Bayesian logistic regression of stillbirth cases in the Bolgatanga Municipality of Ghana, West Africa
DOI:
https://doi.org/10.18203/2320-1770.ijrcog20251954Keywords:
Posterior estimation, Bayesian approach, Stillbirth, Priors, Logistic regressionAbstract
Background: Stillbirth, as an adverse outcome of pregnancy, represents a growing worldwide public health challenge. The risks of stillbirth have been reported to exhibit considerable variation across different factors due to variability in socio-economic and geographical settings. Thus, this study was aimed at modelling the risk of stillbirth in the Bolgatanga Municipality of the Upper East region of Ghana and identifying some possible risk factors.
Methods: A retrospective cohort study design was utilized in this work. Thus, all the data were obtained from the medical recorded histories of all single birth outcomes at Bolgatanga Regional hospital in Ghana from September 2023 to December 2024. Bayesian logistic regression was applied in fitting the data on stillbirth in this study. R studio was the statistical software that was utilized in analysing the data.
Results: Based on the results of the posterior estimation of the Bayesian logistic regression, maternal age, educational level and hypertension status were established as significant risk factors of stillbirth in the Bolgatanga Municipality. Overall, women with low maternal age (<20 years) and those with advanced maternal age (≥35 years), women with no formal education, and women with hypertension during pregnancy were established to have a higher risk of stillbirth in the Bolgatanga Municipality.
Conclusions: The study concluded by indicating the need for various agencies of healthcare in the Bolgatanga Municipality to institute targeted interventions that will help control the effects of the risk factors and enhance improved overall pregnancy outcomes.
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References
Jamie AH. Prevalence and determinants of stillbirth in attended deliveries in University Hospital, Eastern Ethiopia in 2021. Caspian J Reprod Med. 2022;8(1):9-14.
Egbe TO, Ewane EN, Tendongfor N. Stillbirth rates and associated risk factors at the Buea and Limbe regional hospitals, Cameroon: a case-control study. BMC Pregnancy Childbirth. 2020;20(75):1-8. DOI: https://doi.org/10.1186/s12884-020-2767-8
Kasa GA, Woldemariam AY, Adella A, Alemu B. The factors associated with stillbirths among sub-saharan African deliveries: a systematic review and meta-analysis. BMC Pregnancy Childbirth. 2023;23(835):1-18. DOI: https://doi.org/10.1186/s12884-023-06148-6
United Nations. UN-IGME-2020-Stillbirth-Report. 2020.
Nakamya P, Komakech A, Migamba SM, Biribawa C, Kwesiga B, Bulage L, et al. Trends and geospatial distribution of stillbirths in Uganda, 2014–2020. BMC Pregnancy Childbirth. 2024;24(249):1-14. DOI: https://doi.org/10.1186/s12884-024-06434-x
Mahmood NH, Kadir DH, Yahya RO, Birdawod HQ. The significance of delivery methods and fetal gender in reducing stillbirth rate: Using the generalized regression model. Clin Epidemiol Glob Health. 2024;29:1-9. DOI: https://doi.org/10.1016/j.cegh.2024.101710
Dah AK, Osarfo J, Ampofo GD, Appiah-Kubi A, Mbroh H, Azanu WK, et al. Stillbirth incidence and determinants in a tertiary health facility in the Volta Region of Ghana. PLos One. 2023;18(12):e0296076. DOI: https://doi.org/10.1371/journal.pone.0296076
Hug L, You D, Blencowe H, Mishra A, Wang Z, Fix MJ, et al. Global, regional, and national estimates and trends in stillbirths from 2000 to 2019: a systematic assessment. Lancet. 2021;398(10302):772-85. DOI: https://doi.org/10.1016/S0140-6736(21)01112-0
Saleem S, Tikmani SS, McClure EM, Moore JL, Azam SI, Dhaded SM, et al. Trends and determinants of stillbirth in developing countries: results from the Global Network's Population-Based Birth Registry. Reprod Health. 2018;15(100):23-30. DOI: https://doi.org/10.1186/s12978-018-0526-3
Nonterah EA, Agorinya IA, Kanmiki EW, Kagura J, Tamimu M, Ayamba EY, et al. Trends and risk factors associated with stillbirths: A case study of the Navrongo War Memorial Hospital in Northern Ghana. Plos One. 2020;15(2):e0229013. DOI: https://doi.org/10.1371/journal.pone.0229013
Tesema GA, Tessema ZT, Tamirat KS, Teshale AB. Prevalence of stillbirth and its associated factors in East Africa: generalized linear mixed modeling. BMC Pregnancy Childbirth. 2021;21(414):1-10. DOI: https://doi.org/10.1186/s12884-021-03883-6
Nwoga HO, Ajuba MO, Igweagu CP. Still birth in a tertiary health facility in Enugu state South-East Nigeria: a hidden tragedy. Int J Reprod Contracept Obstet Gynecol. 2021;10(7):2584-90. DOI: https://doi.org/10.18203/2320-1770.ijrcog20212643
Milton R, Modibbo F, Gillespie D, Alkali FI, Mukaddas AS, Kassim A, et al. Incidence and sociodemographic, living environment and maternal health associations with stillbirth in a tertiary healthcare setting in Kano, Northern Nigeria. BMC Pregnancy Childbirth. 2022;22(692):1-14. DOI: https://doi.org/10.1186/s12884-022-04971-x
Vanotoo L, Dwomoh D, Laar A, Kotoh AM, Adanu R. Modeling clinical and non-clinical determinants of intrapartum stillbirths in singletons in six public hospitals in the Greater Accra Region of Ghana: a case–control study. Sci Rep. 2023;13(1013):1-12. DOI: https://doi.org/10.1038/s41598-022-27088-9
Mallam I, Abubakar I, Yakubu A. Application of multivariate logistic regression and decision trees to assess factors influencing prevalence of abortion and stillbirth in yankasa sheep. Animal Sci Genet. 2023;19(4):17-27. DOI: https://doi.org/10.5604/01.3001.0053.9650
Gwacham-Anisiobi U, Opondo C, Cheng TS, Kurinczuk JJ, Anyaegbu G, Nairl M. Rates and risk factors for antepartum and intrapartum stillbirths in 20 secondary hospitals in Imo state, Nigeria: A hospital-based case control study. PLOS Glob Public Health. 2024;4(10):e0003771. DOI: https://doi.org/10.1371/journal.pgph.0003771
Rastegar M, Nazar E, Nasehi M, Sharafi S, Fakoor V, Shakeri MT. Bayesian estimation of the time-varying reproduction number for pulmonary tuberculosis in Iran: a registry-based study from 2018 to 2022 using new smear-positive cases. Infect Dis Model. 2024;9(3):963-74. DOI: https://doi.org/10.1016/j.idm.2024.05.003
Gemechu LL, Debusho LK. Bayesian spatial modelling of tuberculosis-HIV co-infection in Ethiopia. PLos One. 2023;18(3):e0283334. DOI: https://doi.org/10.1371/journal.pone.0283334
Blangiardo M, Cameletti M. Spatial and spatio-temporal Bayesian models with R-INLA. John Wiley & Sons; 2015. DOI: https://doi.org/10.1002/9781118950203
Hahn U. The Bayesian boom: good thing or bad? Front Psychol. 2014;5(765):1-12. DOI: https://doi.org/10.3389/fpsyg.2014.00765
Robert CP, Rousseau JM. A special issue on Bayesian inference: challenges, perspectives and prospects. Phil Trans R Soc A. 2023;381:1-4. DOI: https://doi.org/10.1098/rsta.2022.0155
Lukman PA, Abdullah S, Rachman A. Bayesian logistic regression and its application for hypothyroid prediction in post-radiation nasopharyngeal cancer patients. J Phys Conf Ser. 2021;1725:1-10. DOI: https://doi.org/10.1088/1742-6596/1725/1/012010
Uspensky JV. Introduction to Mathematical Probability. New York: McGraw-Hill; 1937.
Farhin, S. and Khan, A. A. Bayesian survival analysis of acute encephalitis syndrome with censoring mechanism using brms package. J Stat Appl Probab. 2022;11(3):963-80. DOI: https://doi.org/10.18576/jsap/110319
Amani A, Nansseu JR, Ndeffo GF, Njoh AA, Cheuyem FZL, Libite PR, et al. Stillbirths in Cameroon: an analysis of the 1998-2011 demographic and health surveys. BMC Pregnancy Childbirth. 2022;22:736. DOI: https://doi.org/10.1186/s12884-022-04993-5
Regassa Y, Lemi H, Charkos TG. Determinants of stillbirth among mothers who gave birth at Bishoftu General Hospital, Ethiopia: using a Bayesian logistic regression model. Front Glob Women's Health. 2024. DOI: https://doi.org/10.3389/fgwh.2024.1441636
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