Body Mass Index Trajectories during 6–18 Years Old and the Risk of Hypertension in Young Adult: A Longitudinal Study in Chinese Population

Table 1

Parameter estimates for the latent class growth mixture modeling.

Nb. latent classes	Polynomial degree	Log-likelihood	BIC	% participants per class	Mean posterior probabilities	Posterior probabilities >0.7 (%)
2	Cubic	−10461.73	−10499.40	83.55/16.45	0.97/0.87	96.68/78.57
3	Cubic	−10323.23	−10379.74	65.38/27.83/6.78	0.88/0.80/0.88	85.78/72.55/83.46
4	Cubic	−10196.91	−10272.25	64.53/27.30/4.70/3.47	0.88/0.89/0.80/0.84	85.43/85.23/69.47/75.38
5	Cubic	−10147.65	−10241.83	20.03/56.14/17.04/3.15/3.63	0.75/0.79/0.76/0.83/0.88	61.90/70.89/68.72/76.39/83.33
6	Cubic	−10075.40	−10188.42	19.18/55.07/17.68/2.83/1.44/3.79	0.80/0.79/0.77/0.76/0.89/0.88	64.15/70.39/64.90/68.77/81.48/80.28

Parameter estimates include the number of latent classes considered, the polynomial form of the model, the maximum log-likelihood, and the Bayesian Information Criterion (BIC), and for models with 2 or more classes, the a-posteriori classification of subjects in each class (%), the mean of posterior probabilities in each latent class, and the % of subjects classified in each class with a posterior probability above 0.7 are considered.