Table 6.

Logistic multilevel, multivariate regression models with past-year externalising disorder† as the outcome among 4072 urban China residents‡

	Individual-level exposures only			Individual-level exposures and neighbourhood-level income			Individual-level exposures and neighbourhood-level marital status
	OR	95% CI lower limit	95% CI upper limit	OR	95% CI lower limit	95% CI upper limit	OR	95% CI lower limit	95% CI upper limit
Individual-level fixed effects
Age 35–49	0.49*	0.26	0.91	0.49*	0.26	0.92	0.53*	0.28	0.99
Age 50–64	0.17*	0.07	041	0.17*	0.07	041	0.19*	0.08	0.45
Age 65+	0.05*	0.01	0.24	0.05*	0.01	0.24	0.06*	0.01	0.27
Female	0.40*	0.27	0.59	0.40*	0.27	0.59	0.38*	0.26	0.57
Ratio of individual income to city income	1.05*	1.00	1.09	1.04*	1.00	1.09	1.04	0.99	1.09
In top 50% of country-level education	1.78*	1.15	2.75	1.77*	1.13	2.77	1.72*	1.13	2.62
Married	1.92*	1.09	3.40	1.92*	1.08	3.42	2.23*	1.19	4.16
Migrant to megacity	0.83	0.54	1.29	0.83	0.54	1.29	0.78	0.49	1.24
Unemployed	5.01*	2.23	11.24	5.01*	2.24	11.23	5.71*	2.50	13.05
Neighbourhood-level fixed effects
Ratio of neighbourhood income to city income				1.01	0.73	1.42
Percent married in neighbourhood							0.98*	0.97	0.99
Random effects	Variance estimate	Zero G test χ2	p Value	Variance estimate	Zero G test χ2	p Value	Variance estimate	Zero G test χ2	p Value
Intercept	0.12	1.80	0.090	0.12	1.80	0.090	0.08	1.01	0.157

* =p<0.05.

†Externalising disorders include behavioural (intermittent explosive disorder) and substance use (alcohol and drug abuse with or without dependence) disorders.

‡Models include the above variables as well as fixed effects for city and for having a missing (‘do not know’ or refused) value on individual unemployment.