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Contraceptive Counseling at Mizan-Tepi University Teaching Hospital, Southwest Ethiopia

Article Information

Rohana Martha Bruker1*, Margo Harrison2

1Center for Global Health at the Colorado School of Public Health, 2 S Ogden St Apt 21 Denver, CO 80209, USA

2Assistant Professor, Center for Global Health, Obstetrics and Gynecology and OB Health (SOM), Australia

*Corresponding author: Rohana Bruker, Center for Global Health at the Colorado School of Public Health, 2 S Ogden St Apt 21 Denver, CO 80209, USA.

Received: 27 June 2022; Accepted: 08 July 2022; Published: 23 August 2022

Citation: Rohana Bruker, Margo Harrison. Contraceptive Counseling at Mizan-Tepi University Teaching Hospital, Southwest Ethiopia. Journal of Women’s Health and Development 5 (2022):197-205.

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Abstract

Background: In Ethiopia, postpartum contraception remains underutilized. Few women receive contraceptive counseling despite the country having the highest rates of unintended pregnancies in Sub-Saharan Africa. This study characterizes the prevalence of contraceptive counseling at Mizan- Tepi University Teaching Hospital (MTUTH) and examines differences in maternal demographic, antepartum, and postpartum characteristics between women who did and did not receive contraceptive counseling.

Methods: A prospective cross-sectional study was conducted in 2019 with a convenience sample of 1000 women delivering at 28 weeks or more from MTUTH. Data were collected through chart reviews and patient interviews upon admission, delivery, and discharge. Purposeful modeling was used to identify significant predictors of contraceptive counseling.

Results: The prevalence of contraceptive counseling was 4.55%. Among those with contraceptive counseling data recorded, receipt of counseling was associated with parity and delivery provider (p < 0.05). Odds of receiving contraceptive counseling among women with no previous births (parity=0) were 0.83 times less likely than women who had given birth at least three times (parity=3+) (OR: 0.17; 95% CI: 0.05-0.57). Odds of receiving contraceptive counseling among women who had an integrated emergency and surgical officer (IESO) or medical doctor (MD) as their delivery provider were 0.67 times less likely than women who had a midwife (OR: 0.33; 95% CI: 0.11-0.97). Health Equity: Inequities were identified to increase contraceptive counseling access for women served by MTUTH.

Conclusion: Most women at MTUTH do not receive contraceptive counseling. This quality improvement project allows hospital leadership to develop targeted interventions to improve rates of contraceptive counseling and contributes to the literature surrounding the characterization of contraceptive counseling and uptake in Ethiopia.

Keywords

MTUTH, (SNNPR), AIC, COMIRB, CCU, IESO

Hospital articles, Southwest Ethiopia articles

Article Details

1. Background

Underutilization of family planning services remains a worldwide public health issue, especially in developing nations. Looking at contraceptive use more specifically, studies have shown that it is practiced by most in-union women in nearly all regions of the world, however prevalence of contraceptive use is lowest in the least developed countries [1]. More than two-thirds of women in developing countries who do not want to conceive are not using contraception, and African countries represent the world region with the lowest prevalence of contraceptive use at 33% in 2015 [1,2]. In Ethiopia, the 2020 prevalence of modern contraceptive utilization was 58.5% among all women [3]. For married women, contraceptive utilization was 36.5% among women aged 15-19 and 46.4% among those 25-34 years old [4]. This number remains below the national target of 55% for married women [5]. Furthermore, Ethiopia has one of the highest rates of unintended pregnancies in sub-Saharan Africa with nearly every women experiencing at least one unintended birth [6]. Despite these statistics, contraception in postpartum remains underutilized in Ethiopia [7]. Previous studies have identified key determinants of contraceptive utilization in Ethiopia including: antenatal and postnatal care visits, maternal education, number of live children, women’s occupation, spousal support, age, wealth status, and history of family planning use and counselling [2,8,9]. This study will be examining these and other determinants of contraceptive counseling more closely as contributors to contraception adoption. Quality family planning counseling in the postpartum period is vital in contraception adoption and retention, as well as reducing maternal and infant morbidity and mortality [10]. In Sub-Saharan African countries, counseling and contraceptive provision lag behind other developing countries [11]. This is reflected in Ethiopia, as few women/couples receive contraceptive counselling [12]. A 2016 study, using the Ethiopian Demographic and Health Survey, showed that only 36.2% of women were informed on contraceptive methods [13]. In country disparities in counseling and adoption are furthered by regional, educational, socioeconomic, and religious factors, along with partner approval and support [6,12]. Specifically, women affiliated with non-orthodox religions (i.e. Muslim, Protestant, or others), having only a primary education, a husband employed in agriculture, being unskilled or with an unknown job, living in Amhara or Oromia regions, and receiving services from private clinics and pharmacies were associated with lower odds of having received contraceptive counselling [13]. With the existing variations in contraceptive counseling and uptake in Ethiopia, it is necessary to address the issue within the contexts of individual communities. This study will focus on maternal discharge patients at Mizan-Tepi University Teaching Hospital (MTUTH) located in Teppi, a city of the Sheka zone of the Southern Nations, Nationalities and Peoples’ Region (SNNPR) of Ethiopia. Despite being one of the regions and zones with a relatively high prevalence of contraceptive utilization (2016 regional prevalence: 40%; 2016 zonal prevalence: 39.5%), the level of family planning counseling is inadequate in major Ethiopian hospitals, and the need for training and consideration of maternal background remains [3,10,14]. In recognition of these trends, quality improvement projects serve to identify gaps in care within Ethiopian healthcare facilities to allow for the development of interventions that will improve contraceptive counseling practices and ultimately contraceptive use. A thorough characterization of the prevalence of contraceptive counseling practices for this hospital and region has yet to be conducted. An analysis of various demographic, intrapartum, and postpartum characteristics was performed to determine differences between groups of women who did and did not receive contraceptive counseling along with those who had missing data for contraceptive counseling upon discharge. Identification of significant predictors will allow MTUTH leadership to better understand how to improve contraceptive counseling and adoption within the hospital. Furthermore, these findings contribute to the body of knowledge surrounding contraceptive counseling in Ethiopia and support efforts to increase contraception use within the communities served by the hospital.

2. Methods

A hospital-based cross-sectional study was conducted between May 6th and October 21st, 2019, with a convenience sample of all women (n=1000) delivering at 28 weeks or more from MTUTH in Ethiopia. Physicians collected deidentified data from chart reviews and structured patient interviews on paper forms, which were reviewed prior to data entry into REDCap, upon admission, delivery, and discharge. This data set was made available by the Department of Obstetrics and Gynecology with the Center for Global Health. Live maternal discharges, including those who experienced stillborn and early infant death outcomes, were included to comprehensively review factors (i.e. birth experience and other medical complications) affecting contraceptive counseling. No subjects were excluded for this analysis as no maternal deaths were recorded. Using SAS Studio On Demand for Academics version 9.04.01, a number of covariates were considered as predictors of contraceptive counseling. Initial steps focused on determining the prevalence of contraceptive counseling at MTUTH. Bivariate comparisons of prevalence rates among selected covariates between subjects with missing and non-missing contraceptive counseling data and between subjects who did and did not receive contraceptive counseling were then carried out for the secondary and tertiary aims of the study. Due to the substantial proportion of missing data present for this population, analyses were conducted to examine whether patterns of missingness were random. Chi-square tests were performed for categorical covariates, while Fisher’s t-tests were used to determine significance (p<0.05) among numeric covariates. Due to the relatively small sample size, predictive modeling was avoided, and purposeful modeling was implemented to develop a multivariable logistic regression that included covariates that best predicted whether a woman did or did not receive contraceptive counseling for the final aim. Covariate model inclusion and screening was informed by current literature and by covariate significance (p < 0.20) from initial analyses. The most significant covariate was first entered, and model fit was evaluated using Akaike information criterion (AIC). Each predictor was individually added by decreasing significance, including the last model’s terms, until the main effects model was completed. Due to the frequency distribution among contraceptive counseling status groups (received: 35, did not receive: 732, no data recorded: 231), the final model was limited to three/four covariates. This quality improvement survey was given an exempt from human subjects’ research approval (COMIRB # 18-2738). Oral consent was obtained from each woman before any of their data was recorded. Grant writing and resource evaluation was not necessary for this project.

3. Results

The following tables display outcomes from descriptive statistics performed for all covariates considered for this study. Variables were transformed to better understand the grouped effects of each exposure on the primary outcome—contraceptive counseling. Obstetric high risk was classified as yes if pregnancy included any of the following: premature rupture of membrane, antepartum hemorrhage, uterine rupture, chorioamnionitis, preeclampsia/eclampsia/chronic HTN, diabetes (pregestational/gestational), anemia, or HIV. Antepartum interventions included any of the following: antepartum blood transfusion, antepartum therapeutic antibiotics, antepartum antihypertensive, antepartum magnesium sulfate, or antepartum steroids. Postpartum complications included hemorrhage, wound dehiscence, wound infection, urinary tract infection, pneumonia, endometritis, admission to CCU, referral to ICU, antibiotics given, blood transfusion, intravenous fluid, pain medication administered, antihypertensive administered, anticonvulsant administered, uterotonics, or D&C reoperation. Finally, neonatal complications was created to include infant resuscitated with bag & mask, referred to MTUTH NICU, intranasal oxygen, CPAP, fluid administration, blood transfusion, or antibiotic administration. Table-1 and -2 show means, standard deviations, and Satterthwaite p-values from Fisher’s t-tests for numeric covariates while frequencies, percentages, and p-values are displayed from Chi-square tests performed for categorical covariates. Table-1 displays comparisons between populations of women who did and did not have contraceptive counseling data recorded. As shown, nearly a quarter (23.1%) of the 1,000 women on whom data was collected did not have information regarding contraceptive counseling recorded. Marital status, postpartum complications, parity, and maternal age were significantly associated with whether a woman had contraceptive data recorded. Women were more likely to have contraceptive counseling data recorded if they were married/cohabitating or experienced postpartum complications and this likelihood increased with parity (the number of times a woman had given birth to a fetus with a gestational age of 24 weeks or more) and maternal age, p < 0.05. Overall, the majority of women with missing contraceptive counseling data had completed up to primary school (45.02%), resided in a rural setting (57.14%), were Protestant (55.41%), married/cohabitating (99.13%), did not smoke or drink alcohol during pregnancy (99.13%; 98.70%), did not have a high risk pregnancy (86.15%), had an unassisted vaginal delivery (67.53%), were assisted by a midwife (73.16%), did not experience antepartum interventions, postpartum complications, or neonatal complications (96.97%; 90.48%; 96.10%), gave birth to a live fetus that sustained through discharge (89.61%), had experienced no prior deliveries (58.44%), carried to term (91.34%), completed at least 4 antenatal visits (60.61%), and delivered to a single fetus (92.21%). These trends were consistent among the entire sample population and between counseling status groups for both Table-1 and Table-2.

Maternal Characteristics

Total Cohort

Missing Contraceptive Counseling Data

Contraceptive Counseling Data Present

p-value

N=1000

N = 231 (23.10%)

N = 769 (76.90%)

n (column %)

n (column %)

n (column %)

Educational Status

0.2

Unable to read and write

233 (23.30%)

47 (20.35%)

186 (24.19%)

Read and write only

54 (5.40%)

8 (3.46%)

46 (5.98%)

Primary school

399 (39.90%)

104 (45.02%)

295 (38.36%)

Secondary school

140 (14.00%)

35 (15.15%)

105 (13.65%)

Higher education

173 (17.30%)

36 (15.58%)

137 (17.82%)

Unknowna

1 (0.10%)

1 (0.43%)

0 (0.00%)

Residence

0.38

Urban

454 (45.40%)

99 (42.86%)

355 (46.16%)

Rural

546 (54.60%)

132 (57.14%)

414 (53.84%

Religion

0.35

Muslim

111 (11.10%)

19 (8.23%)

92 (11.96%)

Orthodox Christian

336 (33.60%)

81 (35.06%)

255 (33.16%)

Protestant

549 (54.90%)

128 (55.41%)

421 (54.75%)

Jehovah Witness

2 (0.20%)

1 (0.43%)

1 (0.13%)

Unknown

2 (0.20%)

2 (0.87%)

0 (0.00%)

Marital Status

0.03*

single/widowed/separated

27 (2.70%)

11 (4.76%)

16 (2.08%)

not single (married/cohabitating)

964 (96.40%)

216 (93.51%)

748 (97.27%)

Unknown

9 (0.90%)

4 (1.73%)

5 (0.65%)

Smoke

0.58

Yes

1 (0.10%)

0 (0.00%)

1 (0.13%)

No

994 (99.40%)

229 (99.13%)

765 (99.48%)

Unknown

5 (0.50%)

2 (0.87%)

3 (0.39%)

Alcohol

0.66

Yes

5 (0.50%)

1 (0.43%)

4 (0.52%)

No

990 (99.00%)

228 (98.70%)

762 (99.09%)

Unknown

5 (0.50%)

2 (0.87%)

3 (0.39%)

Transferred during laborb

0.29

Yes

492 (49.20%)

120 (51.95%)

372 (48.37%)

No

506 (50.60%)

109 (47.19%)

397 (51.63%)

Unknown

2 (0.20%)

2 (0.87%)

0 (0.00%)

Obstetric High Risk

0.31

Yes

160 (16.00%)

32 (13.85%)

128 (16.64%)

No

840 (84.00%)

199 (86.15%)

641 (83.36%)

Method of Delivery

0.21

Unassisted vaginal delivery/spontaneous

716 (71.60%)

156 (67.53%)

560 (72.82%)

Assisted vaginal/instrumental delivery by forceps

14 (1.40%)

4 (1.73%)

10 (1.30%)

Assisted vaginal/instrumental delivery by vacuum

29 (2.90%)

11 (4.76%)

18 (2.34%)

Cesarean delivery

234 (23.40%)

55 (23.81%)

179 (23.28%)

Unknown

7 (0.70%)

5 (2.16%)

2 (0.26%)

Delivery Provider

0.73

Midwife

732 (73.20%)

169 (73.16%)

563 (73.21%)

Integrated emergency and surgical officer (IESO)/MDc

263 (26.30%)

58 (25.11%)

205 (26.66%)

Unknown

5 (0.50%)

4 (1.73%)

1 (0.13%)

Antepartum Interventions

0.12

Yes

50 (5.00%)

7 (3.03%)

43 (5.59%)

No

950 (95.00%)

224 (96.97%)

726 (94.41%)

Postpartum Complications

<0.0001*

Yes

182 (18.20%)

22 (9.52%)

160 (20.81%)

No

818 (81.80%)

209 (90.48%)

609 (79.19%)

Neonatal Complications

0.51

Yes

47 (4.70%)

9 (3.90%)

38 (4.94%)

No

953 (95.30%)

222 (96.10%)

731 (95.06%)

Neonatal Sex

0.48

Male

531 (53.10%)

118 (51.08%)

413 (53.71%)

Female

469 (46.90%)

113 (48.92%)

356 (46.29%)

Neonatal Status on Day of Discharge

0.05

Alive

935 (93.50%)

207 (89.61%)

728 (94.67%)

Dead

57 (5.70%)

19 (8.23%)

38 (4.94%)

Unknown

8 (0.80%)

5 (2.16%)

3 (0.39%)

Fetal Status at Delivery

0.25

Alive

904 (90.40%)

200 (86.58%)

704 (91.55%)

Dead

44 (4.40%)

13 (5.63%)

31 (4.03%)

Unknown

52 (5.20%)

18 (7.79%)

34 (4.42%)

Parity

<0.0001*

0

428 (42.80%)

135 (58.44%)

293 (38.10%)

1

263 (26.30%)

38 (16.45%)

225 (29.26%)

2

144 (14.40%)

29 (12.55%)

115 (14.95%)

3+

165 (16.50%)

29 (12.55%)

136 (17.69%)

Gestational Aged

0.23

Term

892 (89.20%)

211 (91.34%)

681 (88.56%)

Preterm

108 (10.80%)

20 (8.66%)

88 (11.44%)

History of Cesarean Birth

0.72

0

510 (51.00%)

82 (35.50%)

428 (55.66%)

1

44 (4.40%)

7 (3.03%)

37 (4.81%)

2+

7 (0.70%)

2 (0.86%)

5 (0.65%)

Unknown

439 (43.90%)

140 (60.61%)

299 (38.88%)

Number of Antenatal Visits

0.09

0

20 (2.00%)

8 (3.46%)

12 (1.56%)

<4

300 (30.00%)

63 (27.27%)

237 (30.82%)

4+

680 (68.00%)

160 (69.26%)

520 (67.62%)

Number of Fetuses Delivered

0.19

Single

948 (94.80%)

213 (92.21%)

735 (95.58%)

Multiple

49 (4.90%)

15 (6.49%)

34 (4.42%)

Unknown

3 (0.30%)

3 (1.30%)

0 (0.00%)

mean (sd)

mean (sd)

mean (sd)

Maternal Age (years)

24.63 (4.70)

24.05 (4.62)

24.80 (4.70)

0.03*

Number of Days Hospitalized, Mother

1.86 (1.90)

1.83 (1.55)

1.87 (2.00)

0.8

*significant at p<0.05
aunknown values not considered in p-value calculations
btransferred during labor to Mizan Tepi University Teaching Hospital from another clinical setting for higher level of care
cincludes general practitioners, Ob/Gyn residents, and Ob/Gyn attendings
dterm births characterized as those delivered at 37 weeks or more; preterm less than 37 weeks

Table 1: Comparisons of maternal characteristics of women overall and by whether data was or was not recorded for contraceptive counseling.

After removing those with missing contraceptive counseling data (n=231), the overall prevalence of contraceptive counseling at MTUTH was found to be 4.55%. Table-2 shows results from comparisons between women who did and did not receive contraceptive counseling. Delivery provider and parity were significantly associated with reception of contraceptive counseling, p < 0.05. Women who received contraceptive counseling were more likely to have been assisted by a midwife and to have had a parity of 2 or more.

Maternal Characteristics

Total Cohort

Received Counseling

Did Not Receive Counseling

p-value

N=769

N=35 (4.55%)

N=734 (95.45%)

n (column%)

n (column %)

n (column %)

Educational Status

0.52

Unable to read and write

186 (24.19%)

11 (31.43%)

175 (23.84%)

Read and write only

46 (5.98%)

0 (0.00%)

46 (6.27%)

Primary school

295 (38.36%)

12 (34.29%)

283 (38.56%)

Secondary school

105 (13.65%)

5 (14.29%)

100 (13.62%)

Higher education

137 (17.82%)

7 (20.00%)

130 (17.71%)

Residence

0.52

Urban

355 (46.16%)

18 (51.43%)

337 (45.91%)

Rural

414 (53.84%)

17 (48.57%)

397 (54.09%)

Religion

0.81

Muslim

92 (11.96%)

6 (17.14%)

86 (11.72%)

Orthodox Christian

255 (33.16%)

11 (31.43%)

244 (33.24%)

Protestant

421 (54.75%)

18 (51.43%)

403 (54.90%)

Jehovah Witness

1 (0.13%)

0 (0.00%)

1 (0.14%)

Marital Status

0.38

single/widowed/separated

16 (2.08%)

0 (0.00%)

16 (2.18%)

not single (married/cohabitating)

748 (97.27%)

34 (97.14%)

714 (97.28%)

Unknowna

5 (0.65%)

1 (2.86%)

4 (0.54%)

Smoke

0.91

Yes

1 (0.13%)

0 (0.00%)

1 (0.14%)

No

765 (99.48%)

35 (100.00%)

730 (99.46%)

Unknown

3 (0.39%)

0 (0.00%)

3 (0.41%)

Alcohol

0.85

Yes

4 (0.52%)

0 (0.00%)

4 (0.54%)

No

762 (99.09%)

35 (100.00%)

727 (99.05%)

Unknown

3 (0.39%)

0 (0.00%)

3 (0.41%)

Transferred during laborb

0.98

Yes

372 (48.37%)

17 (48.57%)

355 (48.37%)

No

397 (51.63%)

18 (51.43%)

379 (51.63%)

Obstetric High Risk

0.59

Yes

128 (16.64%)

7 (20.00%)

121 (16.49%)

No

641 (83.36%)

28 (80.00%)

613 (83.51%)

Method of Delivery

0.19

Unassisted vaginal delivery/spontaneous

560 (72.82%)

31 (88.57%)

529 (72.07%)

Assisted vaginal/instrumental delivery by forceps

10 (1.30%)

0 (0.00%)

10 (1.36%)

Assisted vaginal/instrumental delivery by vacuum

18 (2.34%)

0 (0.00%)

18 (2.45%)

Cesarean delivery

179 (23.28%)

4 (11.43%)

175 (23.84%)

Unknown

2 (0.26%)

0 (0.00%)

2 (0.27%)

Delivery Provider

0.047*

Midwife

563 (73.31%)

31 (88.57%)

532 (72.58%)

Integrated emergency and surgical officer (IESO)/MDc

205 (26.69%)

4 (11.43%)

201 (27.42%)

Antepartum Interventions

0.97

Yes

43 (5.59%)

2 (5.71%)

41 (5.59%)

No

726 (94.41%)

33 (94.29%)

693 (94.41%)

Postpartum Complications

0.16

Yes

160 (20.81%)

4 (11.43%)

156 (21.25%)

No

609 (79.19%)

31 (88.57%)

578 (78.75%)

Neonatal Complications

0.56

Yes

38 (4.94%)

1 (2.86%)

37 (5.04%)

No

731 (95.06%)

34 (97.14%)

697 (94.96%)

Neonatal Sex

0.53

Male

413 (53.71%)

17 (48.57%)

396 (53.95%)

Female

356 (46.29%)

18 (51.43%)

338 (46.05%

Neonatal Status on Day of Discharge

0.31

Alive

728 (94.67%)

32 (91.43%)

696 (94.82%)

Dead

38 (4.94%)

3 (8.57%)

35 (4.77%)

Unknown

3 (0.39%)

0 (0.00%)

3 (0.41%)

Fetal Status at Delivery

0.19

Alive

704 (91.55%)

32 (91.43%)

672 (91.55%)

Dead

31 (4.03%)

3 (8.57%)

28 (3.81%)

Unknown

34 (4.42%)

0 (0.00%)

34 (4.63%)

Parity

0.01*

0

293 (38.10%)

4 (11.43%)

289 (39.37%)

1

225 (29.26%)

13 (37.14%)

212 (28.88%)

2

115 (14.95%)

8 (22.86%)

107 (14.58%)

3+

136 (17.69%)

10 (28.57%)

126 (17.17%)

Gestational Aged

0.99

Term

681 (88.56%)

31 (88.57%)

650 (88.56%)

Preterm

88 (11.44%)

4 (11.43%)

84 (11.44%)

History of Cesarean Birth

0.85

0

428 (55.66%)

30 (85.71%)

398 (54.22%)

1

37 (4.81%)

1 (2.86%)

36 (4.90%)

2+

4 (0.52%)

0 (0.00%)

4 (0.54%)

Unknown

299 (38.88%)

4 (11.43%)

295 (40.19%)

Number of Antenatal Visits

0.43

0

12 (1.56%)

1 (2.86%)

11 (1.50%)

<4

237 (30.82%)

14 (0.40%)

223 (30.38%)

4+

520 (67.62%)

20 (57.14%)

500 (68.12%)

Number of Fetuses Delivered

0.19

Single

735 (95.58%)

35 (100.00%)

700 (95.37%)

Multiple

34 (4.42%)

0 (0.00%)

34 (4.63%)

mean (sd)

mean (sd)

mean (sd)

Maternal Age (years)

24.63 (4.70)

25.66 (4.45)

24.76 (4.71)

0.25

Number of Days Hospitalized, Mother

1.86 (1.90)

2.80 (5.72)

1.82 (1.62)

0.32

*significant at p<0.05
aunknown values not considered in p-value calculations
btransferred during labor to Mizan Tepi University Teaching Hospital from another clinical setting for higher level of care
cincludes general practitioners, Ob/Gyn residents, and Ob/Gyn attendings
dterm births characterized as those delivered at 37 weeks or more; preterm less than 37 weeks

Table 2: Comparison of maternal characteristics of women overall and by whether contraceptive counseling was or was not received.

We used AIC model selection to distinguish among a set of possible models to describe the relationship between various antepartum, intrapartum, and postpartum maternal characteristics and contraceptive counseling. Using statistical significance (p < 0.20) to inform model building, candidate models were compared with the following eligible covariates: method of delivery, parity, delivery provider, postpartum complications, fetal status at delivery, and the number of fetuses delivered. The best-fit model, with the lowest AIC value (273.88), included parity, delivery provider, and fetal status at delivery. It should be noted that there were zero counts for the outcome for multiple fetuses delivered, and this resulted in confidence intervals that were uninterpretable. Therefore, this variable was not included in the final model. Table-3 shows results of multivariable modeling. Odds of receiving contraceptive counseling among women with no previous births (parity=0) were 0.83 times less likely than women who had given birth at least three times previously (parity=3+)(OR: 0.17; 95% CI: 0.05-0.57). Odds of receiving contraceptive counseling among women who had an integrated emergency and surgical officer (IESO) or medical doctor (MD) as a delivery provider were 0.67 time less likely than women whose delivery provider was a midwife (OR: 0.33; 95% CI: 0.11-0.97).

Characteristic

Odds Ratio

95% Confidence Interval

Parity

0 vs 3

0.17

0.05, 0.57*

1 vs 3

0.76

0.32, 1.81

2 vs 3

0.89

0.33, 2.35

Delivery Provider

MD/IESO vs Midwife

0.33

0.11, 0.97*

Fetal Status at Delivery

Alive vs Dead

0.38

0.10, 1.39

*significant at p < 0.05; null excluded within 95% CI

Table 3: Multivariable model of characteristics associated with contraceptive counseling (N=1000).

4. Discussion

Most women at MTUTH do not receive contraceptive counseling. While this finding is concurrent with trends of underutilization of family planning services in major Ethiopian hospitals, a prevalence of less than five percent suggests room for overall improvement, enforcement, and prioritization of contraceptive counseling within the organization. Analysis of missing contraceptive counseling data revealed potential areas of focus for the hospital. Whether or not a woman had data recorded significantly differed by marital status, postpartum complications, parity, and maternal age. While it is unclear why a woman may have been exempted from the collection of this measure (i.e. different discharge procedures, elected not to respond, etc.), these factors present opportunities for investigation as to the cause of these differences. It should also be noted that though maternal age was statistically significant, the clinical significance of this finding is less valid (24.05 years vs 24.80 years). Examination of predictors of contraceptive counseling among those women who did have data recorded revealed that women whose delivery providers were midwives, were more likely to receive counseling. Not only was parity associated with increased likelihood of having contraceptive counseling data recorded, but it also increased the odds of receiving contraceptive counseling as the parity level increased. This finding was consistent with the literature and indicates that parity may influence provider motivation to provide counseling. Additionally, studies suggest that reported desire to limit births rises dramatically at parities two and three among women [15]. As mentioned, the frequency breakdown between counseling groups limited the potential for covariate inclusion in this study. Another limitation of this analysis was that we could only consider the variables in our dataset, and this survey was designed to assess many other pregnancy outcomes outside of family planning. Therefore, no data was collected surrounding previous contraception practices or knowledge among the women in addition to what type of contraception the women started, if they did. Some women may have received contraceptive counseling in hospital and a subsequent tubal ligation during the delivery. These women would not have likely received contraceptive counseling upon discharge, and these nuances are not documented in the data set. Future analyses should control for sterilization procedures, if possible, and collect more information regarding existing contraception knowledge and practices among women to better address any information biases. Due to the method of recruitment, sampling bias likely compromised the generalizability of this study to the larger Ethiopian population. However, for the purposes of this study as a hospital-specific quality improvement project, this bias was not important to control for. Lastly, we were also limited in our understanding and insight into the specific discharge procedures at Mizan-Tepi University Teaching Hospital and the quality of contraceptive counseling that clients receive. Therefore, quality assumptions or proposals for hospital-specific intervention development were limited. Despite these drawbacks, this study adds to the body of literature outlining the disparities in contraceptive counseling and proposes potential contributors to low rates of contraception use despite high rates of unplanned pregnancies in Ethiopia. Quality family planning services, which include contraceptive services, pregnancy testing and counseling, helping clients who want to conceive, and providing infertility, preconception, and sexually transmitted disease services, have been proven to increase knowledge and awareness among clients and providers, decrease bias, and reduce maternal and infant morbidity and mortality [16]. This project focuses on MTUTH and the communities of women that it serves. While the goal is to improve contraceptive counseling overall, identifying overlooked populations of women allows hospital leadership to develop targeted discharge procedures to increase contraception education, awareness, and access. Findings such as these can be used to address the larger issues of underutilization of family planning services by proposing opportunities for intervention development and improving maternal and infant health in Ethiopia.

5. Conclusion

Contraceptive counseling is a service that remains vastly underutilized in Ethiopia. Room for overall improvement is evident as reflected by the prevalence of less than five percent of women receiving counseling at MTUTH. Improving the provision rate and quality of family planning services for all women across all demographics is necessary to support thoughtful and well-informed decisions surrounding contraception. Health care facilities should train providers and integrate conversations surrounding contraception into workflows and discharge procedures, paying special attention to disparities in contraception counseling provision. Future studies should look to characterize the quality of contraceptive counseling in Ethiopia more broadly and suggest specific avenues for intervention development.

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