Skip to main content

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

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

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

  1. 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
  2. Control variables included individual’s demographic, socioeconomic status, health behaviors and city-level climate variables in living areas. City dummy variables were also controlled
  3. * P < 0.10; ** P < 0.05; *** P < 0.01
Back to article page

International Journal of Mental Health Systems

ISSN: 1752-4458