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Table 4 Association of air pollution emission per capita/per unit area 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
Marginal effects Boot. Std. Marginal effects Boot. Std. Marginal effects Boot. Std. Marginal effects Boot. Std.
Association of air pollution emission per unit area (tons per square kilometer) and depressive symptoms and the role of chronic disease among respondents without mental-related chronic disease: Tobit model (N = 10,508)
 Log of SO2 emission per unit area 0.191 0.163 0.156 0.153
 Log of TSP emission per unit area 0.490*** 0.132 0.419*** 0.161
 Chronic disease 0.856*** 0.107 0.861*** 0.094
 Log of SO2 emission per unit area × chronic disease 0.161* 0.093
 Log of TSP emission per unit area × chronic disease 0.284** 0.124
 Sigma(u) 2.088*** 0.063 2.040*** 0.079 2.092*** 0.057 2.043*** 0.072
 Sigma(e) 3.453*** 0.042 3.456*** 0.040 3.449*** 0.037 3.451*** 0.040
 Log likelihood − 29,375 − 29,329 − 29,368 − 29,320
  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 emission per capita (tons per 10 thousand people) and depressive symptoms and the role of chronic disease among respondents without mental-related chronic disease: Tobit model (N = 10,508)
 Log of SO2 emission per capita 0.359*** 0.122 0.332** 0.137
 Log of TSP emission per capita 0.615*** 0.121 0.564*** 0.122
 Chronic disease 0.860*** 0.114 0.865*** 0.088
 Log of SO2 emission per capita × chronic disease 0.145 0.105
 Log of TSP emission per capita × chronic disease 0.211* 0.118
 Sigma(u) 2.089*** 0.072 2.041*** 0.057 2.093*** 0.081 2.046*** 0.076
 Sigma(e) 3.452*** 0.041 3.455*** 0.034 3.447*** 0.048 3.449*** 0.037
 Log likelihood − 29,374 − 29,329 − 29,365 − 29,319
  1. Models 1–8 are estimated using the xi:xttobit-command in Stata 14. 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