Assessment of height growth in Indian children using growth centiles and growth curves

Abstract

Background

Growth centiles and growth curves are two ways to present child anthropometry; however, they differ in the type of data used, the method of analysis, the biological parameters fitted and the form of interpretation.

Aim

To fit and compare height growth centiles and curves in Indian children.

Subjects and methods

1468 children (796 boys) from Pune India aged 6–18 years with longitudinal data on age and height (n = 7781) were analysed using GAMLSS (Generalised Additive Models for Location Scale and Shape) for growth centiles, and SITAR (SuperImposition by Rotation and Translation) for growth curves.

Results

SITAR explained 98.7% and 98.8% of the height variance in boys and girls, with mean age at peak height velocity 13.1 and 11.0 years, and mean peak velocity 9.0 and 8.0 cm/year, respectively. GAMLSS (Box-Cox Cole Green model) also captured the pubertal growth spurt but the centiles were shallower than the SITAR mean curve. Boys showed a mid-growth spurt at age 8 years.

Conclusion

GAMLSS displays the distribution of height in the population by age and sex, while SITAR effectively and parsimoniously summarises the pattern of height growth in individual children. The two approaches provide distinct, useful information about child growth.

Keywords:

• Height centiles
• growth curves
• GAMLSS
• SITAR
• India

Acknowledgements

The authors acknowledge the National Supercomputing Mission (NSM) for providing computing resources of ‘PARAM Brahma’ at IISER Pune, which is implemented by C-DAC and supported by the Ministry of Electronics and Information Technology (MeitY) and Department of Science and Technology (DST), Government of India.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

Data sharing is not applicable to this article as no new data were created or analysed in this study.

Additional information

Funding

This work was supported by the Newton Bhabha PhD Placement Programme 2019–2020, jointly funded by the Department of Biotechnology, Ministry of Science and Technology, Govt. of India and British Council, New Delhi. SAA also acknowledges funding by the Council of Scientific and Industrial Research, India under grant number 09/936(0202)/2018 EMR-I.