Modeling time-to-first antenatal care (anc) visit in Ethiopia: a comparison of acceleration failure time and Parametric shared frailty models

Abstract

Background: The survival of pregnant women is one of great interest of the world and especially to a developing country like Ethiopia which had the highest maternal mortality ratios in the world due to low utilization of maternal health services including Antenatal care (ANC).Survival analysis is a statistical method for data analysis where the outcome variable of interest is time to occurrence of an event. AFT and frailty model is an extension of Cox's PH model in which the hazard function depends upon time and an unobservable random quantity called frailty. Regional states of the women were used as a clustering effect in all frailty models. Methodology: The study aimed to model the determinants of time-to-first antenatal care visits to Ethiopia. The data for the study were taken from the 2016 EDHS and data of 7161 women in the age group of 15-49 years, who got pregnancy during five years survey whom survival information available were included in the analysis. The AFT and gamma shared frailty models with weibull, log-normal and log-logistic baseline distribution were employed to identify the best model fit for the timing of first ANC visit using health-related risk factors, socio-economic and demographic factors. All the fitted models were compared by AIC. Results: The median of time of first ANC visit was 5 months. The log-logistic with Gamma shared frailty model is an appropriate model when compared with other models for a time at first ANC visit dataset based on AIC and graphical evidence. The clustering effect was significant for modelling the determinants of time-to-first ANC visit dataset. The final model showed that place of residence, perceived problem to get medical care due to distance, wanted pregnancy; women and husband education level, religions, wealth index, and parity were found to be significant determinants of time at first ANC visit at 5% level of significance. The estimated acceleration factor for the group of women's who had secondary and higher educational level was highly earlier time at first ANC visit by the factor of ϕ=0.89 and ϕ=0.86 respectively. Conclusion: The log-logistic with gamma shared frailty model described time at first ANC visit data set better than other models and there was heterogeneity between the regions on time-tofirst ANC initiation. Specific efforts are needed to target women of lower socioeconomic status, access to informal education for woman and husband, accessing health facilities due to distance and give awareness about having few numbers of children was an important avenue for rising women's time at first ANC visit.Background: The survival of pregnant women is one of great interest of the world and especially to a developing country like Ethiopia which had the highest maternal mortality ratios in the world due to low utilization of maternal health services including Antenatal care (ANC).Survival analysis is a statistical method for data analysis where the outcome variable of interest is time to occurrence of an event. AFT and frailty model is an extension of Cox's PH model in which the hazard function depends upon time and an unobservable random quantity called frailty. Regional states of the women were used as a clustering effect in all frailty models. Methodology: The study aimed to model the determinants of time-to-first antenatal care visits to Ethiopia. The data for the study were taken from the 2016 EDHS and data of 7161 women in the age group of 15-49 years, who got pregnancy during five years survey whom survival information available were included in the analysis. The AFT and gamma shared frailty models with weibull, log-normal and log-logistic baseline distribution were employed to identify the best model fit for the timing of first ANC visit using health-related risk factors, socio-economic and demographic factors. All the fitted models were compared by AIC. Results: The median of time of first ANC visit was 5 months. The log-logistic with Gamma shared frailty model is an appropriate model when compared with other models for a time at first ANC visit dataset based on AIC and graphical evidence. The clustering effect was significant for modelling the determinants of time-to-first ANC visit dataset. The final model showed that place of residence, perceived problem to get medical care due to distance, wanted pregnancy; women and husband education level, religions, wealth index, and parity were found to be significant determinants of time at first ANC visit at 5% level of significance. The estimated acceleration factor for the group of women's who had secondary and higher educational level was highly earlier time at first ANC visit by the factor of ϕ=0.89 and ϕ=0.86 respectively. Conclusion: The log-logistic with gamma shared frailty model described time at first ANC visit data set better than other models and there was heterogeneity between the regions on time-tofirst ANC initiation. Specific efforts are needed to target women of lower socioeconomic status, access to informal education for woman and husband, accessing health facilities due to distance and give awareness about having few numbers of children was an important avenue for rising women's time at first ANC visit.