The DOI matches its Crossref record; 28 of the 29 references it cites were found in a registry or an index.
Characterizing extreme values of body mass index-for-age by using the 2000 Centers for Disease Control and Prevention growth charts.
Open accessAbstract
Background The 2000 Centers for Disease Control and Prevention (CDC) growth charts included lambda-mu-sigma (LMS) parameters intended to calculate smoothed percentiles from only the 3rd to the 97th percentile. Objective The objective was to evaluate different approaches to describing more extreme values of body mass index (BMI)-for-age by using simple functions of the CDC growth charts. Design Empirical data for the 99th and the 1st percentiles of BMI-for-age were calculated from the data set used to construct the growth charts and were compared with estimates extrapolated from the CDC-supplied LMS parameters and to various functions of other smoothed percentiles. A set of reestimated LMS parameters that incorporated a smoothed 99th percentile were also evaluated. Results Extreme percentiles extrapolated from the CDC-supplied LMS parameters did not match well to the empirical data for the 99th percentile. A better fit to the empirical data was obtained by using 120% of the smoothed 95th percentile. The empirical first percentile was reasonably well approximated by extrapolations from the LMS values. The reestimated LMS parameters had several drawbacks and no clear advantages. Conclusions Several approximations can be used to describe extreme high values of BMI-for-age with the use of the CDC growth charts. Extrapolation from the CDC-supplied LMS parameters does not provide a good fit to the empirical 99th percentile values. Simple approximations to high values as percentages…
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“Trends over time in obesity prevalence among US youth by age, race and Hispanic origin, income, and education of household head have been published,1,5,13 but trends in obesity and severe obesity prevalence by urbanization level have not been well studied.”
From Differences in Obesity Prevalence by Demographics and Urbanization in US Children and Adolescents, 2013-2016 (2018) · cites this paper as [13]
In the citing paper
“Trends over time in obesity prevalence among US youth by age, race and Hispanic origin, income, and education of household head have been published,1,5,13 but trends in obesity and severe obesity prevalence by urbanization level have not been well studied.”
From Differences in Obesity Prevalence by Demographics and Urbanization in US Children and Adolescents, 2013-2016 (2018) · cites this paper as [13]
Citations
Cites
Multiple Imputation for Nonresponse in Surveys
Rubin, D. B. (1987) · Wiley Series in Probability and Statistics · doi:10.1002/9780470316696 · Cited by 20,701
Statistical Analysis With Missing Data
Lahiff, M., Little, R. J. A., & Rubin, D. B. (1989) · Journal of the American Statistical Association · doi:10.2307/2289883 · Cited by 17,385
Statistical Analysis with Missing Data
Little, R. J. A., & Rubin, D. B. (2002) · Wiley Series in Probability and Statistics · doi:10.1002/9781119013563 · Cited by 8,473
CDC GROWTH CHARTS FOR THE UNITED STATES: METHODS AND DEVELOPMENT 2000
Kuczmarski, R. J., Ogden, C. L., Guo, S. S., Strawn, L. G., Flegal, K. M., & Mei, Z. (2002) · Cited by 6,426
Self-citationCDC growth charts: United States.
Kuczmarski, R. J., Ogden, C. L., Grummer‐Strawn, L. M., Flegal, K. M., Guo, S. S., Wei, R. X., Mei, Z., Curtin, L. R., Roche, A. F., & Johnson, C. L. (2000) · PubMed · Cited by 5,298
Self-citationStatistical Analysis With Missing Data
Ghosh, S., Little, R. J. A., & Rubin, D. B. (1988) · Technometrics · doi:10.2307/1269814 · Cited by 4,730
Prevalence of overweight and obesity among US children, adolescents, and adults, 1999-2002.
Hedley, A. A., Ogden, C., Johnson, C. L., Carroll, M., Curtin, L. R., & Flegal, K. (2004) · Journal of the American Medical Association (JAMA) · doi:10.1001/jama.291.23.2847 · Cited by 4,670
Barlow, S. E., & and the Expert Committee (2007) · Pediatrics · doi:10.1542/peds.2007-2329c · Cited by 4,497
Prevalence and Trends in Overweight Among US Children and Adolescents, 1999-2000
Ogden, C. L. (2002) · JAMA · doi:10.1001/jama.288.14.1728 · Cited by 4,060
Self-citationSmoothing reference centile curves: The lms method and penalized likelihood
Cole, T. J., & Green, P. J. (1992) · Statistics in Medicine · doi:10.1002/sim.4780111005 · Cited by 2,803
Cited by
Sorted by citations
Items 301–400 of 435
Identifying characteristics and outcomes in youth with obesity and developmental disabilities
Rubin, M. B., Miller, C. M., Bauer, S. C., Ariza, A. J., & Binns, H. J. (2020) · Disability and health journal · doi:10.1016/j.dhjo.2020.100988 · Cited by 5
Imoisili, O. E., Lundeen, E. A., Freedman, D. S., Womack, L. S., Wallace, J., Hambidge, S. J., Federico, S. G., Everhart, R. M., Harr, D., Vance, J., et al. (2020) · Academic Pediatrics · doi:10.1016/j.acap.2020.11.026 · Cited by 5
Self-citationTonsillectomy Outcomes for Children With Severe Obesity
Hines, S. E., Pickett, K. L., Tholen, K., Handley, E., & Friedman, N. R. (2021) · The Laryngoscope · doi:10.1002/lary.29712 · Cited by 5
Schneider, G., Banaschewski, T., Feldman, B. L., Gustafsson, P. A., Murphy, B. P., Reynolds, M. W., Coghill, D., & Spalding, W. M. (2019) · Journal of Child and Adolescent Psychopharmacology · doi:10.1089/cap.2018.0132 · Cited by 5
“Second, calculated z -scores for individuals whose weight or height lie outside the CDC reference population 3rd and 97th percentiles ( z = – 1.88) are known to be unreliable (Kuczmarski et al. 2002; Flegal et al. 2009, 2013).”
InfluentialFirman, N., Boomla, K., Hudda, M. T., Robson, J. P., Whincup, P. H., & Dezateux, C. A. (2019) · Journal of Public Health · doi:10.1093/pubmed/fdz188 · Cited by 5
Champion, J. D., & Collins, J. L. (2013) · Journal of the American Association of Nurse Practitioners · doi:10.1111/1745-7599.12015 · Cited by 5
“…as weight in kilograms divided by height in meters squared) and BMI percentiles from measured height and weight were derived for age and sex using the Centers for Disease Control and Prevention National Center for Health Statistics Growth Charts (Flegal et al., 2009; Ogden et al., 2002).”
MethodObesity in children: bariatric surgery
Canoy, D., & Yang, T. O. (2015) · Europe PMC (PubMed Central) · doi:10.25405/ncl.34463175 · Cited by 5
Epidemiology, Etiology, and Consequences of Obesity
MOORE, B. J., & Pi‐Sunyer, X. (2012) · Wiley eBooks · doi:10.1002/9781394323142.ch1 · Cited by 5
Identification of Overweight in Children in the United States: A Simplified Approach
Nainar, S. M. H. (2011) · Obesity · doi:10.1038/oby.2011.159 · Cited by 4
Crespi, C. M., Gao, S., Payne, A., Nobari, T. Z., Avila, A., Nau, C., Whaley, S. E., & Wang, M. C. (2020) · Pediatric Research · doi:10.1038/s41390-020-1099-8 · Cited by 5
Overview of paediatric obesity for the paediatric mental health provider
Scheimann, A. O. (2012) · International Review of Psychiatry · doi:10.3109/09540261.2012.678816 · Cited by 4
“(Flegal et al., 2009; Skelton et al., 2009).”
BackgroundMusic ergogenic effect on strength performance: randomized clinical test
Araújo, M. H. D. A., Júnior, J. T., Venâncio, P. E. M., Tolentino, G. P., Lima, W. A., Soares, V., & Silva, I. O. (2018) · Manual Therapy Posturology & Rehabilitation Journal · doi:10.17784/mtprehabjournal.2018.16.574 · Cited by 4
“These variables were used to calculate the body mass index (BMI) by means of equation [BMI = weight (kg) / height (m) 2](23).”
MethodWickel, E. E., Ali, L., Hawkins, H., & Hemming, E. (2019) · BMC Pediatrics · doi:10.1186/s12887-019-1886-8 · Cited by 5
Lipton-Inga, M., Manzanarez, B., Vidmar, A. P., Garcia, S., Fink, C., Iverson, E., & Geffner, M. E. (2021) · Childhood Obesity · doi:10.1089/chi.2021.0090 · Cited by 4
Piombo, S. E., Huh, J., & Valente, T. W. (2022) · Childhood Obesity · doi:10.1089/chi.2021.0270 · Cited by 4
Impact of Short-Term Weight Loss on Hemostasis and Thrombosis after Bariatric Surgery
Taha, A., Eroğlu, H., Demirbas, I. E., Demir, B., & Dilektaşlı, E. (2023) · Surgery Research and Practice · doi:10.1155/2023/1729167 · Cited by 3
“It may be recommended to use low-molecular-weight heparin (LMWH) for a long time in the early postoperative period together with vitamin support [35, 36].”
BackgroundFox, C. K., Vock, D. M., Sherwood, N. E., Gross, A. C., Ryder, J. R., Bensignor, M. O., Bomberg, E. M., Sunni, M., Bramante, C. T., Jacobs, N., et al. (2024) · Contemporary Clinical Trials · doi:10.1016/j.cct.2024.107444 · Cited by 4
Lifestyle intervention for children and adolescents with severe obesity – results after one year
Skodvin, V. A., Lekhal, S., Kommedal, K. G., Benestad, B., Skjåkødegård, H. F., Danielsen, Y. S., Linde, S.-R. F., Roelants, M., Hertel, J. K., Hjelmesaeth, J. S., et al. (2020) · Tidsskrift for Den norske legeforening · doi:10.4045/tidsskr.19.0682 · Cited by 4
Perceptions of body mass index (BMI) in pediatric cancer survivors and their providers
Elchuri, S. V., Patterson, B. C., Wasilewski‐Masker, K. J., Mertens, A. C., Record, E., & Meacham, L. R. (2014) · Pediatric Blood & Cancer · doi:10.1002/pbc.25020 · Cited by 4
Parents’ Willingness to Pay for Pediatric Weight Management Programs
Drouin, O., Sharifi, M., Gerber, M. W., Horan, C. M., Orav, E. J., Marshall, R., & Taveras, E. M. (2019) · Academic Pediatrics · doi:10.1016/j.acap.2019.05.124 · Cited by 4
Robinson, T. N., Matheson, D., Haydel, K. F., Flora, J. A., & Desai, M. (2021) · Childhood Obesity · doi:10.1089/chi.2021.0166 · Cited by 4
Implications of the Energy Gap for the Prevention and Treatment of Childhood Obesity
Dietz, W. H. (2012) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2012.02.001 · Cited by 4
Assessment of Nutritional Status
Goodinson, S. M. (2020) · American Academy of PediatricsItasca, IL eBooks · doi:10.1542/9781610024181-24 · Cited by 4
PAutilities: Streamline Physical Activity Research
Hibbing, P. R. (2019) · doi:10.32614/cran.package.pautilities · Cited by 4
Prevalence and Polysomnographic Features of Obstructive Sleep Apnea in Childhood Obesity
Gedamu, H. Y., Ulualp, S. O., Wani, A., Chapel, A. C., Lenes‐Voit, F., & Mitchell, R. B. (2026) · The Laryngoscope · doi:10.1002/lary.70394 · Cited by 3
Brissman, M., Ek, A. E., Wennborg, S., Nordin, K., Eli, K., Janson, A., & Nowicka, P. (2026) · Acta Paediatrica · doi:10.1111/apa.70633 · Cited by 3
“This metric resembles the Centers for Disease Control and Prevention (CDC) index %CDC95 [25], which expresses BMI relative to the 95th percentile.”
A retrospective review of patient outcomes in the pediatric HEROES weight management program
Hawkins, M. J., Wiggins, S. A., & Struwe, L. A. (2018) · Applied Nursing Research · doi:10.1016/j.apnr.2018.06.017 · Cited by 3
Ball, G. D. C., Sharma, A., Moore, S. A., Metzger, D. L., Klein, D., Morrison, K. M., on behalf of the CANadian Pediatric Weight management Registry (CANPWR) Investigators, Buchholz, A., Chanoine, J., Hamilton, J. K., et al. (2023) · European Journal of Pediatrics · doi:10.1007/s00431-023-05039-4 · Cited by 3
Kashiwazaki, R., Jensen, A. M., Haemer, M. A., & Friedman, N. R. (2023) · Otolaryngology · doi:10.1002/ohn.512 · Cited by 3
Qiu, G., Riley, J. M., Dikdan, S. J., Johnson, D. M., Masood, I. R., HAJDUCZOK, A. G., & Shipon, D. (2024) · Childhood Obesity · doi:10.1089/chi.2023.0194 · Cited by 3
Jáuregui, E. J., Diala, O. R., Rove, K. O., Hoefner‐Notz, R., Tong, S., Nguyen, T. T., & Friedman, N. R. (2024) · The Laryngoscope · doi:10.1002/lary.31594 · Cited by 3
“24 This metric has been shown to correlate well with anthropometric indices of obesity and is more consistent across child age.”
Ramírez, J. P., Torres-Aparcana, H., Rebatta, F. B., & Agüero-Zamora, R. (2019) · Anales de la Facultad de Medicina · doi:10.15381/anales.v80i4.17253 · Cited by 3
“Optando por el criterio de un IMC ≥ p99, la prevalencia encontrada fue relativamente baja (2,4%), representando un 30% de los obesos reportados (7,6%).”
BackgroundInfluentialPanchaud, M., Szymanski, J., Marques-Vidal, P. M., & Giusti, V. (2014) · International Journal of Endocrinology · doi:10.1155/2014/356289 · Cited by 3
Linden, B. C., & Barnett, S. J. (2015) · Springer eBooks · doi:10.1007/978-3-319-04343-2_77 · Cited by 3
Activity Levels for Four Years in a Cohort of Urban-Dwelling Adolescent Females
Rockette‐Wagner, B., Hipwell, A. E., Kriska, A. M., Storti, K. L., & McTigue, K. M. (2016) · Medicine & Science in Sports & Exercise · doi:10.1249/mss.0000000000001152 · Cited by 3
Mobilizing during Infancy to Prevent Severe Obesity
Hassink, S. G. (2017) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2017.01.018 · Cited by 3
Prospective clinical study of the skin markers in childhood obesity-an emerging pandemic
Bhubaneswar, A., Bhubaneswar, M. D. A., Jena, A. K., Bhubaneswar, A., Panda, M., Bhubaneswar, A., & Patro, N. (2016) · Pediatric Review International Journal of Pediatric Research · doi:10.17511/ijpr.2016.i06.15 · Cited by 3
“There is a significant association of physical and psychological impairment with this condition, such as social rejection and teasing by their peer groups ending in low self esteem [1,2].”
BackgroundPak, N., Allahverdi, B., Moslemi, S., Rostami, P., Sayarifard, F., Mehdizadeh, M., Zamani, F., & Sayarifard, A. (2020) · Iranian Journal of Pediatrics · doi:10.5812/ijp.96605 · Cited by 3
Body Composition versus BMI as Measures of Success in a Clinical Pediatric Weight Management Program
Stackpole, K., Khoury, P. R., Siegel, R., & Gier, A. (2020) · Reports — Medical Cases Images and Videos · doi:10.3390/reports3040032 · Cited by 3
“Severe obesity is defined as having a BMI at or above 120% of the 95th percentile for BMI [13,14].”
BackgroundCreating Equal Opportunities for a Healthy Weight
Institute of Medicine (2013) · National Academies Press eBooks · doi:10.17226/18553 · Cited by 10
Tester, J. M., Xiao, L., Chau, C. A., Tinajero-Deck, L., Srinivasan, S., & Rosas, L. G. (2023) · Childhood Obesity · doi:10.1089/chi.2022.0234 · Cited by 2
Quadri, M., Ariza, A. J., Tucker, J. M., Bea, J. W., King, E. C., Kirk, S., Sweeney, B. R., Santos, M., Silver, L. E., Roberts, K. J., et al. (2024) · Childhood Obesity · doi:10.1089/chi.2023.0201 · Cited by 3
Marrone, A. K., Venkataraman‐Rao, P., & Gottschalk, L. (2021) · Pediatric Obesity · doi:10.1111/ijpo.12768 · Cited by 2
“As a result, recommendations to use percentage of the 95th percentile BMI-for-age were made, which have been widely accepted by the scientific community.(6,8) 3.”
BackgroundMethodFlegal, K. M. (2022) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-062220-103411 · Cited by 2
Self-citationPediatric metabolic and bariatric surgery: indications and preoperative multidisciplinary evaluation
Mangarelli, C., Fell, G. L., Hobbs, E., Lowry, K. W., Williams, E., & Pratt, J. S. A. (2024) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2024.08.025 · Cited by 2
Dieting Practices of Adolescents Seeking Obesity Treatment
Jebeile, H., House, E. T., Baur, L. A., Kwok, C., Collins, C. E., Garnett, S. P., & Lister, N. B. (2025) · Nutrients · doi:10.3390/nu17193100 · Cited by 3
“To investigate the association between the number of diets trialled and age, BMI expressed as a percentage of the 95th percentile [27], disordered eating and body satisfaction outcomes, we conducted multiple one-way ANOVAs.”
Fornander, M. J., Bates, C. R., Hampl, S. E., Beck, A. R., & Gillette, M. L. D. (2021) · Clinical Practice in Pediatric Psychology · doi:10.1037/cpp0000427 · Cited by 2
Assessment of the Obese Child or Adolescent
Barlow, S. E., Taylor, S. A., Hastings, E. S., & Garland, B. H. (2014) · Springer eBooks · doi:10.1007/978-1-4939-2311-3_20 · Cited by 2
The development of youth-onset severe obesity in urban US girls
McTigue, K. M., Stepp, S. D., Moore, C. G., Cohen, E. D., Hipwell, A. E., Loeber, R., & Kuller, L. H. (2015) · Journal of Clinical & Translational Endocrinology · doi:10.1016/j.jcte.2015.04.001 · Cited by 2
Overview on Obesity - A Review
Ashrafuzzaman, S. (2012) · BIRDEM Medical Journal · doi:10.3329/birdem.v1i1.12384 · Cited by 2
Assessment of Nutritional Status
Goodinson, S. M. (2020) · American Academy of PediatricsItasca, IL eBooks · doi:10.1542/9781610023610-24 · Cited by 2
Min, J., Griffis, H. M., Mendoza, M., Tam, V. W., Kaplinski, M. A., Kogon, A. J., Hanson, H. M., Meyers, K. E. C., & Natarajan, S. S. (2020) · Clinical Pediatrics · doi:10.1177/0009922820927037 · Cited by 2
Sivan, R. F., Lev, M. R. B., Silbermintz, A., Mozer‐Glassberg, Y., Seguier‐Lipszyc, E., Shalitin, S., Stafler, P., Tiroler, S., Shamir, R., & Waisbourd‐Zinman, O. (2021) · Journal of Pediatric Gastroenterology and Nutrition · doi:10.1097/mpg.0000000000003109 · Cited by 2
“In this age group, severe obesity is defined as a BMI greater than 120% of the 95th percentile weight for age, or a body mass index (BMI) of 35 kg/m(2) or greater (1,2).”
BackgroundObesity and Corticosteroid Dosing Guideline Adherence in Children Hospitalized With Asthma
Kyler, K. E., Bettenhausen, J. L., Hall, M., Glynn, E. F., Hoffman, M. A., Shakhnovich, V., Smolderen, K. G. E., & Davis, A. M. (2021) · Hospital Pediatrics · doi:10.1542/hpeds.2020-001420 · Cited by 2
Adenotonsillectomy for the treatment of obstructive sleep apnoea in extreme paediatric obesity
Vakharia, N., Murkin, C., Hall, A., & Bajaj, Y. (2021) · The Journal of Laryngology & Otology · doi:10.1017/s0022215121002693 · Cited by 2
Robbins, J. M., Mallya, G. G., Polansky, M., & Schwarz, D. F. (2015) · Apple Academic Press eBooks · doi:10.1201/b18225-5 · Cited by 2
Kakinami, L., Smyrnova, A., Paradis, G., Tremblay, A., & Henderson, M. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-058857 · Cited by 2
Choosing an accurate outcome metric for pediatric obesity care
Gorecki, M. C., & Binns, H. J. (2018) · Pediatric Diabetes · doi:10.1111/pedi.12796 · Cited by 3
“However, we have concerns regarding the use of body mass index (BMI) z-scores as your outcome variable and are wondering if you could reanalyze the data using the newer metric BMI percent of the 95th percentile (BMIp95).(2,3) While z-scores have long been used as the standard outcome metric in pediatric obesity care,…”
MethodFactores sociodemográficos y de riesgo cardiovascular asociados a obesidad severa en niñas
Ramírez, J. P., Henostroza, O. C., & Ramírez, A. A. (2021) · Anales de la Facultad de Medicina · doi:10.15381/anales.v82i1.20497 · Cited by 1
A study of growth pattern of school going children of Kolkata, India
Ghorai, T., Mazumder, S., Gangopadhyay, S., Chatterjee, T., Shaw, K., Das, P., & Samanta, A. (2023) · International Journal of Community Medicine and Public Health · doi:10.18203/2394-6040.ijcmph20230232 · Cited by 1
Treating Children and Adolescents With Obesity: Characteristics of Success
Christison, A. L., Tucker, J. M., King, E. C., Sweeney, B. R., Cuda, S. E., Frank, M., Kirk, S., & on behalf of the POWER Work Group (2023) · Childhood Obesity · doi:10.1089/chi.2023.0083 · Cited by 1
Barron, A. G., Fenick, A. M., Maciejewski, K. R., Turer, C. B., & Sharifi, M. (2024) · Applied Clinical Informatics · doi:10.1055/s-0044-1787975 · Cited by 1
Perioperative considerations in anesthesia for pediatric bariatric procedures
Schakett, B., Huang, G. T.-W., Pranav, H., & Glover, C. D. (2024) · Seminars in Pediatric Surgery · doi:10.1016/j.sempedsurg.2024.151460 · Cited by 1
The Association Between Physical Activity and Markers of Obesity in Children Living With Obesity
dos Santos, E. S. B., de Medeiros, I. A. C. M., Oliveira, M. S. D. S., Cureau, F. V., Mortatti, A. L., & Oliveira, R. S. (2025) · Pediatric Exercise Science · doi:10.1123/pes.2024-0079 · Cited by 1
Extreme Value Analysis Applied in Dietary Data
Panagoulias, D. P., Tsihrintzis, G. A., & Virvou, M. K. (2025) · Learning and analytics in intelligent systems · doi:10.1007/978-3-031-90174-4_4 · Cited by 1
Ward, T. W., Killanin, A. D., Rice, D. L., Ende, G. C., Steiner, E. L., Coutant, A. T., Embury, C. M., Calhoun, V. D., Wang, Y.-P., Stephen, J. M., et al. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.78 · Cited by 1
“The LMS parameters for BMI were derived from equations for smoothed percentiles ( Flegal et al., 2009; Flegal & Cole, 2013) based on Cole’s LMS method ( Cole, 1990; Cole & Green, 1992).”
Obesity in children and adolescents
Berman, C., Kohn, B., & Wilson, D. P. (2026) · Journal of clinical lipidology · doi:10.1016/j.jacl.2025.07.004 · Cited by 5
Christison, A. L., Kim, R., King, E. C., Sahay, R., Kharofa, R. Y., Sweeney, B. R., Thaker, V., Tucker, J. M., Vidmar, A. P., Yee, J. K., et al. (2026) · Pediatric Obesity · doi:10.1111/ijpo.70127 · Cited by 1
“Clinical characteristics included % of the BMI 95th percentile (%BMI p95 ) and obesity class (Class 1: 100% to 119% BMI p95 ; Class 2: 120%–139% BMI p95 ; Class 3: ≥ 140% BMI p95 ) [21].”
Obesity, Metabolic Syndrome and Type 2 Diabetes
Steinberger, J., & Kelly, A. S. (2013) · Springer eBooks · doi:10.1007/978-1-4471-4619-3_53 · Cited by 2
Provider Preference for Growth Charts in Tracking Children with Obesity
Chambers, M. A., Reddy, S. P., Olaiya, M. T., Dunnigan, D. L., Wasak, D., Hoskin, M. A., Knowler, W. C., & Sinha, M. (2020) · The Journal of Pediatrics · doi:10.1016/j.jpeds.2019.11.039 · Cited by 1
Ezenwugo, C. N. (2020) · Cited by 1
Integrating multiple built environment data sources
Won, J. Y., Elliott, M. R., Sanchez‐Vaznaugh, E. V., & Sánchez, B. N. (2023) · The Annals of Applied Statistics · doi:10.1214/22-aoas1692 · Cited by 1
“We conduct a stratified analysis by sex and grade, given that boys and girls mature at different ages and have different obesity prevalence (Flegal et al. (2009)).”
Pandey, S., Kavishwar, A., & Pandey, M. (2024) · Cureus · doi:10.7759/cureus.63202 · Cited by 1
“Severe obesity is defined as a gender-specific BMI greater than or equal to 120% of the 95th percentile which approximates the empirical 99th percentile at most ages [18].”
BackgroundImam, R., Chastang, K. M., Olowojesiku, R., Sherman, M. G., Mukadam, A. M., Barber, J. R., Liomba, A. M., Seydel, K. B., & Postels, D. G. (2024) · The Pediatric Infectious Disease Journal · doi:10.1097/inf.0000000000004581 · Cited by 1
Severe Obesity Defined by Percentiles of WHO and Cardiometabolic Risk in Youth with Obesity
Valerio, G., Bonito, P. D., Sessa, A. D., Ballarin, G., Calcaterra, V., Corica, D., Faienza, M. F., Franco, F., Licenziati, M. R., Maffeis, C., et al. (2024) · Children · doi:10.3390/children11111345 · Cited by 1
Sarıkaya, E., Kara, L., GÖK, E., Berber, U., Şıraz, Ü. G., & Hatipoğlu, N. (2025) · Pediatrics International · doi:10.1111/ped.70068 · Cited by 1
Diagnosis of Severe Obesity in Korean Children and Adolescents
Jung, J., & Cho, Y. G. (2016) · Daehan imsang geon-gang jeungjin hakoeji/Daehan imsang geon'gang jeungjin haghoeji · doi:10.15384/kjhp.2016.16.3.174 · Cited by 1
Energy Management for Personalized Weight Reduction (EMPOWER) Program: Three-Year Outcome Data.
Vidmar, A. P., Fink, C., Torres, B., Manzanarez, B., Mittelman, S. D., Wee, C. P., & Borzutzky, C. (2019) · PubMed · Cited by 1
Obesity in Children/Adolescents and Obesity-Related Comorbidities
Kohut, T. J., Robbins, J., Prout, E. P., Katz, L. E. L., Brothers, J. A., Vazquez-Diaz, S., Genuario, K., & Panganiban, J. A. (2020) · Springer eBooks · doi:10.1007/978-3-030-53370-0_27 · Cited by 1
McSweeney, Z. C., McSweeney, M. D., Huang, S. H., & Hill, S. G. (2021) · Journal of Child Health Care · doi:10.1177/13674935211037535 · Cited by 1
Assessment of the Obese Child or Adolescent
Barlow, S. E., Taylor, S. A., Hastings, E. S., & Garland, B. H. (2014) · Springer eBooks · doi:10.1007/978-1-4939-1203-2_20 · Cited by 1
“Studies that apply either of these definitions to national prevalence data indicate a 4–6 % prevalence of severe obesity among children across age groups [4, 5].”
BackgroundCombinAd: avaliação e melhoria da prescrição de contraceptivos orais combinados na adolescência
de Família, M., Neves, G. C., Sousa, A. S., de Família, M., Sousa, A. B., & de Família, M. (2021) · Revista Portuguesa de Clínica Geral · doi:10.32385/rpmgf.v37i6.12978 · Cited by 1
Hyer, S. L. (2020) · Open Access Journal of Endocrinology · doi:10.23880/oaje-16000146 · Cited by 1
Konty, K., Sweeney, S. H., & Day, S. E. (2022) · Spatial Demography · doi:10.1007/s40980-022-00109-x · Cited by 1
Treatment of severe obesity in adolescents : A mixed method approach.
Reece, L. J. (2016) · SHURA (Sheffield Hallam University Research Archive) (Sheffield Hallam University) · Cited by 1
The Treatment of Childhood and Adolescent Obesity
Armstrong, S., & Farpour‐Lambert, N. J. (2022) · Wiley eBooks · doi:10.1002/9781119695257.ch27 · Cited by 1
Daniels, S. R., & Bolling, C. F. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-809324-5.23631-6 · Cited by 1
Wang, Y., Cheng, G., & Wang, L. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-99967-0.00144-7 · Cited by 1
Conservative Treatment for Morbidly Obese Adolescents: The German Experience
van Egmond-Fröhlich, A. (2014) · Springer eBooks · doi:10.1007/978-3-7091-0968-7_5
Metabolic syndrome in obese African American adolescents
Yeh, Y.-L. (2014) · Human Biology
Growth Patterns of US Children from 1963 to 2012Preprint
Zhong, X., Li, J., Rao, G., & Unnikrishnan, K. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1303.0686
“Based on the CDC growth charts, a BMI percentile ≥ 85 and < 95 is classified as overweight and a BMI percentile ≥ 95 is is classified as obese; the lower percentiles are observed for issues associated with being underweight [16], [17].”
MethodMeasuring adiposity change in adolescents
Garnett, S. P. (2012) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2012.08.029
Flegal, K. M., Wei, R. X., Ogden, C. L., Freedman, D. S., Johnson, C. L., & Curtin, L. R. (2010) · American Journal of Clinical Nutrition · doi:10.3945/ajcn.2009.29042
Self-citationGrowth and morbidity in extreme preterm born infants
Horemuzova, E. (2013) · Figshare
Gow, M. L., Ho, M. M., Halim, J. A., Chisholm, K. W., Noakes, M., Baur, L. A., Cowell, C. T., & Garnett, S. P. (2014) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2014.10.072
Obesity and Heart Diseases, a Worsened Epidemic in Recent Decades
Wu, J.-L., & Juan, C.-W. (2015) · InTech eBooks · doi:10.5772/61044 · Cited by 1
Michalsky, M. P. (2015) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2015.10.065
Early Detection of Atherosclerosis in Primary School Children
Nedog, V. (2014) · Cardiology and Angiology An International Journal · doi:10.9734/ca/2014/9958
“Third, we didn't try to establish diagnosis of hypertension or obesity in children with higher IMT values, because of the fact that the blood pressure and BMI percentiles are based upon gender, age, and height [13,14].”
Background42 Bariatric Surgery in Adolescents
Barnett, S. J., Michalsky, M. P., & Inge, T. H. (2014) · Springer eBooks · doi:10.1007/978-1-4939-1637-5_42
Metadata
- Authors
- Flegal, K. M., Wei, R., Ogden, C. L., Freedman, D. S., Johnson, C. L., & Curtin, L. R.
- Affiliations
- Centers for Disease Control and Prevention (US)
- National Center for Health Statistics (US)
- Corresponding author
- Flegal, Katherine M
- Venue
- The American Journal of Clinical Nutrition
- Publisher
- Elsevier BV
- Published
- 2009-11
- Volume
- 90
- Issue
- 5
- Pages
- 1314-1320
- ISSN
- 0002-9165 (ISSN-L)
- OpenAlex
- W2130113732
- Cited by
- 435
- References
- 29
- Citations by year
- 2026: 8 · 2025: 10 · 2024: 27 · 2023: 14 · 2022: 25 · 2021: 32 · 2020: 44 · 2019: 33 · 2018: 38 · 2017: 42 · 2016: 30 · 2015: 26 · 2014: 29 · 2013: 28 · 2012: 28
- FWCI
- 16.06
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- American Journal of Clinical Nutrition (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Obesity, Physical Activity, Diet
- Health Sciences › Medicine › Physiology (medical) › Body Composition Measurement Techniques
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
- Keywords
- body mass index for age, CDC growth charts, 99th percentile, overweight children, childhood obesity
- MeSH terms
- Adolescent, Centers for Disease Control and Prevention, U.S., Child, Child, Preschool, Female, Growth, Humans, Male, Nutrition Surveys, Thinness, United States, Body Mass Index, Overweight, Young Adult
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