Age, puberty, body dissatisfaction, and physical activity decline in adolescents. Results of the German Health Interview and Examination Survey (KiGGS)

Table 6 Sequential comparison of multinomial logistic models for the prediction of physical activity frequency in boys (n = 3 225)

	*Statistics for individual predictors*								*Model statistics*
Model		Age	Pubic hair stage	Voice change	Pubertal timing	BDS	Migback × pubic hair stage	BDS × age	Correct classification	Pseudo -2 Log- Likelihood	Wald χ² (df) corr. for model	Nagelkerke's pseudo R²
0 ^#	Wald χ2 (df) corrected								36.5%	9431.11	39.09 (13.62)	.018
	p-value*										< .001
1	Wald χ2 (df) corrected	68.82 (2.92)							37.6%	9319.74	104.58 (16.06)	.050
	p-value*	< .001									< .001
2	Wald χ2 (df) corrected	22.77 (2.95)	4.81 (5.56)	1.55 (5.76)					37.7%	9310.25	104.20 (24.40)	.053
	p-value*	< .001	.836	.990							< .001
3	Wald χ2 (df) corrected	34.45 (2.92)	7.58 (5.52)	5.31 (5.75	18.80 (5.54)				38.2%	9282.33	112.61 (27.93)	.060
	p-value*	< .001	.068	.284	.007						< .001
4	Wald χ2 (df) corrected	33.06 (2.91)	7.14 (5.51)	5.42 (5.74)	18.70 (5.56)	9.90 (8.44)			38.5%	9267.46	115.69 (33.30)	.065
	p-value*	< .001	.084	.299	.008	.022					< .001
5	Wald χ2 (df) corrected	28.01 (2.90)	12.70 (5.67)	6.20 (5.75)	19.01 (5.54)	13.86 (8.13)	20.50 (5.75)	14.73 (8.15)	38.3%	9217.06	126.10 (40.51)	.078
	p-value*	< .001	.013	.258	.007	.017	.024	.008			< .001

* Adjustment for multiple tests: Šidák sequential
^# model 0 = baseline model including body fat percentage and sociodemographic variables: region, SES, migrant background migback = migrant background
Each row of the table shows the results of one tested model. Left-hand the test statistics for the independent variables are given while right-hand information on model fit is displayed.
The corrected Wald chi-square test tests if an individual independent variable (individual predictors) or all independent variables together (model statistics) significantly contribute to the prediction of the dependent variable; it is corrected for the sampling plan.
Correct classification rate is the proportion of participants for whom the tested model could correctly predict the category of the dependent variable (PA frequency).
Pseudo -2 Log-Likelihood: In logistic regression models are compared due to their -2 log-likelihood; since for complex samples no likelihood ratio test is available the values are only descriptive; better fitting models have smaller values.
Nagelkerke's pseudo R² is a measure of explained variation in the dependent variable that emulates R² from linear regression.

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