Socio-demographic characteristics of all participants
93.26% of 1839 participants were of Han ancestry, the average age of which were 33.5 ± 8.17 years. Among them, 69.01% had a college education and approximately half (52.04%) had individual income per month over 5000 RMB. 83.14% of those persons were married. 78.47% had one child at least. 93.2% of those 1839 persons were employed. Table 1 showed all the demographic information for 1839 common participants. All those 900 health care providers came from hospitals(80.33%) or family planning organizations(19.67%). 93.88% of them were obstetrics and gynecology physicians and others were family planning practitioners. In those obstetrics and gynecology physicians, 21.02% served in the department of family planning in hospitals.
Table 1
Socio-demographic characteristics of participants (n = 1839)
Socio-demographic characteristics
|
cases
|
Frequency (%)
|
Age(years)a
|
≤ 30
|
666
|
36.22
|
31–40
|
758
|
41.22
|
≥ 41
|
415
|
22.57
|
Nationality
|
Han nationality
|
1715
|
93.26
|
minority nationality
|
124
|
6.74
|
Level of education
|
Junior high school or below
|
263
|
14.30
|
Middle special / senior high school
|
307
|
16.69
|
Junior college
|
1178
|
64.06
|
Master degree or above
|
91
|
4.95
|
Marital status
|
Unmarried
|
256
|
13.92
|
Married
|
1583
|
86.08
|
Number of children
|
0
|
396
|
21.53
|
1
|
708
|
38.50
|
≥ 2
|
735
|
39.97
|
Occupation
|
Public employees
|
389
|
21.15
|
Professional and technical personnel
|
716
|
38.93
|
Self-employed
|
112
|
6.09
|
Farming
|
497
|
27.03
|
Unemployed
|
125
|
6.80
|
Account
|
Country registered residence
|
890
|
48.40
|
|
City registered residence
|
949
|
51.60
|
Monthly income
|
<3000¥
|
291
|
15.82
|
3000–5000¥
|
591
|
32.14
|
5000–10000¥
|
509
|
27.68
|
>100000¥
|
448
|
24.36
|
Living condition
|
Rural area
|
552
|
36.22
|
Urban
|
1085
|
41.22
|
Suburb
|
202
|
22.57
|
Number of boys
|
0
|
825
|
14.30
|
1
|
791
|
16.69
|
≥ 2
|
223
|
64.06
|
Status of abortion and Conception Control
30.61%(563/1839) of participants had the history of induced abortion, and 19.96% (367/930) experienced repeated abortion. 28.90% of 256 unmarried women had at least one abortion. Only 45.02% of 1839 participants insisted on adopting contraceptive methods every time during sex. 25.93%(477/1839) chose a LARC as the main contraceptive method.
Performance of PAC and in our study
12.23% of participants applied PAC services. The women with age less than 20-years old or receiving only elementary school education or even lower knowing nothing about PAC services. Comparing to persons beyond 41 years old, the women with age between 20–40 years olds seldom used PAC services(OR:0.301 95%CI: 0.167–0.541 for the group of 20–30 years old and OR:0.474, 95%CI: 0.321–0.701 for the group of 30–40 years old respectively). Participants who lived in urban had a higher prevalence of using PAC services(OR:2.798, 95%CI: 1.419–5.496). Except that, women with technical jobs just like lawyers, teachers or medical staffs more frequently used PAC services(OR:6.971, 95%CI: 1.580–30.76). We pointed out the person with monthly income lower than 10000 (p < 0.01) and the person obtaining free contraceptives inconveniently (p = 0.000) was main influencing factors for the acceptability of PAC services(Table 2). In our investment for 900 health care providers, 66.11% of their work units provided PAC services. PAC services were carried out mainly in 3-A-grade General Hospitals and maternal and child health institutions The application of PAC services was only 12.4% in primary hospitals. There was significant difference in rates of supplying PAC services between their workplaces with and without the department of family planning.
Table 2
Main factors associated with PAC use among participants: logistic regression.
Variable
|
Odds ratio (95 CI)
|
P–Value
|
Age
|
21–30
|
0.301(0.167–0.541)
|
0.000*
|
31–40
|
0.474(0.321–0.701)
|
0.000*
|
≥ 41
|
1
|
|
Occupation
|
Public employees
|
3.572(0.791–16.121)
|
0.098
|
Professional and technical personnel
|
6.971(1.580–30.760)
|
0.010*
|
Self-employed
|
2.963(0.552–15.889)
|
0.205
|
Farming
|
5.942(0.731–16.246)
|
0.095
|
Unemployed
|
1
|
|
Monthly income
|
<3000¥
|
0.772(0.378–1.827
|
0.517
|
3000–5000¥
|
0.452(0.277–0.739)
|
0.002*
|
5000–10000¥
|
0.612(0.404–0.928)
|
0.021*
|
>100000¥
|
1
|
|
Living condition
|
Rural area
|
1.315(0.564–3.064)
|
0.553
|
Urban
|
2.798(1.419–5.496)
|
0.003*
|
Suburb
|
1
|
|
Obtain free contraceptives in time
|
Not in time
|
0.269(0.172–0.422)
|
0.000
|
In time
|
1
|
|
Factors associated with applications of free Contraceptives
In our study, 51.22% (942/1839) of people did not obtain contraceptives free of charge from the government. Worrying about the quality of contraceptives, being unsatisfied with models and types and feeling embarrassed were main reasons for them to refuse free contraceptives. All those influence factors were described in Fig. 1. Family planning departments, self-service terminal for free contraceptives and department of gynecology in public hospitals are main sources of which people at reproductive age to obtain free contraceptives(88.4%). The satisfaction with those approachs was only 57.44%(874/1839). Youger women(20–40 years old) had a lower incidence of using free contraceptives comparing to women being over 40 year-old. The participants’monthly income lower than 3000 or between 3000–5000 had higher odds of using free contraceptives(OR: 2.119, 95%CI:1.125–3.991 and OR: 2.014, 95%CI:1.260–3.221 respectively) The higher income people, the population living in urban and suburb, and the persons being self-employed or without working did not intend to obtain free contraceptives(p < 0.05)(Table 3). We also analyzed the influence factors for betimes of obtaining free contraceptives.The major factors were also associated with intention to use free contraceptives. Another factor that the women had more than one boy was also strongly associated with timeliness(OR:2.066, 95%CI:1.265–3.374) (Table 4).
Table 3
The strong influence factors associated with intention to use free contraceptives
Variable
|
Odds ratio (95 CI)
|
P–Value
|
Age(years)a
|
≤ 30
|
0.335(0.201–0.560)
|
0.000*
|
31–40
|
0.011(0.423–0.869)
|
0.011*
|
≥ 41
|
1
|
|
Occupation
|
Public employees
|
2.441(1.036–5.754)
|
0.041*
|
Professional and technical personnel
|
2.336(1.001–5.450)
|
0.050*
|
Self-employed
|
0.779(0.234–2.590)
|
0.464
|
Farming
|
2.738(0.819–9.150)
|
0.102*
|
Unemployed
|
1
|
|
Monthly income
|
<3000¥
|
2.119(1.125–3.991)
|
0.02
|
3000–5000¥
|
2.014(1.260–3.221)
|
0.003
|
5000–10000¥
|
1.208(0.770–1.895)
|
0.412
|
> 10000¥
|
1
|
|
Living condition
|
Rural area
|
2.059(1.139–3.722)
|
0.017*
|
Urban
|
0.843(0.506–1.403)
|
0.511
|
Suburb
|
1
|
|
Obtain free contraceptives in time
|
Not in time
|
0.083(0.043–0.160)
|
0.000*
|
In time
|
|
|
Table 4
The strong influence factors associated with the timeliness of free contraceptives use
Variable
|
Odds ratio (95 CI)
|
P–Value
|
Age(years)a
|
≤ 30
|
0.389(0.261–0.580)
|
0.000*
|
31–40
|
0.436(0.310–0.615)
|
0.000*
|
≥ 41
|
1
|
|
Level of education
|
Junior high school or below
|
0.375(0.112–1.252)
|
0.111
|
Middle special / senior high school
|
0.340(0.485–1.029)
|
0.000*
|
Junior college
|
0.706(0.485–1.029)
|
0.070
|
Master degree or above
|
1
|
|
Occupation
|
Public employees
|
1.477(1.096–2.609)
|
0.042*
|
Professional and technical personnel
|
1.775(1.096–3.061)
|
0.02*
|
Self-employed
|
0.737(0.412–1.318)
|
0.303
|
Farming
|
4.601(0.956–22.151)
|
0.057
|
Unemployed
|
1
|
|
Monthly income
|
<3000¥
|
1.780(1.085–2.920)
|
0.022*
|
3000–5000¥
|
1.974(1.388–2.809)
|
0.000*
|
5000–10000¥
|
1.680(1.222–2.309)
|
0.001*
|
>100000¥
|
1
|
|
Living condition
|
Rural area
|
1.155(0.731–1.871)
|
0.559
|
Urban
|
0.536(0.354–0.811)
|
0.003*
|
Suburb
|
1
|
|
Number of boys
|
≥ 2
|
2.066(1.265–3.374)
|
0.004*
|
|
1
|
1.354(0.999–1.835)
|
0.051
|
|
0
|
1
|
|
Our survey showed that the contraceptives free of charge were provided in 87.22% of the 900 health care providers’ work units. Obtaining from self-service terminal for free contraceptives(35.84%) and having prescriptions of free contraceptives after counselling (21.74%) were main approaches. The staff faced many difficulties in promoting contraceptive service provision, which were showed in Fig. 2.
Knowledge and performance of LARC and in our study
In this study, only 46.80% of 1839 people know exactly about types of LARC. Few (9.74% had used IUDs, 1.53% had used implants and 6.96% had used vasoligation or female ligation) used LARC. 27.80% participant took regard condom as LARC and 50.49% of them took the condom as the main contraceptive method. 29.8% of the women had the intention to use IUDs or implants during the post abortion period. By using binary logistic regression, the following factors for LARC use were identified as risk factors for age, job, educational level, monthly income, the use of PAC services. (Table 5). We also used binary logistic regression logistic regression to analyze variables that had the significant correlation with a woman’s intention to use a LARC after abortion or after childbirth. The result showed that the women who had less than one boy, used PAC services, obtained free contraceptives and were between 30–40 years old were more likely to use a LARC(Table 6).
Table 5
The main factors associated with LARCs use in our study
Variable
|
Odds ratio (95 CI)
|
P–Value
|
Age(years)a
|
≤ 30
|
0.483(0.284–0.822)
|
0.007*
|
31–40
|
0.724(0.494–1.061)
|
0.097*
|
≥ 41
|
1
|
|
Level of education
|
Junior high school or below
|
2.766(0.604–12.688)
|
0.190
|
Middle special / senior high school
|
1.742(0.870–3.491)
|
0.117*
|
College
|
1.867(1.175–2.969)
|
0.008*
|
Master degree or above
|
1
|
|
Occupation
|
Public employees
|
0.748(0.380–1.880)
|
0.681
|
Technologists
|
2.291(1.063–4.936)
|
0.034*
|
Self-employed
|
1.017(0.413–2.552)
|
0.955
|
Farming
|
0.614–7.715
|
0.235
|
Unemployed
|
1
|
|
Monthly income
|
<3000¥
|
1.740(0.887–3.412)
|
0.107
|
3000–5000¥
|
1.920(1.204–3.065)
|
0.006*
|
5000–10000¥
|
1.043(0.666–1.634)
|
0.853
|
>100000¥
|
1
|
|
Use of PAC services
|
No
|
0.413–0.941
|
0.025*
|
|
Yes
|
1
|
|
Table 6
Associations between factors and an intention to use LARCs among women with unintended pregnancy after abortion
Variable
|
Odds ratio (95 CI)
|
P–Value
|
Age(years)a
|
≤ 30
|
0.718(0.488–1.054)
|
0.093
|
31–40
|
0.689(0.506–0.940)
|
0.019*
|
≥ 41
|
1
|
|
Number of children
|
0
|
0.344(0.135–0.876)
|
0.025*
|
|
1
|
0.733(0.355–1.516)
|
0.403
|
|
≥ 2
|
1
|
|
obtain free contraceptives in time
|
Not in time
|
0.609(0.459–0.808)
|
0.001*
|
In time
|
1
|
|
Use of PAC services
|
No
|
0.469(0.334–0.659)
|
0.000*
|
|
Yes
|
1
|
|
For 900 health care providers, about 60.78% of them have recommended IUDs to women after abortion. The staff worked in 3-A-grade General Hospitals were 3.220 times significantly more likely to recommend IUDs to women after abortion compared to those who worked in Family Planning Service Center(OR = 3.220, 95%CI:1.788–5.797). The situation was also observed in the staff who worked in Women's and children's Hospital comparing to those who worked in Family Planning Service Center (OR = 2.143, 95%CI:1.274–3.603). Health care providers whose workplaces set up the department of family planning(OR = 1.544, CI:1.067–2.233) or supplied PAC services(OR = 1.987, 95%CI:1.412–2.795) were more likely to recommend IUDs to women after abortion. Comparing to the persons working in the department of maternal and child health, gynaecologists especially working in the department of family planning had higher odds to recommend women to use IUD after abortion(OR = 2.234, 95%CI:1.303–3.892) (Table 7). Only 29.78% of them recommend IUDs to unmarried and childless women. The significant predictors described above also influenced health care providers to recommend IUDs after abortion (Talbe 8).
Table 7
The main factors closely related with the intention to recommend IUDs to women after abortion
Variable
|
Odds ratio (95 CI)
|
P–Value
|
Workplace.
|
3-A-grade General Hospitals
|
3.220(1.788–5.797)
|
0.000
|
the basic hospital.
|
1.236(0.771–1.981)
|
0.379
|
Women's and children's Hospital
|
2.143(1.274–3.603)
|
0.004
|
|
Family Planning Service Center
|
1
|
|
Setting up
|
Yes
|
1.544(1.067–2.233)
|
0.021
|
the department of family planning
|
No
|
1
|
|
Department
|
Gynecology department
|
1.990(1.262–3.139)
|
0.003
|
Obstetrics department
|
1.319(0.799–2.810)
|
0.279
|
the department of family planning
|
2.234(1.303–3.829)
|
0.003
|
Department of maternal and child health
|
1
|
|
Supplying PAC services
|
Yes
|
1.987(1.412–2.795)
|
0.000*
|
No
|
1
|
|
Table 8
The main factors closely related with the intention to recommend IUDs to unmarried and childless women
Variable
|
Odds ratio (95 CI)
|
P–Value
|
Workplace.
|
3-A-grade General Hospitals
|
2.485(1.287–4.797)
|
0.007
|
the basic hospital.
|
2.165(1.165–4.030)
|
0.015
|
Women's and children's Hospital
|
2.238(1.213–4.128)
|
0.010
|
|
Family Planning Service Center
|
1
|
|
Setting up
|
Yes
|
1.545(1.089–2.412)
|
0.05
|
the department of family planning
|
No
|
1
|
|
Department
|
Gynecology department
|
2.167 (1.354–3.496)
|
0.001
|
Obstetrics department
|
0.637(0.488–1.551)
|
0.637
|
the department of family planning
|
2.737(1.558–4.807)
|
0.000
|
Department of maternal and child health
|
1
|
|
Supplying PAC services
|
No
|
0.419(0.263–0.635)
|
0.000*
|
|
Yes
|
1
|
|