Table 2.

Binary logistic regression model for age-categories as the predictor for gender.

Age Categories	Coefficient	p-value	O.R.	95% C.I. for O.R.
				Lower	Upper
0–4 years	0.544	<0.000	1.723	1.564	1.898
5–17 years	0.364	<0.000	1.439	1.365	1.517
18–35 years	0.030	0.087	1.030	0.996	1.066
36–55 years	−0.112	<0.000	0.894	0.864	0.926
Constant	−0.645	<0.000	0.525	–

The Nagelkerke R² shows that the model is explaining 0.6% of the results and Hosmer Lemeshow tests show that the model is a good fit (p = 1.000).

Reference category = “56 years & above”; Predicted probabilities for “females”.