BACKGROUND: Depression is prevalent during antenatal and postnatal stages of pregnancy. The effect of depression can be seen in complications during and after pregnancy, fetal growth retardation, abortions and preterm births. The literature abounds on postpartum depression (PD) while few studies are on antepartum depression (AD). AIM: The systematic review aims to compute the prevalence of AD from published articles. MATERIAL AND METHODS: The published articles (26) used in this review were obtained from the search of the search keywords “Depressive conditions in pregnancy AND trimesters”. All the articles were considered irrespective of language and their citation status as of the time of the query. Only articles that presented the prevalence mean and sample size were included. Articles on questionnaires filled by nonpregnant women and men were excluded. Articles that presented the prevalence of depression for the postpartum period only were excluded but were included if they addressed depression at both postpartum and trimester(s) of pregnancy. P-value of less than or equal to 0.05 was considered significant. RESULTS: Analysis of the 26 articles showed that 4,303 subjects tested positive for depression in a sample of 28,248 pregnant mothers, giving the prevalence rate as 15%. Confounding was removed, and the sample size was adjusted to be 25,771 and 4,223 were screened to have depressive symptoms, thereby giving a new prevalence rate as 16.4%. It was also revealed that AD is most prevalent in the last trimester of pregnancy and least in the second trimester. Pregnancy duration and PD are not correlated with AD. This implies that AD can be observed in any period of the pregnancy and cannot predict the incidence of PD. CONCLUSION: Efforts must be intensified to monitor pregnant women during the third trimester to reduce the incidence of maternal depression during pregnancy, thereby reducing the prevalence.

A B S T R A C TA three parameter probability model, the so called Weibull-exponential distribution was proposed using the Weibull Generalized family of distributions. Some important models in the literature were found to be sub models of the new model. Explicit expressions for some of its basic mathematical properties like moments, moment generating function, reliability analysis, limiting behavior and order statistics were derived. The method of maximum likelihood estimation was proposed in estimating its parameters and real life applications were provided to illustrate its flexibility and potentiality over the exponential distribution.

This article introduces a two-parameter probability model which represents another generalization of the Inverse Exponential distribution by using the quadratic rank transmuted map. The proposed model is named Transmuted Inverse Exponential (TIE) distribution and its statistical properties are systematically studied. We provide explicit expressions for its moments, moment generating function, quantile function, reliability function and hazard function. We estimate the parameters of the TIE distribution using the method of maximum likelihood estimation (MLE). The hazard function of the model has an inverted bathtub shape and we propose the usefulness of the TIE distribution in modeling breast cancer and bladder cancer data sets.

In this article, a random number of datasets was generated from random samples of used GSM (Global Systems for Mobile Communications) recharge cards. Statistical analyses were performed to refine the raw data to random number datasets arranged in table. A detailed description of the method and relevant tests of randomness were also discussed.

No abstract

Crime is an act that brings about offences and it is punishable under the law. Major crimes in Nigeria include rape, kidnapping, murder, burglary, fraud, terrorism, robbery, cyber-crimes, bribery and corruption, money laundering and so on. According to the statistics released by the Nigerian National Bureau of Statistics in 2016, Lagos, Abuja, Delta, Kano, Plateau, Ondo, Oyo, Bauchi, Adamawa and Gombe States made the top ten list of states with high number of crimes. Crime is an important topic and it is of interest to us because of the consequences and penalties it attracts (which ranges from fine to death). This data article contains the partial analysis (both descriptive and inferential) of crime data set obtained between 1999 and 2013. The aim of the study is to show the pattern and rate of crime in Nigeria based on the data collected and to show the relationships that exist among the various crime types. Analyzing this data set can provide insight on crime activities within Nigeria.

Breast cancer is the type of cancer that develops from breast tissue; it is mostly common in women and it is one of the most studied diseases, largely because of its high mortality (second to lung cancer). However, it occurs in males also. This article presents a statistical study of the distribution of age, gender, length of stay, mode of diagnosis, status (dead or alive) after treatment and the location of breast cancer among 300 patients admitted in the University of Ilorin teaching hospital, Ilorin, Nigeria. The study covers a period of five (5) years; from 2011 to 2016 and logistic regression was used to perform the basic analysis in this study. It was discovered that the age of patients and the location of the breast cancer (right or left) contributes significantly to the survival of the patients. However, early detection and treatment of the disease is highly encouraged. This study also recommends that awareness should be taken to the grassroots and males should not be excluded from this discussion.

BACKGROUND: Noise pollution has become a major environmental problem leading to nuisances and health issues. AIM: This paper aims to study and analyse the noise pollution levels in major areas in Ota metropolis. A probability model which is capable of predicting the noise pollution level is also determined. METHODS: Datasets on the noise pollution level in 41 locations across Ota metropolis were used in this research. The datasets were collected thrice per day; morning, afternoon and evening. Descriptive statistics were performed, and analysis of variance was also conducted using Minitab version 17.0 software. Easy fit software was however used to select the appropriate probability model that would best describe the dataset. RESULTS: The noise levels are way far from the WHO recommendations. Also, there is no significant difference in the effects of the noise pollution level for all the times of the day considered. The log-logistic distribution provides the best fit to the dataset based on the Kolmogorov Smirnov goodness of fit test. CONCLUSION: The fitted probability model can help in the prediction of noise pollution and act as a yardstick in the reduction of noise pollution, thereby improving the public health of the populace.