Factors to Consider in Midwifery Care during Climacteric and Monopause Period

This study discusses the management of climacteric obstetrics and menopause. Menopause is the final feminine cycle or when the final monthly cycle happens, one of the mental viewpoints of changing self-concept amid menopause is unquestionably menopausal ladies ended up on edge around their bodies and frame self-concept approximately how their bodies are. The side effects experienced by ladies some time recently menopause cause the mother to be ill-equipped approximately physical and mental changes. To decrease this, ladies must get ready themselves both physically and mentally for menopause. Ladies who are going through menopause go through the primary stages counting premenopause, perimenopause, menopause, and postmenopause, and menopause for the most part happens in ladies matured 45-50 a long time.

Statistical Analysis of the Risk Factors of Myocardial Infarction in Pakistan Using Logistic Regression and Neural Network

Heart attack is a life threatening disease and its prevalence in Pakistan is 6.2%. Pakistan comprises of four provinces and its estimated population is over 190 million. Relevant literature about the MI occurrence and its epidemiology has established that both are regionspecific. A reasonable research literature about the risk factors of heart diseases exists in advanced countries, but the same is not true for an emerging state like Pakistan. Additionally, its cure necessitates extraordinary expenditures. Pakistan being the rising country is struggling to encounter this contest with insufficient resources nevertheless with tiny achievement. This work offers a compact procedure of research work in which presentation of statistical / parametric (binary LR) along with non-parametric (the ANN model) methods are used to an epidemiological research. On the contrary, this work demonstrates an instance of how the logistic regression & neural network modeling methods can be applied to investigate the etiologies & risk factors for an MI. Prior to the construction of the multiple logistic regression, simple regression analysis is performed and only the independent variables holding p-value < 0.2 are selected for the ultimate inclusion to the Multiple Logistic Regression model. Outlier’s detection, autocorrelation examination and multicollinearity Identification are performed in advance. On the other hand the neural network model is run with all the collected data for comparison of results to the LR model. On relating the outcomes from both the methods, 16 variables are significantly linked to heart attack. It is possibly established that a harmonious group of etiologies & risk factors, from both logistic regression and neural networks is recognized which indicates that ANN is a powerful alternative technique to recognize etiologies & risk factors for heart attack in Pakistan. Generally, both models performed at equal level. In all the models chest pain remained the most significant variable proving that it is the most alarming etiology / symptom of a heart attack in our country. The risk factors found significant in both male and female models are; chest pain, family history, obesity, cholesterol level, smoking, physical activity, hypertension, diabetes mellitus, breathing problem, less intake of fish, psychosocial factors, & easily angered. Similarly, on provincial classification of data, and on comparison, the variables gender, living environment, marital status, ethnicity, sleeping duration, obesity, tobacco use, life style and hypertension are not the same (differ significantly) in all the four provinces and vary from one province to other. In short, it is certified in the study that certain probable etiologies & risk factors belong to eating habits, psychological activities, family history, medical history and socioeconomic status of the cases. But most of the variables are associated to case’s medical history which expose that these factors are leading to myocardial infarction in the country. Analysis is performed using SPSS version 19 & AMOS version 18 at Aksaray University, Turkey.