| Literature DB >> 21284893 |
Zhiyong Liu1, Minmin Zhu, Hassan H Dib, Zi Li, Shuhua Shi, Zengzhen Wang.
Abstract
BACKGROUND: Large numbers of unmarried migrants are on the continuous move from rural-to-urban areas within China mainland, meanwhile their Reproductive Health (RH) is underserved when it is compared with the present urban RH policies. The purpose of this study is to investigate the RH knowledge and the utilization of RH services among unmarried migrants.Entities:
Mesh:
Year: 2011 PMID: 21284893 PMCID: PMC3044659 DOI: 10.1186/1471-2458-11-74
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Social and demographic characteristics of unmarried rural-to-urban migrants in the three chosen cities in China
| characteristics | No. of Gender (%) | Total | |
|---|---|---|---|
| Han | 1622 (96.6) | 1648 (95.2) | 3270 (95.6) |
| minority | 56 (3.4) | 84 (4.9) | 140 (4.1) |
| Illiterate | 14 (0.8) | 20 (1.2) | 34 (1.0) |
| Elementary school | 46 (2.7) | 194 (11.2) | 240 (7.0) |
| Junior school | 810 (48.2) | 747 (43.1) | 1557 (45.6) |
| high school/technical secondary school | 640 (38.1) | 582 (33.6) | 1222 (35.8) |
| College and above | 170 (10.1) | 180 (10.9) | 350 (10.3) |
| 15-19 | 412 (24.5) | 602 (34.8) | 1014 (29.7) |
| 20-24 | 1012 (60.3) | 994 (57.4) | 2006 (58.8) |
| 25-29 | 198 (11.8) | 110 (6.4) | 308 (9.0) |
| ≥30 | 58 (3.5) | 26 (1.5) | 84 (2.7) |
| Less than 1 | 261 (15.5) | 254 (14.7) | 515 (15.1) |
| 1~ | 430 (25.6) | 470 (27.1) | 900 (26.4) |
| 2~ | 312 (18.6) | 338 (19.5) | 650 (19.1) |
| 3~ | 341 (20.3) | 416 (24.0) | 757 (22.2) |
| 5~ | 228 (13.6) | 178 (10.3) | 406 (11.9) |
| ≥10 year | 108 (6.5) | 76 (4.4) | 184 (5.4) |
| construction | 20 (1.2) | 0 | 20 (0.6) |
| traffic and storage | 28 (1.7) | 0 | 28 (0.8) |
| communication | 10 (0.6) | 4 (0.2) | 14 (0.4) |
| trade and food | 358 (21.3) | 570 (32.9) | 928 (27.2) |
| real estate | 6 (0.4) | 8 (0.5) | 14 (0.4) |
| finance and insurance | 6 (0.4) | 10 (0.6) | 16 (0.5) |
| manufacturing enterprise | 916 (54.5) | 896 (51.7) | 1812 (53.1) |
| social work | 238 (14.2) | 166 (9.6) | 404 (11.8) |
| Self-employed a | 98 (5.8) | 78 (4.5) | 176 (5.2) |
| Under 600 | 86 (5.1) | 66 (3.8) | 152 (4.5) |
| 600~ | 756 (45.0) | 986 (56.9) | 1742 (51.1) |
| 1000~ | 490 (29.2) | 440 (25.4) | 930 (27.3) |
| 1500~ | 192 (11.4) | 188 (10.9) | 380 (11.1) |
| above2000 | 156 (9.3) | 52 (3.0) | 208 (6.1) |
| Inter province | 960 (57.1) | 950 (54.9) | 1910 (56.0) |
| within province | 720 (42.9) | 782 (45.2) | 1502 (44.0) |
| Guangzhou | 662 (39.4) | 708 (40.9) | 1370 (40.2) |
| Shenzhen | 490 (29.2) | 522 (30.1) | 1012 (29.7) |
| Wuhan | 528 (31.4) | 502 (29.0) | 1030 (30.2) |
Note: . self-employment laborers refer to people who run a private small-scale business by themselves, such as vendors, rice-noodle sellers, food-shop owners, and tailor-shop owners.
Participants' distribution of responses in the three chosen cities in China about reproductive health knowledge (accurate) and condom
| RH knowledge (n, %) | Condom use (n, %) | |||||||
|---|---|---|---|---|---|---|---|---|
| Pregnancy and fertilization knowledge | contraception knowledge | Family planning policy knowledge | STD/AIDS spread approach | Never used | occasionally | half the time | Every time | |
| Male(1680) | 403 (24.0)*** | 146 (8.9) | 744 (44.3) | 886 (52.7) | 232 (49.4) | 153 (32.6) | 67 (14.3) | 18 (3.8) |
| Female(1732) | 601 (34.7) | 161 (9.3) | 705 (40.7) | 948 (54.7) | 107 (43.5) | 80 (32.5) | 48 (19.5) | 11 (4.5) |
| 15-20(1014) | 194(19.1) | 93(9.2) | 355(35.0) | 430(42.4) | ||||
| 20-24(2006) | 672(33.5)** | 183(9.3) | 879(43.9)** | 1152(52.4)** | ||||
| 25-29 (308) | 103(33.5)** | 30(9.7) | 171(55.6)** | 196(53.6)** | ||||
| 30 and above(84) | 36(42.6)*** | 6(7.1) | 42(50.0)** | 56(62.7)** | ||||
| blue-collar(2788) | 800(28.7) | 259(9.3) | 948(34.0) | 1628(53.4) | ||||
| Self-employed laborers(448) | 160(35.8)* | 29(6.4) | 196(43.8)** | 301(62.3)* | ||||
| White-collar(176) | 75(42.6)** | 22(12.4) | 98(55.6)** | 104(55.0) | ||||
| Shenzhen(1012) | 293(29.0) | 71(7.0) | 405(40.0) | 588(55.1) | ||||
| Guangzhou (1370) | 395(28.8) | 141(10.3) | 527(38.5) | 747(54.5) | ||||
| Wuhan (1030) | 317(30.8) | 99(9.6) | 521(50.6)* | 499(48.4)** | ||||
Notes: *** p ≤ 0.001; ** p ≤ 0.01; * p ≤ 0.05;
b. we have regrouped "construction, traffic and storage, trade and food, manufacturing enterprise" to blue-collar and "communication, real estate, finance'' to white collar.
RH services utilized/obtained by unmarried rural-to-urban migrants in the three chosen cities in China
| Services | Shenzhen (n = 1370) | Guangzhou (n = 1012) | Wuhan (n = 1030) | all | χ2 value | P value |
|---|---|---|---|---|---|---|
| Female obtained | 330 (24.1) | 241 (23.8) | 404 (39.2) | 975 (28.3) | 19.313 | 0.001 |
| male obtained | 444 (32.4) | 205 (20.3) | 330 (32.0) | 979 (27.5) | 14.487 | 0.001 |
| female obtained | 673 (49.1) | 509 (50.3) | 492 (47.8) | 1674 (49.6) | 3.143 | 0.09 |
| male obtained | 704 (51.4) | 528 (52.1) | 474 (46.0) | 1706 (50.2) | 14.487 | 0.001 |
| free obtained | 292 (9.3) | 149 (14.1) | 262 (25.5) | 703 (16.1) | 28.229 | 0.0001 |
| purchased | 6 (0.4) | 12 (1.2) | 28 (2.7) | 46 (1.4) | ||
| never use | 1235 (90.2) | 851 (84.1) | 740 (71.9) | 2826 (82.6) | ||
| female obtained | 123 (50.0) | 78 (31.6) | 99 (42.5) | 246 (40.4) | 13.278 | 0.001 |
| male obtained | 247 (52.6) | 185 (39.3) | 227 (48.3) | 470 (46.9) | 13.231 | 0.001 |
Note: c. ''Pre-test results shows that males got a higher ratio of refusing to respond (more than 90%), then we set it as an item just for females.''
Logistic regression coefficients predicting RH service utilization in three Cities in China
| Variables (obtained = 1, not = 0) | RH consult services | STD/AIDS health education | RH checkup services |
|---|---|---|---|
| 0.67 (0.59, 0.75)** | 1.81 (1.59, 2.05) ** | / | |
| Shenzhen | 0.64 (0.55, 0.75)*** | 1.58 (1.32, 1.91)** | 0.15 (0.12, 0.19)*** |
| Guangzhou | 0.53 (0.46, 0.61)*** | 1.24 (1.06, 1.48)** | 0.26 (0.21, 0.32)*** |
| Elementary school | 1.36 (1.18, 1.63)*** | 1.29 (1.23, 1.34)** | 1.96(1.68, 2.28)*** |
| Junior school | 2.36 (1.95, 2.94)*** | 1.47 (1.14, 1.89)** | 2.76 (2.37, 3.82)** |
| high school | 3.48 (2.90, 4.31)** | 0.97 (0.87, 1.33) | 3.67 (2.88, 4.65)** |
| college and above | 4.01 (2.63, 6.25)*** | 0.99 (0.79, 1.24) | 3.70 (2.33, 5.88)** |
| 20-24 | 1.65 (1.50, 1.78)** | 1.22 (1.06, 1.42)* | 1.84 (1.53, 2.06)** |
| 25-29 | 3.74 (2.23, 4.03)*** | 1.31 (1.14, 1.56)** | 2.22 (1.78, 2.57)*** |
| >30 | 2.94 (2.27, 3.70)*** | 1.18 (0.94, 1.47) | 3.92 (2.76, 5.11)*** |
| 1~ | 1.17 (0.92, 1.49) | 0.97 (0.85, 1.23) | 0.63 (0.46, 0.87) *** |
| 2~ | 1.01 (0.83, 1.21) | 1.04 (0.86, 1.25) | 0.73 (0.57, 0.93)** |
| 3~ | 0.90 (0.73, 1.11) | 1.28 (1.06, 1.55)** | 0.94 (0.72, 1.21) |
| 5~ | 1.03 (0.87, 1.23) | 1.11 (0.94, 1.32) | 0.93 (0.75, 1.16) |
| >10 | 1.12 (0.95, 1.32) | 1.14 (0.97, 1.34) | 0.84 (0.68, 1.04) |
| 600~ | 1.03 (0.78, 1.34) | 1.09 (0.80, 1.65) | 0.90 (0.60, 1.41) |
| 1000~ | 0.97 (0.79, 1.25) | 1.12 (0.90, 1.54) | 0.84 (0.62, 1.16) |
| 1500~ | 1.08 (0.96, 1.27) | 1.07 (0.86, 1.39) | 0.85 (0.62, 1.20) |
| > = 2000 | 1.45 (1.02, 1.79)* | 0.99 (0.80, 1.28) | 0.91 (0.65, 1.22) |
| white-collar | 1.33 (1.11,1.61)*** | 0.67 (0.54, 0.83)** | 1.47 (1.14, 1.89)** |
| Self-employed laborers | 0.99 (0.98,1.03) | 0.52 (0.45, 0.57)** | 1.29 (1.23, 1.34)** |
| 1.077** | 3.38** | 19.36*** |
Notes: *** p ≤ 0.001; ** p ≤ 0.01; * p ≤ 0.05;
b. we have regrouped “construction, traffic and storage, trade and food, manufacturing enterprise “ to blue-collar and “communication, real estate, finance” to white collar.