Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies.
Using linear and natural cubic splines, SITAR, and latent trajectory models to characterise nonlinear longitudinal growth trajectories in cohort studies.
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DOI：
10.1186/s12874-022-01542-8
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发表时间：
2022-03-15
影响因子：
4
通讯作者：
Lawlor DA
中科院分区：
文献类型：
--
作者：
Elhakeem A;Hughes RA;Tilling K;Cousminer DL;Jackowski SA;Cole TJ;Kwong ASF;Li Z;Grant SFA;Baxter-Jones ADG;Zemel BS;Lawlor DA
Longitudinal data analysis can improve our understanding of the influences on health trajectories across the life-course. There are a variety of statistical models which can be used, and their fitting and interpretation can be complex, particularly where there is a nonlinear trajectory. Our aim was to provide an accessible guide along with applied examples to using four sophisticated modelling procedures for describing nonlinear growth trajectories. This expository paper provides an illustrative guide to summarising nonlinear growth trajectories for repeatedly measured continuous outcomes using (i) linear spline and (ii) natural cubic spline linear mixed-effects (LME) models, (iii) Super Imposition by Translation and Rotation (SITAR) nonlinear mixed effects models, and (iv) latent trajectory models. The underlying model for each approach, their similarities and differences, and their advantages and disadvantages are described. Their application and correct interpretation of their results is illustrated by analysing repeated bone mass measures to characterise bone growth patterns and their sex differences in three cohort studies from the UK, USA, and Canada comprising 8500 individuals and 37,000 measurements from ages 5–40 years. Recommendations for choosing a modelling approach are provided along with a discussion and signposting on further modelling extensions for analysing trajectory exposures and outcomes, and multiple cohorts. Linear and natural cubic spline LME models and SITAR provided similar summary of the mean bone growth trajectory and growth velocity, and the sex differences in growth patterns. Growth velocity (in grams/year) peaked during adolescence, and peaked earlier in females than males e.g., mean age at peak bone mineral content accrual from multicohort SITAR models was 12.2 years in females and 13.9 years in males. Latent trajectory models (with trajectory shapes estimated using a natural cubic spline) identified up to four subgroups of individuals with distinct trajectories throughout adolescence. LME models with linear and natural cubic splines, SITAR, and latent trajectory models are useful for describing nonlinear growth trajectories, and these methods can be adapted for other complex traits. Choice of method depends on the research aims, complexity of the trajectory, and available data. Scripts and synthetic datasets are provided for readers to replicate trajectory modelling and visualisation using the R statistical computing software. The online version contains supplementary material available at 10.1186/s12874-022-01542-8.
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影响因子：
12.3
作者：
Cousminer DL;Wagley Y;Pippin JA;Elhakeem A;Way GP;Pahl MC;McCormack SE;Chesi A;Mitchell JA;Kindler JM;Baird D;Hartley A;Howe L;Kalkwarf HJ;Lappe JM;Lu S;Leonard ME;Johnson ME;Hakonarson H;Gilsanz V;Shepherd JA;Oberfield SE;Greene CS;Kelly A;Lawlor DA;Voight BF;Wells AD;Zemel BS;Hankenson KD;Grant SFA
通讯作者：
Grant SFA
影响因子：
7.7
作者：
Cole TJ;Donaldson MD;Ben-Shlomo Y
通讯作者：
Ben-Shlomo Y
影响因子：
13.8
作者：
Elhakeem, Ahmed;Heron, Jon;Lawlor, Deborah A.
通讯作者：
Lawlor, Deborah A.
影响因子：
5.4
作者：
Brilleman, Samuel L.;Howe, Laura D.;Tilling, Kate
通讯作者：
Tilling, Kate
影响因子：
39.3
作者：
Buscot, Marie-Jeanne;Thomson, Russell J.;Magnussen, Costan G.
通讯作者：
Magnussen, Costan G.