Statistical methods and applications in growth and development - SITAR, LMS and IOTF

The study of human growth and development involves the assessment and summary of size and how it changes over time. Assessment can take place on several different timescales: e.g. one-off, i.e. a single measurement to assess size using a growth reference; and longer term, where several measurements over an extended period of time define the shape of the individual's growth curve. Both timescales involve statistical issues that the author has previously studied: his LMS method (1992) for constructing growth references, and his SITAR mixed effects growth model for analysing growth curves (2010). The aim of the grant is to progress both topics: providing web-based software to replace the author's popular but now ageing Excel add-in LMSgrowth and PC program LMSchartmaker for manipulating growth data; and continuing to develop his SITAR model, as funded with a current MRC grant, by extending the existing dedicated R library and highlighting further novel applications of the method.

The SITAR method of growth curve analysis (Cole et al 2010) summarises individual growth patterns of e.g height or weight in three parameters (size, timing and intensity) that are estimated as subject-specific random effects, plus a natural cubic spline estimate of the average growth curve. It explains over 95% of the age-specific variance in the outcome measure, and as such is an effective summary of individual growth patterns. The subject-specific random effects, representing individual growth, can then be related to earlier growth-affecting exposures or later health outcomes. Thus it is relevant in translational medicine and life course epidemiology. The first objective of the project is to further develop the SITAR methodology, by applying it to a series of existing growth studies, and developing the existing SITAR software library in the R statistical language for its wider dissemination.
The LMS method (Cole and Green 1992) is widely used for constructing growth references and centile charts, particularly for skew measurements such as weight, BMI or waist circumference. The second objective is to port existing software to fit and use the LMS method (LMSgrowth and LMSchartmaker) from the desktop to an R-shiny web-based platform, which will improve access to the software and extend its capabilities. A programmer post is included in the costings.

Who will benefit from this research, and how?
o Academia?All researchers, national and international, interested in the analysis of longitudinal growth will find SITAR of interest, as it will allow them to summarise individual growth patterns in a simple way and then link the pattern to other aspects of the individual's health and lifestyle.
o Public Sector?National policy makers concerned with the high and rising levels of childhood obesity will value the opportunity to assess prevalence rates based on BMI references constructed using the LMS method.
o Business/Industry?The international pharmaceutical industry will value a statistical tool that simplifies and sharpens the assessment of growth- affecting treatments. SITAR's efficient use of data will mean that clinical trials involving growth outcomes need not be as large as before, and hence may reach conclusions more quickly and certainly more cheaply. This in turn should make cheaper the development of new growth-affecting drugs.
o Parents and children?Parents and children worldwide will benefit indirectly from the improvements to growth assessment arising from this work.