TJ, Faith MS, Pietrobelli A, (2005) What is the best measure of adiposity change in growing children: BMI, BMI%, BMI z-score or BMI centile? European Journal of Clinical Nutrition 59, 419– 425. 15674315
  15. [17]Gulati AK, Kaplan DW & Daniels SR (2012) Clinical tracking of severely obese children: a new growth chart. Pediatrics 130, 1136– 40. 23129082 PMC4528342
  16. [18]Chambers M, Tanamas SK, Clark EJ, (2017) Growth Tracking in Severely Obese or Underweight Children. Pediatrics 140, https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5703793/. PMC5703793 29114063
  17. [20]Waterlow JC (1972) Classification and definition of protein-calorie malnutrition. Br Med J 3, 566– 569. 4627051 PMC1785878
  18. [21]Gomez F, Galvan RR, Frenk S, (1956) Mortality in second and third degree malnutrition. J Trop Pediatr (Lond) 2, 77– 83. 24544135
  19. [22]Freedman DS & Berenson GS (2017) Tracking of BMI z Scores for severe obesity. Pediatrics 140 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5574726/. PMC5574726 28830920
  20. [23]Berenson GS, McMahan CA, Voors AW, (1980) Cardiovascular risk factors in children: the early natural history of atherosclerosis and essential hypertension New York: Oxford University Press.
  21. [24]Webber LS, Cresanta JL, Croft JB, (1986) Transitions of cardiovascular risk from adolescence to young adulthood--the Bogalusa Heart Study: II. Alterations in anthropometric blood pressure and serum lipoprotein variables. Journal of Chronic Diseases 39, 91– 103. 3944231
  22. [25]Freedman DS, Lawman HG, Galuska DA, (2018) Tracking and Variability in Childhood Levels of BMI: The Bogalusa Heart Study. Obesity (Silver Spring) 26, 1197– 1202. 29888429 PMC6014905
  23. [28]Cole TJ & Altman DG (2017) Statistics Notes: Percentage differences, symmetry, and natural logarithms. BMJ 358, j3683. 28814563
  24. [29]Nickerson CAE (1997) A Note On ‘A Concordance Correlation Coefficient to Evaluate Reproducibility’. Biometrics 53, 1503– 1507. 2720055
  25. [30]McGraw KO & Wong SP (1996) Forming inferences about some intraclass correlation coefficients. Psychological Methods 1, 30– 46.
  26. [33]Kelly AS & Daniels SR (2017) Rethinking the Use of Body Mass Index z-Score in Children and Adolescents with Severe Obesity: Time to Kick It to the Curb? The Journal of Pediatrics 28601360
  27. [34]Wang Y, Cai L, Wu Y, (2015) What childhood obesity prevention programmes work? A systematic review and meta-analysis. Obesity Reviews 16, 547– 565. 25893796 PMC4561621
  28. [35]Hampl S, Odar Stough C, Poppert Cordts K, (2016) Effectiveness of a hospital-based multidisciplinary pediatric weight management program: Two-year outcomes of PHIT Kids. Childhood obesity (Print) 12, 20– 5. 26790094
  29. [36]McCormick EV, Dickinson LM, Haemer MA, (2014) What can providers learn from childhood body mass index trajectories: a study of a large, safety-net clinical population. Academic pediatrics 14, 639– 45. 25129568
  30. [37]Baughcum AE, Gramling K & Eneli I (2015) Severely obese preschoolers in a tertiary care obesity program: characteristics and management. Clinical pediatrics 54, 346– 52. 25404751
  31. [38]O’Connor EA, Evans CV, Burda BU, (2017) Screening for Obesity and Intervention for Weight Management in Children and Adolescents. Evidence Report and Systematic Review for the US Preventive Services Task Force (USPSTF). JAMA 317, 2427– 2427. 28632873
  32. [39]Dwyer T & Blizzard CL (1996) Defining obesity in children by biological endpoint rather than population distribution. International Journal of Obesity 20, 472– 480. 8696427
  33. [40]Williams DP, Going SB, Lohman TG, (1992) Body fatness and risk for elevated blood pressure, total cholesterol, and serum lipoprotein ratios in children and adolescents. American journal of public health 82, 358– 63. 1536350 PMC1694353
  34. [41]Freedman DS, Katzmarzyk PT, Dietz WH, (2009) Relation of body mass index and skinfold thicknesses to cardiovascular disease risk factors in children: the Bogalusa Heart Study. American Journal of Clinical Nutrition 90, 210– 216. 19420092 PMC2697002
  35. [42]Steinberger J, Jacobs DR, Raatz S, (2005) Comparison of body fatness measurements by BMI and skinfolds vs dual energy X-ray absorptiometry and their relation to cardiovascular risk factors in adolescents. International Journal of Obesity 29, 1346– 1352. 16044176
  36. [44]Rigby RA & Stasinopoulos DM (2014) Automatic smoothing parameter selection in GAMLSS with an application to centile estimation. Stat Methods Med Res 23, 318– 332. 23376962
  37. [45]Hales CM, Fryar CD, Carroll MD, (2018) Trends in Obesity and Severe Obesity Prevalence in US Youth and Adults by Sex and Age, 2007–2008 to 2015–2016. JAMA 319, 1723– 1725. 29570750 PMC5876828
  38. [46]Kelly AS, Barlow SE, Rao G, (2013) Severe obesity in children and adolescents: identification, associated health risks, and treatment approaches: A Scientific Statement from the American Heart Association. Circulation 128, 1689– 712. 24016455

Cited by

Sorted by citations

Authors
Freedman, D. S., Woo, J. G., Ogden, C. L., Xu, J. H., & Cole, T. J.
Affiliations
  • Centers for Disease Control and Prevention (US)
  • Cincinnati Children's Hospital Medical Center (US)
  • Louisiana State University Health Sciences Center New Orleans (US)
  • University College London (GB)
Corresponding author
Freedman, David S.
Venue
British Journal of Nutrition
Published
2019-08-23
Volume
124
Issue
5
Pages
493-500
ISSN
  • 0007-1145 (ISSN-L)
  • 1475-2662
OpenAlex
W2969212872
Cited by
49
References
2
Citations by year
2026: 4 · 2025: 6 · 2024: 6 · 2023: 4 · 2022: 11 · 2021: 10 · 2020: 8
FWCI
6.68
Type
journal article
Language
en
Open access
Locations
  • British Journal Of Nutrition (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • Louisiana State University
  • National Institutes of Health (CC999999)
  • Centers for Disease Control and Prevention
  • Medical Research Council (MR/R010692/1)
  • National Institute on Aging (R01AG016592)
  • National Heart, Lung, and Blood Institute (R01HL121230, HL 38 844, AG-16592)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
  • Health Sciences › Medicine › Physiology › Body Composition Measurement Techniques
  • Health Sciences › Medicine › Oncology › Cancer Risks and Factors
Keywords
BMI z-score, childhood obesity, overweight children, CDC growth charts
MeSH terms
Adolescent, Anthropometry, Child, Child, Preschool, Cross-Sectional Studies, Female, Humans, Longitudinal Studies, Male, Reference Values, United States, Body Mass Index, Young Adult

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review