Heart disease is the leading cause of death among Filipinos, accounting for 1 out of every 5 deaths in the past year. Each year, 170,000 Filipinos die from cardiovascular diseases, up from 85,000 more than 20 y ago. This paper aims to estimate the risk of developing Heart Attack using Survival Analysis. The data were obtained from the records of Quirino Memorial Medical Center with a total of 447 observations. The data includes the time t (patient's age), gender of the patient, covariates such as lifestyle (smoking and drinking alcohol); health conditions (Hypertension, Diabetes, Highdensity Lipoprotein (HDL) and Low-density Lipoprotein (LDL) level); and family history of Cardiovascular Disease, and the event of interest which is the occurrence of heart attack. The researchers applied two main statistical treatments in examining the data: (1) Cox Regression in formulating a model to estimate the risk of heart attack based on the given covariates; (2) Kaplan-Meier Estimates in calculating the probability of each patient to survive in accordance to their gender depending on the covariates the patients have. Results showed that females have more risks of developing heart attack than males for patients with hypertension, with diabetes, with a family history of CVD, and those who are smoking. However, for patients who are alcoholic, men are more prone to the risk of heart attack than women. The results were obtained with the help of SPSS.
This study aims to formulate a mathematical model for forecasting and estimating unemployment rate in the Philippines. Also, factors which can predict the unemployment is to be determined among the considered variables namely Labor Force Rate, Population, Inflation Rate, Gross Domestic Product, and Gross National Income. Granger-causal relationship and integration among the dependent and independent variables are also examined using Pairwise Granger-causality test and Johansen Cointegration Test. The data used were acquired from the Philippine Statistics Authority, National Statistics Office, and Bangko Sentral ng Pilipinas. Following the Box-Jenkins method, the formulated model for forecasting the unemployment rate is SARIMA (6, 1, 5) × (0, 1, 1)4 with a coefficient of determination of 0.79. The actual values are 99 percent identical to the predicted values obtained through the model, and are 72 percent closely relative to the forecasted ones. According to the results of the regression analysis, Labor Force Rate and Population are the significant factors of unemployment rate. Among the independent variables, Population, GDP, and GNI showed to have a granger-causal relationship with unemployment. It is also found that there are at least four cointegrating relations between the dependent and independent variables.
This study focuses on minimization of food cost that satisfies the daily nutrients required based on 2000-calorie diet for a diabetic person. This paper attempts to provide a food combination that satisfies the daily nutrient requirements of a diabetic person and its lowest possible dietary food cost. A linear programming diet model is used to determine the cheapest combination of food items that satisfy the recommended daily nutritional requirements of the diabetic persons. According to the findings, a 50 year old and above diabetic male need to spend a minimum of 72.22 pesos for foods that satisfy the daily nutrients they need. In order to attain the minimum spending, the foods must consist of 60.49 grams of anchovy, 91.24 grams of carrot, 121.92 grams of durian, 121.41 grams of chicken egg, 70.82 grams of pork (lean), and 369.70 grams of rice (well-milled). For a 50 year old and above diabetic female, the minimum spending is 64.65 pesos per day and the food must consist of 75.87 grams of anchovy, 43.38 grams of carrot, 160.46 grams of durian, 69.66 grams of chicken egg, 23.16 grams of pork (lean) and 416.19 grams of rice (well-milled).
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