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

Prevalence and factors associated with caesarean section among Tanzanian women of reproductive age: evidence from the 2022 Tanzania demographic and health survey data
Bonfils Nahayo, Gbenga Olorunfemi, Samuel Ndayishimye, Charles Nsanzabera
BMC Public Health.2025;[Epub] CrossRef
Determinants of cesarean mode of childbirth among Rwandan women of childbearing age: Evidence from the 2019–2020 Rwanda Demographic and Health Survey (RDHS)
Nsereko Etienne, Uwase Aline, Mpinganzima Ornella, Usanzineza Henriette, Niyitegeka Jean Pierre, Turabayo Jean Léonard, Mwiseneza Marie Josee, Mugeni Girimpundu Candide, Moreland Patricia
Public Health Challenges.2024;[Epub] CrossRef
Factors Associated with Cesarean Section in Preterm Births at a Tertiary Hospital in Rasht, Iran
Forozan Milani, Seyedeh Hajar Sharami, Seyedeh Maryam Attari, Zahra Rafiee Sorouri, Sara Farzadi, Soodabeh Kazemi
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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
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Md. Akhtarul Islam, Mst. Tanmin Nahar, Md. Ashfikur Rahman, Sutapa Dey Barna, S.M. Farhad Ibn Anik
Sexual & Reproductive Healthcare.2022; 34: 100792. CrossRef
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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
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European Journal of Midwifery.2021; 5(June): 1. CrossRef
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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
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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

6,219 View
46 Download
12 Crossref

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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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
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Guo Li, Xiaorong Zhou, Jianbing Liu, Yuanqi Chen, Hengtao Zhang, Yanyan Chen, Jianhua Liu, Hongbo Jiang, Junjing Yang, Shaofa Nie, Michael French
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