Survival Analysis of Childbirth Using a Mixture Cure Frailty Model
Survival Analysis of Childbirth
-
Azadeh Naderi
,
Abbas Rahimi Foroushani
,
Ali Moghadas Jafari
,
Mohammed Ibrahim Mohialdeen Gubari
,
Mostafa Hosseini
Abstract
Introduction: Childbirth plays a crucial role in population growth and maternal health. In recent decades, many nations,
including Iran, have experienced declining birth rates. Since childbirth is a recurrent event in a parent's life, it is useful to
analyze it through the lens of recurrent event analysis. This methodological framework, commonly employed in biomedicine,
allows for a nuanced examination of the relationship between multiple childbirth experiences and the potential for cured
subjects. This study explores childbirth rates in Hamadan province.
Methods: A total of 633 mothers who gave birth to their first child in 2012 at Fatemiyeh Hospital in Hamadan participated
in this retrospective cohort study. Both mixture cure frailty models and simple frailty models were fitted. The analyses were
conducted using the RSTAN package in RStudio version 26.2.4.
Results: In this study, we analyzed the childbearing patterns of couples and found that the majority (60.6%) had two
children. Additionally, we discovered that 49% of mothers and 55.9% of fathers had education levels below a diploma.
The Kaplan-Meier (KM) curves indicated a cure pattern for families with three or more children, revealing that only
10.6% of individuals had three children, and a mere 0.8% had four. Furthermore, results from a mixture cure frailty model
demonstrated that maternal education plays a crucial role in influencing childbirth probabilities.
Conclusion: Based on the findings of this study, we recommend utilizing mixture cure frailty models rather than simple
frailty models when the dataset contains individuals who are cured.
1. Erfani A, Nojomi M, Hosseini H. PROLONGED BIRTH INTERVALS IN HAMEDAN, IRAN:
VARIATIONS AND DETERMINANTS. Journal of Biosocial Science. 2017;50:1-15.
2. Jafari H, Pourreza A, Kabiri N, Khodyari-Zarnaq R. Main actors in the new population policy
with a growing trend in Iran: a stakeholder analysis. Journal of health, population, and nutrition.
2022;41(1):57.
3. Najafi-Vosough R, Soltanian AR, Fayyazi N. Influence Factors on Birth Spacing and Childbearing
Rates using Survival Recurrent Events Model and Parity Progression Ratios: J Res Health Sci.
2017 Jul 7;17(3):384. eCollection 2017 Summer.
4. Shayan Z, Ayatollahi SM, Zare N, Moradi F. Prognostic factors of first birth interval using the
parametric survival models. Iranian journal of reproductive medicine. 2014;12(2):125-30.
5. Fallahzadeh H, Farajpour Z, Emam Z. Duration and determinants of birth interval in Yazd, Iran: a
population study. Iranian journal of reproductive medicine. 2013;11(5):379-84.
6. Ekawati R, Rahayuwati L, Nurhidayah I, S Agustina H, Rahayu E. DETERMINANT FACTORS OF
FERTILITY IN REPRODUCTIVE AGE WOMEN IN WEST JAVA PROVINCE INDONESIA.
Jurnal Keperawatan Padjadjaran. 2019;7.
7. Sagara I, Giorgi R, Doumbo O, Piarroux R, Gaudart J. Modelling recurrent events: Comparison of
statistical models with continuous and discontinuous risk intervals on recurrent malaria episodes
data. Malaria journal. 2014;13:293.
8. Conlon AS, Taylor JM, Sargent DJ. Multi-state models for colon cancer recurrence and death with
a cured fraction. Statistics in medicine. 2014;33(10):1750-66.
9. Ahmad Reza B, zahra Arab B, Elaheh Talebi G, Ali Akbar Khadem m, Anahita S, Ali A. Joint
frailty model of recurrent and terminal events in the presence of cure fraction using a Bayesian
approach. Journal of Biostatistics and Epidemiology. 2023;8(3).
10. Tsodikov A.D, Ibrahim J.G, Yakovlev A.Y. Estimating Cure Rates from Survival Data: An
Alternative to Two-Component Mixture Models. Journal of the American Statistical Association.
2003;98(464):1063-78.
11. Sevda R, Mahboobe R, Jamileh A, Moein Y, Azita A, Asieh A. Contribution Factors on
Long- term and Short- term Survival of Thalassemia Major Patients. Journal of Biostatistics and
Epidemiology. 2021;7(4).
12. Amanpour F, Akbari S, Azizmohammad Looha M, Abdehagh M, Pourhoseingholi MA. Mixture
cure model for estimating short-term and long-term colorectal cancer survival. Gastroenterology
and hepatology from bed to bench. 2019;12(Suppl1):S37-s43.
13. Kim Y-J. Joint model for recurrent event data with a cured fraction and a terminal event. Biometrical
Journal. 2020;62(1):24-33.
14. Xu Y, Cheung Y. Frailty Models and Frailty-Mixture Models for Recurrent Event Times. Stata
Journal. 2015;15:135-54.
15. Tawiah R, McLachlan GJ, Ng SK. A bivariate joint frailty model with mixture framework for
survival analysis of recurrent events with dependent censoring and cure fraction. Biometrics.
2020;76(3):753-66.
16. Hosseini-Chavoshi M, Abbasi-Shavazi M, McDonald P. Fertility, Marriage, and Family Planning
in Iran: Implications for Future Policy. Population Horizons. 2017;13.
17. Kashem SR, Arokiasamy JT, Khanam ST, Anthonisamy AN, Bhatt P, Islam M. Sociodemographic
factors associated with birth interval: a study among rural women in Chandina, Comilla,
Bangladesh. Journal of Public Health. 2020;28:11-5.
18. Zare N, Soltani M, Sayadi M, Rajaeefard A. Factors affecting inter-birth in rural areas of Zarrindasht
(Fars province). Iranian South Medical Journal. 2015;17(6):1143-52.
19. Rondeau V, Schaffner E, Corbière F, Gonzalez JR, Mathoulin-Pélissier S. Cure frailty models
for survival data: Application to recurrences for breast cancer and to hospital readmissions for
colorectal cancer. Statistical methods in medical research. 2013;22(3):243-60.
| Files | ||
| Issue | Vol 11 No 3 (2025): . | |
| Section | Articles | |
| Keywords | ||
| Birth Mixture cure Fraility models | ||
| Rights and permissions | |
|
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
