Prevalence and Predictors of Stillbirths Following Vaginal Delivery at Tumu Municipality of the Upper West Region, Ghana: a cross-sectional study

doi:10.21203/rs.3.rs-4208440/v1

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Prevalence and Predictors of Stillbirths Following Vaginal Delivery at Tumu Municipality of the Upper West Region, Ghana: a cross-sectional study

https://doi.org/10.21203/rs.3.rs-4208440/v1

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Background

Low- and middle-income countries still have unacceptably high rates that makes it imperative to identify the factors that predict stillbirth so as to effectively develop interventions. This study aimed to identify the prevalence and predictors of stillbirth among mothers who gave birth in the Tumu municipality in the Upper West Region of Ghana.

Methods

Using a retrospective cross-sectional study design, 1,240 women who had vaginal deliveries had their medical records examined. From January 1 to December 31, 2019, information on vaginal deliveries was gathered from the hospital's records. The data were summarised using descriptive statistics, and the relationship between maternal and obstetric characteristics and foetal outcomes was investigated using Pearson's chi-square/Fisher's exact test. To evaluate predictors, logistic regression was fitted at a 95% confidence interval (95% CI), and the results were reported using odds ratio.

Results

Among the 1204 women, 626 (52%) of them were aged 20–29 years; 832 (70%) of mothers were multigravida and 878 (73.50%) attended ANC between 4 to 8 times. There were 1187 (98.6%) live births and the overall prevalence of foetal mortality was 14.12 per 1000 total births. Women who attended ANC between 4–8 times were 91% less likely to record a foetal mortality (AOR 0.090 (0.024–0.342) p-value = < 0.001). Women whose labour was not monitored using a partograph were more than 17 times likely to record a foetal mortality (AOR 17.156, 95% CL: 4.981–59.090, p-value = < 0.001).

Conclusion

The neonatal mortality rate is 14.12 per 1000 live births, with better outcomes for pregnant women who attend ANC 4–8 times. The likelihood of foetal deaths in labors without partograph monitoring is 17 times higher. Refresher training on patographs and early hospital arrival are recommended.

Prevalence

predictors

stillbirths

vaginal delivery

Ghana

Globally, stillbirth is a concern for public health, particularly in Sub-Saharan Africa (SSA) (1). The World Health Organisation defined stillbirth as foetal death in the third trimester (greater than or equal to 28 completed weeks of development) with birth weight greater than or equal to 1000 g or length greater than or equal to 35 cm. It also means that the child dies before the complete expulsion or extraction from its mother (2). While institutional deliveries are on the rise, stillbirth rates in developing nations have not significantly declined (3).

Every year, there is an estimated 2.6 million stillbirths worldwide, with data available showing that low and lower middle-income countries account for 84% of all stillbirths (4). Despite this, there is a lot of proof that not all foetal deaths that call for reporting are actually registered. In developing nations like Ghana, where stillbirths are not counted in routine mortality data gathering, the situation is worse (5, 6).

Various studies have suggested diverse factors including maternal age, occupation and parity to be associated with stillbirth in different settings (6, 7). According to the 2017 Ghana Maternal Health Survey, 20 stillbirths per 1000 live births, or 2% of pregnancies, resulted in stillbirth nationwide (8). Earlier research, have identified a number of significant predictors of stillbirth, that may be maternal or foetal (1, 9).

The rate of stillbirth is a sensitive indicator of the health-care system and a significant predictor of the standard of care received during pregnancy and childbirth. Initiatives launched after 2015 demonstrate that stillbirths remain a sustainable development goal and are part of a global hidden agenda. At the 2014 World Health Assembly, Ghana was one of 194 countries that supported the Every Newborn Action Plan's goal of ending avoidable stillbirths. The plan's objective was to lower the country's rate of stillbirth to 12 or less per 1000 live births by 2030 (10).

Although there are various strategies and plans to improve the wellbeing of mothers and children, the level of stillbirth is a major public health problem in areas such as Tumu (8). Consequently, the stillbirth rate has been 20 stillbirths per 1000 live births (8). Finding stillbirth predictors would, in one way or another, help achieve the global goal of reducing stillbirths. Therefore, this study aimed to assess the adverse pregnancy outcomes and to determine predictors of stillbirth in the Tumu municipality, Upper West Region, Ghana.

Study design and setting

A retrospective descriptive study design was used, in which we reviewed the records of pregnant women who were delivered at the Tumu Municipal Hospital. There was a total of 1,202 delivery records that were collected and kept in the Records Department of the hospital.

The Tumu Municipal Hospital is located in the town of Tumu, the capital of the Sissala East Municipality in the Upper West Region of Ghana. The municipality covers an area of approximately 4600km².

About 58% of the population are illiterate and the rates are higher among females (11). The hospital serves the population of about 67,029 inhabitants and it is the only government hospital and the highest referral point within the district. All emergency cases from all sub-district facilities are directed to it as their initial point of contact. Because there are not enough qualified midwives in the area, community health nurses support the work of the midwives.

Definition and measurement of variables

Dependent variable

The main outcome measure was birth outcome, and as the dependent variable was categorised into Live birth and Stillbirth. Live birth was defined as the delivery of a newborn alive, and Stillbirth was defined as where there was the delivery of a dead foetus.

Independent variables

The explanatory variables selected for the study were: parity, defined as the number of times a person has given birth before the present delivery; while gravidity was the number of pregnancies a participant has had previous to the current pregnancy. The gestational age was the number of weeks a person was pregnant before giving birth. Baby weight referred to the initial weight recorded at birth, while time of arrival referred to the time patients arrived at the facility and time of delivery referred to the time mother gave birth. Mother's haemoglobin (HB) level was the HB level of the mother as recorded in the antenatal clinic (ANC) book prior to labour and delivery. Additionally, ANC visits was defined as the frequency with which a mother visited the antenatal clinic before giving birth. Intermittent Preventive Treatment (IPT) was the routine use of combined sulphadoxine-pyrimethamine for the treatment for malaria during pregnancy.

Data Collection

From 1st January 2019 to 31st December 2019, the medical records of every delivery case recorded in the hospital's register were reviewed. The hospital's registration was reviewed for adverse pregnancy outcome; stillbirth. Maternal age, gravida, parity, education, haemoglobin level, employment status, arrival time, and delivery time were extracted for each patient. The record also yielded information on the mother's blood type, partograph readings, and birth outcome (dead or alive). A check was used to ensure good quality of the data extracted.

Statistical Analysis

Data was analysed using STATA statistical software, version 16.0. Categorical variables were summarised using frequencies and percentages and continuous variables summarised with means (with standard deviations) or medians (with limits) where appropriate. The dependent variable and key explanatory variables were subjected to a chi-square test for associations and Fisher exact test at a cut-off value of 0.05, and variables that failed to reach significance were excluded from the multivariate analysis. Two logistic regression models were fitted between the outcome variable and significant explanatory variables at a 95% confidence interval (95% CI). The first model (Model I) investigated a bivariate association, whereas Model II adopted a multivariate strategy. For Model I and Model II, the results were presented as crude odds ratios (COR) and adjusted odds ratios (AOR), respectively. Odds below 1 were evaluated as having a lower chance of perinatal mortality, while odd numbers above 1 were regarded as having a higher likelihood of perinatal mortality. The Variance Inflation Factor (VIF) was used to run a multi-collinearity test on the significant explanatory variables.

A total of 1,204 participants met the eligibility criteria and hence were included in this study. Nearly all mothers, 1187 (98.59%) gave birth to live babies and the majority of mothers, 626 (51.99%) were within the age group of 20–29 years with the mean (SD) age of 27.59 (6.86) years, with only a little over a tenth, 134 (11.13%) being teenagers. More than a quarter, 394 (33.22%) had no form of formal education while 207 (17.19) had tertiary education. The majority, 395 (33.55%) were peasant farmers with nearly three-fourths, 832 (70.18%) being multigravida. Over a quarter, 431 (36.30%) were multiparous while nearly three-fourths, 878 (73.50%) had ANC attendance between 4 to 8 times during the current pregnancy. Preterm deliveries constituted 20% with only about 36 (2.99%) twin gestations. Over three quarters, 979 (81%) of labour were monitored using a partograph with the majority, 1176 (97.7%) of mothers presenting with an initial temperature of 37.4 degrees Celsius and below. The majority, 979 (81.3%) of babies born weighed between 2.5–3.5 kg, and females constituted the majority (52.4%) of children born.

In the chi-square or Fisher exact test, Antenatal care visits and partograph use during labour were significant predictors of foetal mortality among study participants (Table 1).

Table 1

socio-demographics, maternal and foetal characteristics.
Variable	Birth outcome		Total	X²/F	p-value
Variable	Live birth (%)	Stillbirth (%)	Total	X²/F	p-value
Mothers Age				***	0.407
14–19	134 (11.13)	1 (0.08)	135 (11.21)
20–29	626 (51.99)	7 (0.58)	633 (52.57)
30–55	427 (35.47)	9 (0.75)	427 (36.21)
Mean (SD)	27.59 (6.86)
Educational level				***	0.905
No formal education	394 (32.72)	6 (0.50)	400 (33.22)
Primary school	123 (123)	2 (0.17)	125 (10.38)
Junior high school	249 (20.68)	3 (0.25)	252 (20.93)
Senior high school	218 (218)	2 (0.17)	220 (18.27)
Tertiary	203 (16.86)	4 (0.33)	207 (17.19)
Occupation				***	0.345
Farmer	395 (32.81)	9 (0.75)	404 (33.55)
Hairdresser /seamstress	158 (13.12)	1 (0.08)	159 (13.21)
Trader	109 (9.05)	1 (0.08)	110 (9.14)
Public Servant	157 (13.04)	4 (0.33)	161 (13.37)
House Wife	225 (18.69)	1 (0.08)	226 (18.77)
Student	143 (11.88)	1 (0.08)	144 (11.96)
Gravidity				***	0.790
Primigravida	355 (29.49)	4 (0.33)	359 (29.82)
Multigravida	832 (69.10)	13 (1.08)	845 (70.18)
Parity				***	0.784
Nulliparous	365 (30.32)	4 (0.33)	369 (30.65)
Primiparous	288 (23.92)	5 (0.42)	293 (24.34)
Multiparous	431 (35.80)	6 (0.50)	437 (36.30)
Grand Multiparous	103 (8.55)	2 (0.17)	105 (8.72)
ANC visits				***	0.003
0–3	156 (12.96)	7 (0.58)	163 (13.54)
4–8	878 (72.92)	7 (0.58)	885 (73.50)
9 above	153 (12.71)	3 (0.25)	156 (12.96)
Gestational Age				2.5138	0.113
Less than 37weeks	235 (19.52)	6 (0.50)	241 (20.02)
37 weeks and above	952 (79.07)	11 (0.91)	963 (7998)
Gestational type				***	0.089
Singleton	1153 (95.76)	15 (1.25)	1168 (97.01)
Twin	34 (2.82)	2 (0.17)	36 (2.99)
Partograph use				***	< 0.001
Yes	975 (80.98)	4 (0.33)	979 (81.31)
No	212 (17.61)	13 (1.08)	225 (18.69)
Mother temperature on admission				***	1.000
Less than 37.4	1159 (96.26)	17 (1.41)	1176 (97.67)
37.4 and above	28 (2.33)	0 (0.00)	28 (2.33)
Baby weight (kg)				***	0.140
Less than 2.5	82 (6.81)	3 (0.25)	85 (7.06)
2.5–3.5	967 (80.32)	12 (1.00)	979 (81.31)
3.6 and above	138 (11.46)	2 (0.17)	140 (11.63)
Gender				0.1979	0.656
Male	564 (46.84)	9 (0.75)	573 (47.59)
Female	623 (51.74)	8 (0.66)	631 (52.41)
*** = fisher exact test

Prevalence of Stillbirth and its predictors

The overall prevalence of stillbirth was 14.12 per 1000 total births recorded for the period. Variations in the rates were observed among age subgroupings of the mothers, teenage mothers recorded the least mortality rate of 7.41 per 1000 total births compared to mothers who were 30 years and above 20.64 per 1000 total births. The rates were also varied, where mothers with tertiary level education recorded the highest prevalence of 19.32 per 1000 total births compared with mothers who had senior high school qualification of 9.09 per 1000 total births. Public servants and farmers recorded the highest mortalities of 24.85 and 22.28 per 1000 total births respectively when compared with the others service groups. Mothers who attended ANC for less than 4 times recorded the highest stillbirth rate of 42.94 per 1000 total births compared with mothers who attended ANC between 4–8 times during the current pregnancy. Partograph use and singleton gestations recorded the least stillbirth rates of 4.09 and 12.84 per 1000 total births respectively compared with women whose labour was not monitored with partograph and twin gestations (Table 2)

In the univariate logistic regression analysis, partograph use and ANC were associated with birth outcome. Women who attended ANC between 4–8 times were 82.2% less likely to record a stillbirth (COR 0.178 95% CL: 0.061–0.514, p-value = 0.001) compared with those who attended ANC less than 4 times during the current pregnancy. Women whose labour was not monitored using a partograph were about 15 times more likely to record a foetal mortality (COR 14.947, 95% CL:4.826–46.291 p-value = < 0.001) compared with those whose labour was monitored using a partograph. After adjusting for confounding, women who attended ANC between 4–8 times were 91% less likely to record a foetal mortality (AOR 0.090 (0.234–0.342) p-value = < 0.001) compared with those who attended ANC less than 4 times and Women whose labour was not monitored using a partograph were more than 17 times likely to record a foetal mortality (AOR 17.156, 95% CL: 4.981–59.090, p-value = < 0.001) compared with those whose labour was monitored using a partograph.

Table 2

Prevalence of Stillbirth and its predictors.
Variable	Stillbirth per 1000 total births	COR (CL)	p-value	AOR (CL)	p-value
Overall	14.12
Mothers Age
14–19	7.41	Reference
20–29	11.06	1.50 (0.183–12.280)	0.706	6.65 (0.426-103.806)	0.176
30–55	20.64	2.82 (0.355–22.496)	0.327	17.15 (0.745-394.447)	0.076
Educational level
No formal education	15.00	Reference
Primary school	16.00	1.07 (00.213–5.358)	0.937	1.25 (0.187–8.414)	0.816
Junior high school	11.90	0.79 (0196-3.192)	0.742	1.62 (0.276–9.503)	0.593
Senior high school	9.09	0.60 (0.121–3.010)	0.537	1.47 (0.164–13.180)	0.731
Tertiary	19.32	1.29 (0.361–4.637)	0.692	1.72 (0.059–50.356)	0.752
Occupation
Farmer	22.28	Reference
Hairdresser /seamstress	6.29	0.28 (0.035-2.10)	0.226	0.32 (0.033–3.152)	0.331
Trader	9.09	0.40 (0.050–3.212)	0.311	0.22 (0.023–2.133)	0.193
Public Servant	24..85	1.12 (0.339–3.684)	0.854	0.84 (0.032 22.302)	0.918
House Wife	4.43	0.20 (0.025–1.550)	0.122	0.18 (0 .020-1.663)	0.131
Student	6.94	0.31 (0.039–2.444)	0.265	0.22 (0.013–3.744)	0.295
Gravidity
Primigravida	11.14	Reference
Multigravida	15.39	1.39 (0.449–4.282)	0.570	0.49 (0.000-4750.904)	0.878
Parity
Nulliparous	10.84	Reference
Primiparous	17.06	1.58 (0.422–5.953)	0.496	0.78 (0.000-7670.736)	0.957
Multiparous	13.73	1.27 (0.356–4.536)	0.713	0.51 (0.000-5381.26)	0.886
Grand Multiparous	19.05	1.77 (0.320–9.810)	0.512	0.30 (0.000-3578.28)	0.799
ANC visits
0–3	42.95	Reference
4–8	7.91	0.18 (0.061–0.514)	0.001	0.09 (0.024–0.342)	< 0.001
9 above	19.23	0.44 (0.111–1.721)	0.237	0.22 (0.033–1.526)	0.126
Gestational Age
Less than 37weeks	24.90	Reference		Reference
37 weeks and above	11.42	0.45 (0.166–1.236)	0.122	0.53 (0.154–1.846)	0.321
Gestational type
Singleton	12.84	Reference		Reference
Twin	55.56	4.52 (0.995–20.556)	0.051	1.56 (0.220–11.03)	0.657
Partograph use
Yes	4.09	Reference		Reference
No	57.78	14.95(4.826–46.291)	< 0.001	17.16 (4.981–59.090)	< 0.001
Baby weight (kg)
Less than 2.5	35.29	Reference		Reference
2.5–3.5	12.26	0.34 (0.094–1.226)	0.099	0.62 (0.110–3.531)	0.593
3.6 and above	14.29	0.40 (0.065–2.420)	0.316	0.47 (0.422–5.253)	0.541
Gender
Male	15.71	Reference		Reference
Female	12.68	0.81 (0.308-2.100)	0.657	0.89 (0.295–2.705)	0.843

In underdeveloped nations, where majority of neonatal deaths are believed to occur (12), this phenomenon is still a serious issue (13) and in both developed and developing nations alike, neonatal deaths are reported more in rural than urban areas (14). Therefore, solid strategic interventions that are based on a thorough understanding of the causes and variables associated with the incidence of neonatal deaths are necessary to achieve the necessary reductions in the worldwide burden of neonatal deaths (15). There is however little evidence of this context in most rural poor communities in Ghana, hence the quest of this study to assess the prevalence and predictors of stillbirths following vaginal delivery at Tumu municipality of the Upper West Region of Ghana.

This study found the overall newborn mortality rate to be 14 per 1000 live births. This is marginally lower compared to the national rate of 17 neonatal deaths per 1000 live births (16) though there has been a decline in neonatal death rates from 21 per 1000 live births to 17 per 1000 live births from 2013 to 2022 respectively. This finding and change witnessed over this period though encouraging, is still high. This finding is nonetheless lower than that in other developing countries outside Africa. For instance, a study in India found with 62.0 per 1000 live births (17), another in Afghanistan found 37 per 1000 live births (18), and an increase from 24.8 to 38.1 per 1000 livebirths from 2017 to 2020 in Cambodia (19). In other African countries, there was a comparatively higher neonatal death rate of 20.1 per 1000 live births in Burkina Faso (20), 61.8 per 1000 livebirths in Nigeria, a country that ranks second after India in neonatal deaths (21), and 22.0 per 1000 livebirths in Tanzania (22). The low neonatal death rate seen in this study may be due to the gradual but sustained improvement in the health service delivery like the Community-based Health Planning Services (CHPS) system along with partnerships formed such as the Tumu Healthcare Initiative to improve the maternal healthcare and women’s healthcare services in the Tumu (23). The rate as found in this study is however higher than the 9.2 per 1000 livebirths found in Ethiopia. Improved housing, opting for caesarean section, and delivery at healthcare facilities were cited as being the force behind the declined neonatal death rate recorded (24).

Similar to the findings in this study which indicated that labours not monitored with the partograph had 17-fold higher odds of resulting in neonatal deaths, the use of partographs for labour monitoring has been found in earlier studies conducted in Ghana, Angola, and Burkina Faso to be a useful tool for improving pregnancy outcomes through early referrals for interventions like augmentation and emergency surgery when necessary (25). This gives credence to the fact that partograph use is the best tool for monitoring labour and indicator for timely use of the next intervention to avert a negative outcome. About 81% of labours in this study were monitored with the partograph. This might be as a result of the Upper West Regional Health Directorate's continuous training of midwives as part of its audit of obstetric and newborn referrals in the area.

With recourse to the results, pregnant women who attended ANC 4 to 8 times had better prospects with foetal outcome than their colleagues who attended less times or not at all. This is in consonance with available literature (26). ANC visit is an embodiment of the aphorism ‘Be good to your baby before it’s born’. Because the foetal organs are actively growing throughout the first 12 weeks of pregnancy and subsequently developing through the rest of the pregnancy, this care is crucial (27).

The overall rate of neonatal mortality was 14.12 per 1000 live births. The foetal outcomes of pregnant women who attended ANC 4 to 8 times were better than those of their colleagues who attended ANC less frequently or not at all. The likelihood of foetal deaths in labours without partograph monitoring was 17 times higher. It is recommended that all midwives and other auxiliary staff who support the labour force undergo refresher training on the use of patographs for monitoring labour progress. We also recommend that mothers be better educated about the importance of routinely attending ANC and arriving at the hospital early in the event of labour.

AOR, Adjusted Odds Ratio; ANC, Antenatal care; CI, Confidence Interval; X²/F, Chi-Square or Fisher’s exact test; CHPS, Community-based Health Planning Services; HB, Haemoglobin; IPT, Intermittent Preventive Treatment; OR, Odds Ratio; SSA, SD, Standard deviation; Sub-Saharan Africa; VIS, Variance Inflation Factor

Ethics approval and consent to participate

The Committee on Human Research, Publications and Ethics, School of Medicine and Dentistry, Kwame Nkrumah University of Science and Technology, waived the need for informed consent and granted ethical permission for this work. The retrospective nature of the data without identifying patient information makes consent for participation irrelevant. Informed consent was not required. Because of the following, the research complied with the informed consent waiver requirements: it posed no more than a minimal risk to the patients; it did not negatively impact the patients' rights or welfare; and it was practically impossible to conduct the research without the waiver. The reference number for this approval is CHRPE/AP/172/24. The Tumu Municipal Hospital's management was consulted for approval.

Consent for publication

Not applicable

Availability of data and materials

All data are fully available without restriction

Competing interests

The authors declare that no competing interest existed for this study

Funding

None

Author Contributions

Conception and design: MMB, PDAA, ES, RNA, AAS, ASDA & MHK

Acquisition of data: MMB, PDAA, ES & RNA

Analysis: MMB, PDAA, ES & RNA

Interpretation of data: MMB, PDAA, ES & RNA

Drafting the article: MMB, PDAA, ES, RNA, AAS, ASDA, MHK & BSM

Revising it critically for important intellectual content: MMB, PDAA, ES, RNA &BSM

Final approval of the version to be published: MMB, PDAA, ES, RNA &BSM

Acknowledgements

We sincerely thank all of the mothers whose records were examined for this project. We express our gratitude to the maternity ward and ANC unit staff for their tireless efforts in saving lives, as well as for providing the documentation that made this study possible. We express our sincere gratitude to the hospital's management and the District Director of Health Services for their endorsements and evaluations. Finally, we would like to express our gratitude to God for his protection, inspiration, and guidance during the study.

Author information

Authors and affiliations

Department of Epidemiology and Biostatistics, School of Public Health, Kwame Nkrumah University of Science and Technology, Kumasi-Ghana

Martin Muonibe Beru,Eugene Sackeya,Richard Nomo Angmortey

Tatale District Hospital, Tatale-Ghana

Eugene Sackeya

Tamale Teaching Hospital, Tamale-Ghana

Pascal Deeshini Aliu Alhassan, Martin Muonibe Beru, Richard Nomo Angmortey, Abdul-Samii Danaa Alhassan, Mohammed Hafiz Kanamu

School of Medicine, University for Development Studies

Andrews Akpah-Suka, Abdul-Samii Danaa Alhassan, Mohammed Hafiz Kanamu

School of Pharmacy and Pharmaceutical Sciences, University for Development Studies

Baba Sulemana Mohammed

Corresponding author

Correspondence to Martin Muonibe Beru

[email protected]

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No competing interests reported.

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Prevalence and Predictors of Stillbirths Following Vaginal Delivery at Tumu Municipality of the Upper West Region, Ghana: a cross-sectional study

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Abstract

Background

Methods

Results

Conclusion

Background

Methods

Study design and setting

Definition and measurement of variables

Dependent variable

Independent variables

Data Collection

Statistical Analysis

Results

Prevalence of Stillbirth and its predictors

Discussion

Conclusion

Abbreviations

Declarations

References

Additional Declarations

Status:

Version 1