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Table 4 BMI estimates (outcome equation) of the endogenous treatment effects model with an ordered outcome considering potential endogeneity between smoking and body weight

From: An empirical investigation of the impact of smoking on body weight using an endogenous treatment effects model approach: the role of food consumption patterns

Variables BMI
Full sample Males Females
Smoker (smoking participation) 1.155*** 1.236*** 0.634*
(0.335) (0.439) (0.332)
Sociodemographic characteristicsa
 Gender (women) 0.329***
(0.070)   
 30–60 years old 0.536*** 0.554*** 0.463***
(0.110) (0.166) (0.112)
 Over 60 years old 1.022*** 0.948*** 0.879***
(0.191) (0.258) (0.170)
 Married 0.332*** 0.418*** 0.206**
(0.101) (0.153) (0.102)
 Divorced/widowed 0.261** 0.158 0.222*
(0.114) (0.180) (0.118)
 Big city −0.198*** −0.169 −0.188**
(0.075) (0.110) (0.081)
 Village/Rural area 0.124* 0.130 0.116
(0.071) (0.107) (0.079)
Frequent consumption of:
 Whole grain bread 0.014 −0.075 0.080
(0.059) (0.087) (0.070)
 White-toasted bread −0.158** −0.337*** 0.040
(0.073) (0.122) (0.078)
 Fruits 0.107 0.115 0.077
(0.075) (0.108) (0.093)
 Vegetables 0.014 0.008 −0.005
(0.061) (0.091) (0.070)
 Meat products 0.318*** 0.408*** 0.234***
(0.083) (0.153) (0.076)
 Deep fried foods −0.067 −0.216 0.140
(0.107) (0.147) (0.156)
 Confectionery −0.160*** −0.217** − 0.113**
(0.058) (0.089) (0.065)
μ1 −1.805 −2.273 −1.135
μ2 1.033 0.946 1.142
μ3 2.495 2.689 2.171
Log-Likelihood (both stages) − 5423.587 − 2800.598 − 2584.326
  1. Standard errors are given in parentheses
  2. aAge: 18–29 years old (reference category). Marital status: single (reference category)
  3. Area of residence: town (reference category)
  4. *p < 0.1. **p < 0.05. ***p < 0.01 (Statistically significant variables are highlighted in bold)