BackgroundContraceptives are used in family planning to space or limit pregnancies and are categorized into modern and traditional methods. The modern methods have been proven to be more scientifically effective at preventing unwanted pregnancies than the traditional methods. With data from three (3)-different Demographic and Health Surveys, the aim of this study is to assess the trends and identify factors that consistently influence modern contraceptives’ use among women of the reproductive age group in Ghana.MethodsThe study used secondary data from the 2003, 2008, and 2014 Ghana Demographic Health Surveys (GDHS). The trends of determinants of modern contraceptives use among women of reproductive age in Ghana were determined. A bivariate approach was used to select significant predictors. The Cox proportional hazards model analysis was employed via a multilevel modelling approach.ResultsOut of the total respondents of 2229, 2356, and 4469, 18.75%, 15.75% and 21.53% were modern contraceptives users for 2003, 2008 and 2014 respectively. The multiple cox proportional hazards model analysis identified place of residence and the educational level of a woman as strong predictors of modern contraceptives use in Ghana. Modern contraceptive use is increasing among rural residence. Women who are in formal occupations (professional, clerical, services) are more likely to use modern contraceptives than their colleagues in less formal occupations (manual, agricultural, sales).ConclusionThis study highlights the trends of determinants on modern contraceptive use in Ghana from 2003 to 2014. The most persistent determinants of modern contraceptive use in Ghana during this time period are place of residence and a woman’s educational level. Women working in Agriculture and Sales are the least users of modern contraceptives in Ghana over the period.

BackgroundBreast cancer is one of the most dangerous and frequently occurring cancers among women, and it also affects men. We aimed to determine the prevalence and factors associated with mortality among patients with breast cancer in Saudi Arabia.MethodData for this analysis of breast cancer mortality among Saudi Arabians were obtained from the Saudi Arabian Cancer Registry at the King Faisal Hospital and Research Centre. Both descriptive and inferential statistical analyses were conducted using proportions, chi-squared tests, and the Cox regression model. Frequentist and Bayesian inferential statistics were used to estimate the risk ratios. A frailty term was specified to control for suspected heterogeneity across regions. Bayesian and deviance information criteria were used to discriminate between the frequentist and Bayesian frailty models, respectively.ResultsOut of 5,411 patients, 708 (13.08%) deaths occurred that were attributable to breast cancer. Of those, 12 (1.69%) were men. Among patients who died of breast cancer, 353 (49.86%) had tumours that originated on the left side and 338 (47.74%) on the right side. In terms of the stage or extent of breast cancer, 318 (44.92%) deaths occurred among patients who had distant metastases, followed by 304 (42.94%) who had regional metastases and 86 (12.15%) with localized cancers. Men were 72% more likely than women to die from breast cancer. Divorcees were twice as likely to die, compared to their married counterparts. Patients whose tumours were classified as Grade IV had the highest mortality rate, which was 5.0 times higher than patients with Grade I tumours (credible interval (CrI); 1.577, 14.085) and 3.7 times higher than patients with Grade II tumours (CrI; 1.205, 9.434).ConclusionThere is a high prevalence of breast cancer mortality among Saudi Arabian women, with the highest prevalence among divorced women. Though the prevalence of breast cancer mortality among men is lower than that of women, men had a higher risk of death. We therefore recommend an intensive health education programme for both men and women. These programmes should discuss the consequences of divorce, the prevalence of breast cancer among men, and early diagnoses and treatments for breast cancer.

BackgroundUnmet need for family planning is high (30%) in Ghana. Reducing unmet need for family planning will reduce the high levels of unintended pregnancies, unsafe abortions, maternal and neonatal morbidity and mortality. The purpose of this study was to examine factors that are associated with unmet need for family planning to help scale up the uptake of family planning services in Ghana.MethodsThis cross sectional descriptive and inferential study involved secondary data analysis of women in the reproductive age (15–49 years) from the Ghana Demographic and Health Survey 2014 data. The outcome variable was unmet need for family planning which was categorized into three as no unmet need, unmet need for limiting and unmet need for spacing. Chi-squared test statistic and bivariate multilevel multinomial mixed effects logistic regression model were used to determine significant variables which were included for the multivariable multilevel multinomial mixed effects logistic regression model. All significant variables (p < 0.05) based on the bivariate analysis were included in the multinomial mixed effects logistic regression model via model building approach.ResultsWomen who fear contraceptive side effects were about 2.94 (95% CI, 2.28, 3.80) and 2.58 (95% CI, 2.05, 3.24) times more likely to have an unmet need for limiting and spacing respectively compared to those who do not fear side effects. Respondents’ age was a very significant predictor of unmet need for family planning. There was very high predictive probability among 45–49 year group (0.86) compared to the 15–19 year group (0.02) for limiting. The marginal predictive probability for spacing changed significantly from 0.74 to 0.04 as age changed from 15 to 19 to 45–49 years. Infrequent sexual intercourse, opposition from partners, socio-economic (wealth index, respondents educational level, respondents and partner’s occupation) and cultural (religion and ethnicity) were all significant determinants of both unmet need for limiting and spacing.ConclusionsThis study reveals that fear of side effect, infrequent sex, age, ethnicity, partner’s education and region were the most highly significant predictors of both limiting and spacing. These factors must be considered in trying to meet the unmet need for family planning.Electronic supplementary materialThe online version of this article (10.1186/s13690-019-0340-6) contains supplementary material, which is available to authorized users.

In this paper, we introduce a new univariate version of the Lomax model as well as a simple type copula-based construction via Morgenstern family and via Clayton copula for introducing a new bivariate and a multivariate type extension of the new model. The new density has a strong physical interpretation and can be a symmetric function and unimodal with a heavy tail with positive skewness. The new failure rate function can be “upside-down”, “decreasing” with many different shapes and “decreasing-constant”. Some mathematical and statistical properties of the new model are derived. The model parameters are estimated using different estimation methods. For comparing the estimation methods, Markov Chain Monte Carlo (MCMC) simulations are performed. The applicability of the new model is illustrated via four real data applications, these data sets are symmetric and right skewed. We constructed a modified Chi-Square goodness-of-fit test based on Nikulin-Rao-Robson test in the case of complete and censored sample for the new model. Different simulation studies are performed along applications on real data for validation propose.

In this paper, constant stress accelerated life tests are discussed based on Type I and Type II censored sampling data from Kumaraswmay Weibull distribution. The maximum likelihood estimators are derived for the unknown parameters. The log linear model is assumed as an accelerated model. In addition, confidence intervals for the model parameters are constructed. Optimum test plans, are developed to minimize the generalized asymptotic variance of the maximum likelihood estimators of the model parameters. Monte Carlo simulation is carried out to illustrate the theoretical results of the maximum likelihood estimates, confidence intervals and optimum test plans.

One of the most important asymmetrical probability distributions that recently presented as an extension of the conventional exponential distribution is the alpha power exponential distribution. It may be compared to various asymmetrical well-known models, such as Weibull and gamma distributions. As a result, using an adaptive progressive Type-II hybrid censoring scheme, this paper investigates the estimation problems of the alpha power exponential distribution. Maximum likelihood and Bayesian methods are used to estimate unknown parameters, reliability, and hazard rate functions. Under the assumption of independent gamma priors and symmetric loss function, Bayesian estimators are examined. The Bayesian credible intervals and estimated confidence intervals of the relevant values are also calculated. The various estimating approaches are evaluated using a simulation study that considers various sample sizes and censoring schemes. Furthermore, numerous optimality criteria are examined, and the best progressive censoring schemes are offered. Finally, for an explanation, two real data sets from engineering and chemical fields are provided to show the applicability of the asymmetrical alpha power exponential distribution. The Bayesian method for estimating the parameters and reliability indices of the alpha power exponential distribution is recommended based on numerical results, especially when the number of observed data is small.

Background There is high rate of under-five mortality in West Africa with little effort made to study determinants that significantly increase or decrease its risk across the West African sub-region. This is important since it will help in the design of effective intervention programs for each country or the entire region. The overall objective of this research evaluates the determinants of under-five mortality prior to the end of the 2015 Millennium Development Goals, to guide West African countries implement strategies that will aid them achieve the Sustainable Development Goal 3 by 2030. Method This study used the Demographic and Health Survey (DHS) data from twelve (12) out of the eighteen West African countries; Ghana, Benin, Cote d’ Ivoire, Guinea, Liberia, Mali, Niger, Nigeria, Sierra Leone, Burkina Faso, Gambia and Togo. Data were extracted from the children and women of reproductive age files as provided in the DHS report. The response or outcome variable of interest is under-five mortality rate. A Bayesian exponential, Weibull and Gompertz regression models via a gamma shared frailty model were used for the analysis. The deviance information criteria and Bayes factors were used to discriminate between models. These analyses were carried out using Stata version 15 software. Results The study recorded 101 (95% CI: 98.6–103.5) deaths per 1000 live births occurring among the twelve countries. Burkina Faso (124.4), Cote D’lvoire (110.1), Guinea (116.4), Nigeria (120.6) and Niger (118.3) recorded the highest child under-5 mortality rate. Gambia (48.1), Ghana (60.1) and Benin (70.4) recorded the least unde-5 mortality rate per 1000 livebirths. Multiple birth children were about two times more likely to die compared to singleton birth, in all except Gambia, Nigeria and Sierra Leone. We observed significantly higher hazard rates for male compared to female children in the combined data analysis (HR: 1.14, 95% CI: [1.10–1.18]). The country specific analysis in Benin, Cote D’lvoire, Guinea, Liberia, Mali and Nigeria showed higher under-5 mortality hazard rates among male children compared to female children whilst Niger was the only country to report significantly lower hazard rate of males compared to females. Conclusion There is still quite a substantial amount of work to be done in order to meet the Sustainable Development Goal 3 in 2030 in West Africa. There exist variant differences among some of the countries with respect to mortality rates and determinants which require different interventions and policy decisions.

This paper is an effort to propose a new method to generate probability distributions based on alpha power transformation method for more flexibility. We refer to the new method as modified alpha power transformed method. The new proposed method can be considered as a weighted version of the alpha power transformation method with more ability to model various types of data. A special case has been studied in detail namely; one parameter exponential distribution. The new generalization of the traditional exponential distribution provides a better fit than the exponential distribution and some competitive models. It appears to be a distribution capable of allowing constant, decreasing and increasing hazard rates based on its parameters. Various properties of the new method as well as the new distribution are derived, including explicit expressions for the quantiles, moments, moment generating function and expression of entropies. The point and interval estimations are investigated using maximum likelihood method. A simulation study is carried out and two applications, one for COVID-19 data and the other for software reliability data are considered to show the flexibility of the proposed distribution. The results show that the new distribution provides a better fit than some other competitive distributions including exponential, alpha power exponential, Weibull and gamma distributions.