The fertility rate of a married woman can be measured by the length of the first birth interval (FBI). This length is influenced by some significant factors. Better knowledge about the factors affecting the birth interval can help in controlling population growth and fertility progress. The main focus of this study was to compare the performance of Cox-Proportional Hazard (Cox-PH) and the parametric Accelerated Failure Time (AFT) model in assessing the impact of significant factors affecting the time to FBI of ever-married Bangladeshi women. Information of 14941 women having at least one birth was included in this study from the most recent nationally representative data 2017-18 Bangladesh Demographic and Health Survey (BDHS). We used the Cox-PH model and AFT model under various parametric forms of survival time distributions (Weibull, Exponential, and Log-normal distribution) to measure the effect of factors influencing FBI. And then, a respective Akaike information criterion (AIC) was calculated for selecting the best-fitted model. According to the AIC and BIC values, the log-normal model fitted better than other AFT models. Based on the log-normal model, women's age and age at first marriage, maternal and paternal education, contraceptive use status, used anything to avoid pregnancy, sex of household head, and spousal age difference had a significant association with FBI of ever married Bangladeshi women. The parametric AFT model (log-normal distribution) was a better fitted model in evaluating the covariates associated with FBI of ever-married Bangladeshi Women. Higher education, the right age at marriage, and proper knowledge about family planning (i.e., contraception use) should be ensured for every married person to control the gap of the first birth.
Factors associated with time to first birth interval among ever married Bangladeshi women: A comparative analysis on Cox-PH model and parametric models.
阅读:14
作者:Setu Sarmistha Paul, Kabir Rasel, Islam Md Akhtarul, Alauddin Sharlene, Nahar Mst Tanmin
| 期刊: | PLOS Global Public Health | 影响因子: | 2.500 |
| 时间: | 2024 | 起止号: | 2024 Dec 18; 4(12):e0004062 |
| doi: | 10.1371/journal.pgph.0004062 | ||
特别声明
1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。
2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。
3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。
4、投稿及合作请联系:info@biocloudy.com。
