Skip to main content

Table 1 Descriptive analysis of the variables

From: Are social security policies for Chinese landless farmers really effective on health in the process of Chinese rapid urbanization? a study on the effect of social security policies for Chinese landless farmers on their health-related quality of life

 

Grades and answers

%

x ¯ ± s

Skewness

Standard error of skewness

Kurtosis

Standard error of kurtosis

Independent variables

Mobility

1 = I can walk anywhere without any problems

41.7

1.90 ± 0.852

0.191

0.070

−1.597

0.140

2 = I have some problems in mobility

26.5

3 = I cannot get up

31.8

Self-care

1 = I can take good care of myself without any problems

39.6

1.95 ± 0.859

0.101

0.071

−1.637

0.141

2 = I have some problems in washing my face, brushing my teeth, bathing, and dressing

26.0

3 = I cannot wash my face, brush my teeth, bathe, and dress

34.3

Daily activities

1 = I can perform my daily activities without any problems

36.4

1.95 ± 0.822

0.092

0.070

−1.515

0.140

2 = I have some problems in performing my daily activities

32.2

3 = I cannot perform my daily activities

31.4

Pain/discomfort

1 = I do not feel any pain/discomfort

37.7

1.97 ± 0.852

0.051

0.070

−1.623

0.141

2 = I feel moderate pain/discomfort

27.3

3 = I feel extreme pain/discomfort

35.0

Anxiety/depression

1 = I do not feel anxiety/depression

37.5

1.99 ± 0.858

0.027

0.071

−1.641

0.141

2 = I feel moderate anxiety/depression

26.5

3 = I feel serious anxiety/depression

36.1

Dependent variables

Policy1

Land acquisition compensation policy

 

2.82 ± 1.325

0.199

0.071

−1.118

0.142

Policy2

Medical insurance policy

 

2.76 ± 1.457

0.253

0.070

−1.351

0.140

Policy3

Pension insurance policy

 

2.68 ± 1.396

0.438

0.070

−1.138

0.140

Policy4

Employment security policy

 

2.78 ± 1.435

0.229

0.070

−1.352

0.140

Policy5

Basic livelihood guarantee policy

 

2.86 ± 1.346

0.226

0.071

−1.213

0.141

 

Policy6

Housing compensation policy

 

2.65 ± 1.476

0.279

0.070

−1.395

0.139