Osong Public Health and Research Perspectives

Payam Amini

2 Articles

Factors Associated with Cesarean Section in Tehran, Iran using Multilevel Logistic Regression Model: Payam Amini, Maryam Mohammadi, Reza Omani-Samani, Amir Almasi-Hashiani, Saman Maroufizadeh; Osong Public Health Res Perspect. 2018;9(2):86-92. Published online April 30, 2018; DOI: https://doi.org/10.24171/j.phrp.2018.9.2.08

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Objectives

Over the past few decades, the prevalence of cesarean sections (CS) have risen dramatically worldwide, particularly in Iran. The aim of this study was to determine the prevalence of CS in Tehran, and to examine the associated risk factors.

Methods

A cross-sectional study of 4,308 pregnant women with singleton live-births in Tehran, Iran, between July 6–21, 2015 was performed. Multilevel logistic regression analysis was performed using demographic and obstetrical variables at the first level, and hospitals as a variable at the second level.

Results

The incidence of CS was 72.0%. Multivariate analysis showed a significant relationship between CS and the mother’s age, socioeconomic status, body mass index, parity, type of pregnancy, preeclampsia, infant height, and baby’s head circumference. The intra-class correlation using the second level variable, the hospital was 0.292, indicating approximately 29.2% of the total variation in the response variable accounted for by the hospital.

Conclusion

The incidence of CS was substantially higher than other countries. Therefore, educational and psychological interventions are necessary to reduce CS rates amongst pregnant Iranian women.

Citations

Citations to this article as recorded by

The double burden of maternal overweight and short stature and the likelihood of cesarean deliveries in South Asia: An analysis of national datasets from Bangladesh, India, Maldives, Nepal, and Pakistan
Mosiur Rahman, Syed Emdadul Haque, Md. Jahirul Islam, Nguyen Huu Chau, Izzeldin Fadl Adam, Md. Nuruzzaman Haque
Birth.2022; 49(4): 661. CrossRef
Geospatial analysis of cesarean section in Iran (2016–2020): exploring clustered patterns and measuring spatial interactions of available health services
Alireza Mohammadi, Elahe Pishgar, Zahra Salari, Behzad Kiani
BMC Pregnancy and Childbirth.2022;[Epub] CrossRef
Factors associated with cesarean delivery in Bangladesh: A multilevel modeling
Md. Akhtarul Islam, Mst. Tanmin Nahar, Md. Ashfikur Rahman, Sutapa Dey Barna, S.M. Farhad Ibn Anik
Sexual & Reproductive Healthcare.2022; 34: 100792. CrossRef
The Birth Satisfaction Scale-Revised Indicator (BSS-RI): a validation study in Iranian mothers
Reza Omani-Samani, Caroline J. Hollins Martin, Colin R. Martin, Saman Maroufizadeh, Azadeh Ghaheri, Behnaz Navid
The Journal of Maternal-Fetal & Neonatal Medicine.2021; 34(11): 1827. CrossRef
The effect of familiarization with preoperative care on anxiety and vital signs in the patient’s cesarean section: A randomized controlled trial
Mehrnush Mostafayi, Behzad Imani, Shirdel Zandi, Faeze Jongi
European Journal of Midwifery.2021; 5(June): 1. CrossRef
Dynamic prediction of liver cirrhosis risk in chronic hepatitis B patients using longitudinal clinical data
Ying Wang, Xiang-Yong Li, Li-Li Wu, Xiao-Yan Zheng, Yu Deng, Meng-Jie Li, Xu You, Yu-Tian Chong, Yuan-Tao Hao
European Journal of Gastroenterology & Hepatology.2020; 32(1): 120. CrossRef
Factors Contributing to Iranian Pregnant Women’s Tendency to Choice Cesarean Section
Soraya Nouraei Motlagh, Zahra Asadi-piri, Razyeh Bajoulvand, Fatemeh Seyed Mohseni, Katayoun Bakhtiar, Mehdi Birjandi, Maryam Mansouri
Medical - Surgical Nursing Journal.2020;[Epub] CrossRef
Trends and correlates of cesarean section rates over two decades in Nepal
Aliza K. C. Bhandari, Bibha Dhungel, Mahbubur Rahman
BMC Pregnancy and Childbirth.2020;[Epub] CrossRef
Symptoms of Discomfort and Problems Associated with Mode of Delivery During the Puerperium: An Observational Study
Martínez-Galiano, Delgado-Rodríguez, Rodríguez-Almagro, Hernández-Martínez
International Journal of Environmental Research an.2019; 16(22): 4564. CrossRef

Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods: Payam Amini, Saman Maroufizadeh, Reza Omani Samani, Omid Hamidi, Mahdi Sepidarkish; Osong Public Health Res Perspect. 2017;8(3):195-200. Published online June 30, 2017; DOI: https://doi.org/10.24171/j.phrp.2017.8.3.06

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30 Download
8 Citations

Abstract PDF

Objectives

Preterm birth (PTB) is a leading cause of neonatal death and the second biggest cause of death in children under five years of age. The objective of this study was to determine the prevalence of PTB and its associated factors using logistic regression and decision tree classification methods.

Methods

This cross-sectional study was conducted on 4,415 pregnant women in Tehran, Iran, from July 6–21, 2015. Data were collected by a researcher-developed questionnaire through interviews with mothers and review of their medical records. To evaluate the accuracy of the logistic regression and decision tree methods, several indices such as sensitivity, specificity, and the area under the curve were used.

Results

The PTB rate was 5.5% in this study. The logistic regression outperformed the decision tree for the classification of PTB based on risk factors. Logistic regression showed that multiple pregnancies, mothers with preeclampsia, and those who conceived with assisted reproductive technology had an increased risk for PTB (p < 0.05).

Conclusion

Identifying and training mothers at risk as well as improving prenatal care may reduce the PTB rate. We also recommend that statisticians utilize the logistic regression model for the classification of risk groups for PTB.

Citations

Citations to this article as recorded by

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JMIR Public Health and Surveillance.2022; 8(11): e38182. CrossRef
Iranian midwives’ awareness and performance of respectful maternity care during labor and childbirth
Simin Haghdoost, Fatemeh Abdi, Azam Amirian
European Journal of Midwifery.2021; 5(December): 1. CrossRef
A diagnostic profile on the PartoSure test
Safoura Rouholamin, Maryam Razavi, Mahroo Rezaeinejad, Mahdi Sepidarkish
Expert Review of Molecular Diagnostics.2020; 20(12): 1163. CrossRef
Comparison of Multivariable Logistic Regression and Other Machine Learning Algorithms for Prognostic Prediction Studies in Pregnancy Care: Systematic Review and Meta-Analysis
Herdiantri Sufriyana, Atina Husnayain, Ya-Lin Chen, Chao-Yang Kuo, Onkar Singh, Tso-Yang Yeh, Yu-Wei Wu, Emily Chia-Yu Su
JMIR Medical Informatics.2020; 8(11): e16503. CrossRef
Analysis of Spontaneous Preterm Labor and Birth and Its Major Causes Using Artificial Neural Network
Yun-Sook Kim
Journal of Korean Medical Science.2019;[Epub] CrossRef
A systematic review shows no performance benefit of machine learning over logistic regression for clinical prediction models
Evangelia Christodoulou, Jie Ma, Gary S. Collins, Ewout W. Steyerberg, Jan Y. Verbakel, Ben Van Calster
Journal of Clinical Epidemiology.2019; 110: 12. CrossRef
Comparison of three data mining models for prediction of advanced schistosomiasis prognosis in the Hubei province
Guo Li, Xiaorong Zhou, Jianbing Liu, Yuanqi Chen, Hengtao Zhang, Yanyan Chen, Jianhua Liu, Hongbo Jiang, Junjing Yang, Shaofa Nie, Michael French
PLOS Neglected Tropical Diseases.2018; 12(2): e0006262. CrossRef
Algorithm on age partitioning for estimation of reference intervals using clinical laboratory database exemplified with plasma creatinine
Xiaoxia Peng, Yaqi Lv, Guoshuang Feng, Yaguang Peng, Qiliang Li, Wenqi Song, Xin Ni
Clinical Chemistry and Laboratory Medicine (CCLM).2018; 56(9): 1514. CrossRef

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