- Factors Associated with Cesarean Section in Tehran, Iran using Multilevel Logistic Regression Model
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Payam Amini, Maryam Mohammadi, Reza Omani-Samani, Amir Almasi-Hashiani, Saman Maroufizadeh
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Osong Public Health Res Perspect. 2018;9(2):86-92. Published online April 30, 2018
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DOI: https://doi.org/10.24171/j.phrp.2018.9.2.08
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Abstract
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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.
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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 Journal of Kermanshah University of Medical Scienc.2024;[Epub] CrossRef - Virtual Reality, Fear of Pain and Labor Pain Intensity: A Randomized Controlled Trial
Halimeh Mohammadi, Javad Rasti, Elham Ebrahimi Anesthesiology and Pain Medicine.2023;[Epub] CrossRef - 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
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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
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- Prevalence and Determinants of Preterm Birth in Tehran, Iran: A Comparison between Logistic Regression and Decision Tree Methods
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Payam Amini, Saman Maroufizadeh, Reza Omani Samani, Omid Hamidi, Mahdi Sepidarkish
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Osong Public Health Res Perspect. 2017;8(3):195-200. Published online June 30, 2017
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DOI: https://doi.org/10.24171/j.phrp.2017.8.3.06
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6,194
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45
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12
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Abstract
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- 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. MethodsThis 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. ResultsThe 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). ConclusionIdentifying 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.
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Citations
Citations to this article as recorded by 
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