Adherence to the recommended timing of focused antenatal care in the Accra Metropolitan Area, Ghana.

INTRODUCTION: The proportion of antenatal attendants in Ghana who had at least four antenatal visits increased from 78% in 2008 to 87% in 2014. However, it is not known whether these visits followed the recommended timing of focused antenatal clinic attendance in Ghana. We sought to assess the adherence to the clinic schedule and its determinants in the Accra Metropolis. METHODS: A cross-sectional study was conducted. Face-to-face interviews were conducted with postpartum women. Multiple logistic regression was used in the analysis of determinants of adherence to the recommended timing of clinic attendance. A p-value of <0.05 was considered statistically significant. RESULTS: Among 446 focused antenatal care clinic attendants, 378 (84.8%) had four or more visits. Among these, 101 (26.7%) adhered to the recommended clinic schedule. Women who adhered were more likely to have had education up to Junior High School [AOR=3.31, 95%CI (1.03-10.61)] or Senior High School [AOR=4.47, 95%CI (1.14-17.51)], or have history of abortion [(AOR=3.36, 95%CI (1.69-7.96)]. For every week increase in gestational age at booking at the antenatal clinic, respondents were 34% less likely to complete all four antenatal visits at the recommended times. [(AOR=0.66, 95% (0.60-0.73)]. CONCLUSION: Majority of women receiving focused antenatal care in the Accra Metropolis have four or more visits but only about a quarter of them adhered to the recommended clinic schedule. Having high school education, history of abortion and early initiation of antenatal care were predictors of adherence to clinic schedule. Women should be educated on early initiation of antenatal care to enhance adherence.

Bayesian inference of the Weibull model based on interval-censored survival data.

Interval-censored data consist of adjacent inspection times that surround an unknown failure time. We have in this paper reviewed the classical approach which is maximum likelihood in estimating the Weibull parameters with interval-censored data. We have also considered the Bayesian approach in estimating the Weibull parameters with interval-censored data under three loss functions. This study became necessary because of the limited discussion in the literature, if at all, with regard to estimating the Weibull parameters with interval-censored data using Bayesian. A simulation study is carried out to compare the performances of the methods. A real data application is also illustrated. It has been observed from the study that the Bayesian estimator is preferred to the classical maximum likelihood estimator for both the scale and shape parameters.