2016, Number 5
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Revista Habanera de Ciencias Médicas 2016; 15 (5)
Do new procedures for estimating growth curves introduce outstanding changes in height estimates?
Rubén QM, Rodríguez CLE, Esquivel LM, González FC, Tamayo PV
Language: Spanish
References: 23
Page: 820-833
PDF size: 370.18 Kb.
ABSTRACT
Introduction: The use of growth curves to monitor physical development in children is essential for pediatric health care. Cuban height charts were created during the seventies decade following technics recommended at that time. In the last years, statistical methods based computational technics have been obtained a better model pattern for growth process. In particular WHO in the Multicenter Growth Study used the Box-Cox Power Exponential (BCPE) method. It is important to determine whether the application of such procedure in drawing curves introduce changes in the percentiles' estimates commonly used.
Objective: To evaluate discrepancies between percentiles' estimates from both methods.
Material and methods: supine-decubitus length data and height from Cubans under 20 years old from the first National Growth and Development Study (ENCD) were examined. Perpercentiles were estimated viEl método BCPE a the BCPE method implemented in GAMLSS' package supported in R language. Comparison of smoothed percentiles obtained from both procedures were plotted to evaluate discrepancies.
Results: The best fitted models were: for female supine-decubitus lengths the NO (DFµ=10;DF
ϭ=5;age
0.001) and NO(DFµ=14;DF
ϭ=6;age
0.006) for male respectively and NO(DFµ=16;DF
ϭ=10;age
0.544) and NO(DFµ=16;DF
ϭ=12;age
0.117) for female and male height. Height percentiles estimates were closely enough using either method. Some differences were detected for length percentiles, possibly due to computational corrections done while calculating standard deviations of ENCD.
Conclusions: Some differences were detected for length percentiles estimations but not for the height. The use of computational procedure is recommended because its considerable reduction of the subjective charge as compare with the method used before.
REFERENCES
Natale V, Rajagopalan A. Worldwide variation in human growth and the World Health Organization growth standards: a systematic review. BMJ Open. 2014.
Scherdel P, Botton J, Rolland-Cachera M-F, Léger J, Pelé F, Ancel PY, et al. Should the WHO Growth Charts Be Used in France?. PLoS ONE. 2015; 10(3).
Neyzi O, Bundak R, Gökçay G, Günöz H, Furman A, Darendeliler F, Baş F. Reference Values for Weight, Height, Head Circumference, and Body Mass Index in Turkish Children. J Clin Res PediatrEndocrinol. 2015; 7(4):280-293.
Healy MJR. The effect of age grouping on the distribution of a measurement affected by growth. Am. J. Physical Anthropology. 1962; 35: 49-50.
Cole TJ, Green PJ. Smoothing reference centile curves: The LMS method and penalized likelihood. StatMed. 1992; 11: 1305-1319.
Jordán J. y colaboradores. Desarrollo Humano en Cuba. La Habana: Editorial Científico Técnica; 1976.
Wei Y Pere, Koenker AR, Hey X. Quantile Regression Methods for Reference Growth Charts. StatMed. 2006; 25(8):1369-82.
WHO Multicentre Growth Reference Study Group. WHO Child Growth Standards on length/height, weight and age. Acta Paediatrica. 2006; Suppl 450: 76-85.
WHO Child Growth Standards: length/height-for-age, weight-for-age, weight-forlength, weight-for-height and body mass index-for-age: methods and development. Geneva, World Health Organization. 2006. (Citado: Enero 2016). Disponible en: http://www.who.int/childgrowth/standards/Technical_report.pdf
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2014. (Citado: marzo 2016). Disponible en: https://wwwr-project.org/about.html
Rigby RA and Stasinopoulos DM. Smooth centile curves for skew and kurtotic data modeled using the Box-Cox power exponential distribution. Stat Med. 2004; 23(19): 3053-76.
Rubén M, Rodríguez L, Esquivel M, Orúe M. Experiencia en el uso de R para el ajuste de curvas de crecimiento. RCIM. 2011; 3 (2).
Colectivo de autores. Consulta de Puericultura. 3ra. edición. Ministerio de Salud Pública La Habana; Ed. Ciencias Médicas; 2016.
Rodd C, Metzger D, Sharma A and the Canadian Pediatric Endocrine Group (CPEG). Working Committee for National Growth Charts Extending World Health Organizationweight-for-age reference curves to older children. BMC Pediatrics. 2014; (14):32-38.
Zong XN, Li H, Wu HH, Zhang YQ. Socioeconomic development and secular trend in height in China. Econ Hum Biol. 2015; 19:258-64.
Bodzsar EB, Zsakai A, Mascie-taylor.N. Secular.growth and maturation changes in Hungary in relation to socioeconomic and demographic changes. J Biosoc Sci. 2016; 48(2):158-73.
Chen TJ, Cheng J. Secular Change in Stature of Urban Chinese Children and Adolescents, 1985-2010.Biomed Environ Sci. 2013; 26(1): 3-223.
Guimarey LM, Castro LE, Torres MF, Cesani MF, Luis MA, Quintero FA, Oyhenart EE. Secular changes in body size and body composition in schoolchildren from La Plata City (Argentina). Anthropol Anz. 2014; 71(3):287-301.
Stasinopoulos M, Rigby B, Voudouris V, Akantziliotou C,Enea,M. Generalized Additive Models for Location, Scale and Shape. (Citado Enero, 2016). Disponible en: http://www.gamlss.org/
Rigby R, Stasinopoulos DM. Automatic smoothing parameter selection in GAMLSS with an application to centile estimation. Statistical Methods in Medical Research. 2013; 0(0): 1-15.
Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control. 1974; 19(6):716-723.
Royston P, Wright EM. Goodness-of-fit statistics for age-specific reference intervals. StatMed. 2000; 19:2943-2962.
Van Buuren S,Fredriks M. Worm plot: a simple diagnostic device for modelling growth reference curves. StatMed. 2001; 20:1259-1277.