Background
Methods
Sample
Latent variables
Variables | Value |
---|---|
Demographic information | |
1.Gender | 1 = male, 2 = female |
2.Age in years | 1 = 15–29, 2 = 30–44, 3 = 45–59, 4 = 60–69, 5 = 70–79 |
3.BMI | 1 = underweight, 2 = healthy weight, 3 = overweight, 4 = obese |
4.Marital status | 1 = unmarried, 2 = married, 3 = divorce, 4 = widowed |
5.Residence: location from nearest medial institutions | 1 = < 1 km, 2 = ≤3 km, 3 = ≤5 km, 4 = >5 km |
SES | |
6.Monthly income | 1 = < 1000 RMB [¥], 2 = 1000–2999 RMB [¥], 3 = 3000–4999 RMB [¥], 4 = ≥5000 RMB [¥] |
7.Occupation | 1 = unemployed, 2 = agricultural worker, 3 = worker, 4 = business personnel, freelancer, 5 = enterprise worker, 6 = institutional staff, 7 = civil Servants |
8.Education | 1 = primary school or below, 2 = junior high school, 3 = senior high school, 4 = associate bachelor or above |
Health literacy | |
9.Health knowledge | 1 = poor status (correct rate < 80%) 2 = not poor (correct rate ≥ 80%) |
10.Health behavior | 1 = poor status (correct rate < 80%) 2 = not poor (correct rate ≥ 80%) |
11.Health skills | 1 = poor status (correct rate < 80%) 2 = not poor (correct rate ≥ 80%) |
Statistical analysis
Results
Participants and HL status
Variables | N/% | Health literacy N/% |
χ
2
/ P
|
---|---|---|---|
gender | 11.686*** | ||
male | 603 (51.80) | 84 (13.93) | |
female | 561 (48.20) | 121 (21.57) | |
Age (years) | 135.154*** | ||
15~29 | 248 (21.31) | 84 (33.87) | |
30~44 | 256 (21.99) | 78 (30.47) | |
44~59 | 426 (36.60) | 38 (8.92) | |
60~69 | 151 (12.97) | 3 (1.99) | |
70~79 | 83 (7.13) | 2 (2.41) | |
BMI | 3.215 | ||
emaciation | 100 (8.59) | 16 (16.00) | |
normal | 703 (60.40) | 135 (19.20) | |
overweight | 292 (25.09) | 43 (14.73) | |
obesity | 69 (5.93) | 11 (15.94) | |
Marital status | 32.555*** | ||
unmarried | 197 (16.92) | 58 (29.44) | |
married | 923 (79.30) | 144 (15.60) | |
divorced and widowed | 44 (3.78) | 3 (6.82) | |
Residences (km) | 10.844* | ||
< 1 | 604 (51.89) | 97 (16.06) | |
≤ 3 | 376 (32.30) | 85 (22.61) | |
≤ 5 | 117 (10.05) | 14 (11.97) | |
> 5 | 67 (5.76) | 9 (13.43) | |
Income (RMB/month) | 35.646*** | ||
< 1000 | 333 (28.61) | 27 (8.11) | |
< 3000 h | 601 (51.63) | 119 (19.80) | |
< 5000 | 171 (14.69) | 48 (28.07) | |
≥ 5000 | 59 (5.07) | 11 (18.64) | |
Occupation | 284.675*** | ||
unemployed | 166 (14.26) | 27 (16.27) | |
farmer or worker | 594 (51.03) | 37 (6.23) | |
businessman and freelancer | 160 (13.74) | 21 (13.12) | |
enterprise staff | 34 (2.92) | 8 (23.53) | |
institution or government staff | 210 (18.04) | 125 (51.23) | |
Education | 342.265*** | ||
Primary school or below | 361 (31.01) | 5 (1.39) | |
Junior high school | 433 (37.20) | 54 (12.47) | |
Senior high school | 179 (15.38) | 46 (25.70) | |
associate bachelor or above | 191 (16.41) | 100 (52.36) | |
Total | 1164 (100.00) | 205 (17.61) | – |
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | |
---|---|---|---|---|---|---|---|---|---|---|---|
Demographic information | |||||||||||
1.Gender | 1 | ||||||||||
2.Age | −.100** | 1 | |||||||||
3.BMI | −.156** | .096** | 1 | ||||||||
4.Marital status | .003 | .550** | .104** | 1 | |||||||
5.Residence | .081** | .095** | .045 | .090** | 1 | ||||||
Socioeconomic status | |||||||||||
6.Monthly income | −.073** | −.360** | .003 | −.184** | −.016 | 1 | |||||
7.Occupation | .023 | −.279** | −.028* | .015 | −.074** | .293** | 1 | ||||
8.Education | −.057* | −.556** | −.055* | −.230** | −.132** | .369** | .688** | 1 | |||
Health literacy | |||||||||||
9.Health knowledge | .057* | −.375** | −.066* | −.183** | −.006 | .187** | .347** | .435** | 1 | ||
10.Health behavior | .061* | −.257** | −.067 | −.095** | .007 | .136** | .336** | .374** | .372** | 1 | |
11.Health skill | −.053* | −.213** | −.018 | −.104** | −.090** | .139** | .255** | .282** | .288** | .301** | 1 |
Measurement model
Structural equation model
Variables | Effects |
---|---|
Demographic information | |
Age | −0.499 |
BMI | −0.032 |
Residence | 0.050 |
Socioeconomic status | |
Monthly income | 0.335 |
Occupation | 0.574 |
Education | 0.801 |