Does chronic disease influence susceptibility to the effects of air pollution on depressive symptoms in China?

Table 3 Association of air pollution intensity and depressive symptoms and the role of chronic disease: Robustness test

Variables	Influence of SO₂ emission intensity on depressive symptoms				Influence of TSP emission intensity on depressive symptoms
	Model 1		Model 2		Model 3		Model 4
	Coef.	Std. Err.	Coef.	Std. Err.	Coef.	Std. Err.	Coef.	Std. Err.
Association of air pollution intensity and depressive symptoms and the role of chronic disease among respondents without mental-related chronic disease (N = 10,508)
Log of SO₂ intensity	0.952***	0.141	0.901***	0.145	–	–	–	–
Log of TSP intensity	–	–	–	–	0.929***	0.115	0.875***	0.118
Chronic disease	–	–	0.993***	0.113	–	–	0.991***	0.113
Log of SO₂ intensity × chronic disease	–	–	0.256*	0.138	–	–	–	–
Log of TSP intensity × chronic disease	–	–	–	–	–	–	0.240**	0.118
Adjusted R²	0.123		0.139		0.123		0.140
Wald Chi square	862***		961***		876***		974***

	Model 5		Model 6		Model 7		Model 8
	Marginal effects	Boot. Std.	Marginal effects	Boot. Std.	Marginal effects	Boot. Std.	Marginal effects	Boot. Std.
Association of air pollution intensity and depressive symptoms and the role of chronic disease: Tobit model (N = 23,268)
Log of SO₂ intensity	1.122***	0.101	0.969***	0.090	–	–	–	–
Log of TSP intensity	–	–	–	–	1.169***	0.071	0.989***	0.068
Chronic disease	–	–	1.227***	0.056	–	–	1.230***	0.065
Log of SO₂ intensity × chronic disease	–	–	0.191***	0.063	–	–	–	–
Log of TSP intensity × chronic disease	–	–	–	–	–	–	0.248***	0.061
Sigma(u)	2.484***	0.054	2.406***	0.038	2.491***	0.042	2.414***	0.040
Sigma(e)	3.663***	0.029	3.661***	0.024	3.653***	0.037	3.650***	0.030
Log likelihood	− 67,019		− 66,835		− 66,985		− 66,798

	Model 9		Model 10		Model 11		Model 12
	Marginal effects	Boot. Std.	Marginal effects	Boot. Std.	Marginal effects	Boot. Std.	Marginal effects	Boot. Std.
Association of air pollution intensity and depressive symptoms and the role of chronic disease among respondents without mental-related chronic disease: Tobit model (N = 10,508)
Log of SO₂ intensity	0.832***	0.122	0.788***	0.128	–	–	–	–
Log of TSP intensity	–	–	–	–	0.812***	0.102	0.765***	0.118
Chronic disease	–	–	0.869***	0.102	–	–	0.866***	0.114
Log of SO₂ intensity × chronic disease	–	–	0.221**	0.091	–	–	–	–
Log of TSP intensity × chronic disease	–	–	–	–	–	–	0.208**	0.107
Sigma(u)	2.098***	0.068	2.052***	0.064	2.103***	0.071	2.056***	0.070
Sigma(e)	3.440***	0.042	3.441***	0.050	3.434***	0.038	3.435***	0.048
Log likelihood	− 29,353		− 29,307		− 29,344		− 29,297

Models 1–4 are estimated using the xi:xtreg-command in Stata 14, models 5–12 are estimated using the xi:xttobit-command. Decentralization was calculated using the center-command, and Marginal effects was calculated using the margins-command
Control variables included individual’s demographic, socioeconomic status, health behaviors and city-level climate variables in living areas. City dummy variables were also controlled
* P < 0.10; ** P < 0.05; *** P < 0.01

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