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BackgroundChild and maternal mortality and morbidity remain among the top global health challenges despite various efforts and multitude of resources directed to improving this situation over time. This study assessed trend of the timings of first antenatal care (ANC) visit in Nigeria and also identified the risk factors associated with it.MethodsThe data obtained from three consecutive Nigerian Demographic and Health Surveys in 2003, 2008, and 2013 were pooled. We focused on the ANC attendance history during the current pregnancies or the last pregnancies within 5 years preceding the survey irrespective of how the pregnancy ended. The gestational age at time of first ANC visit was computed as the survival time, while others who did not attend ANC were censored. Basic descriptive statistics and survival analysis methods were used to analyze the data.ResultsA total of 45,690 pregnancies were studied, of which 70% were from rural areas. Mothers were mostly (45%) aged 25–34 years and 47.1% had no formal education, while only 37.9% were involved in decisions on the use of health care facility. Prevalence of ANC use was 60.5% in 2008 and 65.8% in both 2003 and 2013. Less than one-third (32.3%) of the women accessed ANC within first 3 months of pregnancy, with highest rate (41.7%) among women with higher education and those from North Central Nigeria (42.7%). The hazard of the timing of first ANC visit was higher in years 2003 and 2013 than in 2008.ConclusionInitiation of ANC visit in Nigeria is generally late with most women making first visit during second trimester, with significant variations across the years studied. The increase in coverage of ANC recorded in 2003 and 2013 was not accompanied by earlier commencement of ANC visit. Maternal health stakeholders should do more to ensure that all pregnant women start ANC visit earlier.

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We propose a new generalized family of distributions called the exponentiated generalized power series (EGPS) family of distributions and study its sub-model, the exponentiated generalized logarithmic (EGL) class of distributions, in detail. The structural properties of the new model (EGPS) and its sub-model (EGL) distribution including moments, order statistics, Rényi entropy, and maximum likelihood estimates are derived. We used the method of maximum likelihood to estimate the parameters of this new family of distributions. Simulation study was carried out to examine the bias and the mean square error of the maximum likelihood estimators for each of the model's parameters. Finally, we showed real life data examples to illustrate the models' applicability, flexibility and usefulness.

We propose a generalized class of distributions called the Webull-G Power Series (WGPS) family of distributions and its sub-model Weibull-G logarithmic (WGL) distributions. Structural properties of the WGPS family of distributions and its sub-model WGL distribution including hazard function, moments, conditional moments, order statistics, R´enyi entropy and maximum likelihood estimates are derived. A simulation study to examine the bias, mean square error of the maximum likelihood estimators for each parameter is presented. Finally, real data examples are presented to illustrate the applicability and usefulness of the proposed model.