“…To reduce potential confounding effects, several variables commonly thought to correlate with job-related wellbeing were controlled for both steps of the study. The personal characteristics were measured by a region variable (0 = rural, 1 = urban) [ 22 ], a gender variable (0 = female, 1 = male) [ 22 , 25 ], an age group variable (1 = 20 or below, 2 = 21–30, 3 = 31–40, 4 = above 40) [ 22 ], marital status (0 = unmarried, 1 = married) [ 22 ], education (1 = college or below, 2 = bachelor, 3 = master, 4 = doctor) [ 3 , 23 ], working hours per week (1 = 20 h or below, 2 = 21–40 h, 3 = 41–60 h, 4 = 61–80 h, 5 = above 80 h) [ 3 , 24 , 29 ], annual income (1 = RMB 10,000 or below, 2 = RMB 10,001–50,000, 3 = RMB 50,001–100,000, 4 = RMB 100,001–150,000, 5 = RMB 150,000 or above) [ 22 , 25 , 29 ], and industry variables which are consist of 9 type of industries, including civil service(reference group in the first step), farming/mining(0 = no, 1 = yes), manufacturing(dummy variable 0 = no, 1 = yes in the first step, reference group in the second step), power supply/construction/geological exploration/hydraulic management(0 = no, 1 = yes), transportation and network(0 = no, 1 = yes), whole/retail/restaurant(0 = no, 1 = yes), real state/finance(0 = no, 1 = yes), science/education/arts/health/media/social service(0 = no, 1 = yes), and others(0 = no, 1 = yes) [ 23 , 24 , 29 ].…”