Consumption pdf

Consequ- also showed no association between egg consumption ently, egg is an indispensable part of a slimming diets and CHD risk. This result, however, was not - ced by the beneficial effects of its other beneficial con- obtained in the second longer term analysis. Bieng cheap al- incidence in the joint analysis of the Nurses' Health so leads to increased consumption. Despite its choleste- Study with a year follow-up period and the Health rol-increasing effect it is also considered to be protecti- Professionals Follow-up Study involving Lack of any association bet- pretation by many of our colleagues suggesting that egg ween egg consumption and CHD risk in these studies was not harmful, that it insignificantly increased blood led to an impression suggesting that there was generally cholesterol level, and that patients with heart diseases no link between egg consumption and heart diseases.

In , an unfavorable data was added to this con- On the other hand, it is suggested that the increased troversial topic. Si- Despite these data on dietary cholesterol and LDL- milar results from the relationship between egg con- C levels, the effect of egg consumption on the develop- sumption and HF were also obtained in individuals ment of cardiovascular events has not been adequately with previous myocardial infarction MI.

Another The English version of this article is prepared for online access only. Fernandez ML. Dietary cholesterol provided by eggs and monstrated no association between egg consumption and plasma lipoproteins in healthy populations. Shekelle RB, Stamler J. Dietary cholesterol and ischae- od from to Lancet ; The diet and all-causes death rate in the Seven Countries consumption. Lipids and lipoproteins as a year follow-up period found that the levels of total predictors of coronary heart disease, stroke, and cancer in cholesterol was directly proportional to egg consumpti- the Honolulu Heart Program.

Am J Med ; Although significant results were not obtained from 5. Stamler J, Shekelle R. Dietary cholesterol and human co- the male subjects in the study, mortality rate due to ische- ronary heart disease. The epidemiologic evidence. Arch mic heart disease and all-cause mortality rate were obser- Pathol Lab Med ; Dietary guidelines for healthy lity due to heart diseases was divided into 5 groups inclu- American adults.

Circulation ; Keys A, Parlin RW. Serum cholesterol response to chan- all-cause mortality rate was Am J Clin Nutr ; Dietary lipids and blood cholesterol: quantitative meta-analysis In consideration of all results of the studies on the of metabolic ward studies. BMJ ; Hopkins PN. Effects of dietary cholesterol on serum cho- Association and NCEP Guidelines recommend limiting lesterol: a meta-analysis and review.

Am J Clin Nutr average daily dietary cholesterol intake to less than ; Men classified as hypo- or The situation would clearly be understood given the fact hyperresponders to dietary cholesterol feeding exhibit that an average egg yolk also contains at least differences in lipoprotein metabolism. Indeed, any physician who is in- ; However, it is reasonable Samonds KW, et al. Ingestion of egg raises plasma low to recommend limiting average daily dietary cholesterol density lipoproteins in free-living subjects.

The English version of this article is prepared for online access only. Egg consumption and cardiovascular health Effects of shrimp consump- rum cholesterol, and coronary heart disease. Am J Clin tion on plasma lipoproteins. Am J Clin Nutr ; Nutr ; Dietary choleste- La Vecchia C. Association between certain foods and rol from eggs increases the ratio of total cholesterol to risk of acute myocardial infarction in women.

BMJ high-density lipoprotein cholesterol in humans: a meta- ; Fraser GE. Diet and coronary heart disease: beyond die- J Am Coll Cardiol sumption and risk of cardiovascular disease in men and women. JAMA ; Egg consumption and risk of he- The main objective of this study is to determine the factors those affect household food expenditure. DATA AND METHODS This deals with detailed description about study area, source of data, study population, sampling technique, study variables, sample size determination and study design explanation about the theory behind the methods of and models for the analysis.

Sheka is bordered on the south by Bench-Maji, on the west by the Gambela Region, on the north by the Oromiya Region, and on the east by Kaffa. Our target population for this study is households who live in Tepi Town in Andenet Kebele.

For this study, we use simple random sampling techniques by selecting appropriate sampling size from the population in Tepi town in case of Andenet Kebele.

The goal is to include sufficient numbers of subjects so that statistically significant results can be detected. In this study, researcher collected the data from the households directly in a particular time primary data.

Here are some explanatory variables with their categories that affect household average monthly food expenditure. Therefore, the independent variables included in this study were list out below Table 1. In descriptive statistics the statistician tries to describe a situation. Once data is collected, the researcher must organize and summarize them. Finally, the researcher needs presenting the data in some meaningful form, such as charts, graphs, or tables.

Multiple Linear Regression Model Multiple linear regression models are used to model the relationship between a single dependent variable response variable and more than one independent variable. Multiple linear regression is required so that the dependent variable to be continuous and the independent variable to be discrete, continuous and categorical.

In the model of multiple linear regressions, response variable is a linear function of the k explanatory variables and of a statistical error term. The model also has an intercept. The ordinary least square estimation can be work as after a certain procedures. Autocorrelation occurs when the residuals are not independent from each other. It occurs when several independent variables correlate at high levels with one another. Hypothesis Testing for ANOVA Adequacy of the model in multiple linear regressions can be checked by testing the regression coefficient associated with the independent variable.

The explanatory variables corresponding to such regression coefficients are important for the model. Rejecting the null hypothesis implies that ith independent variable has statistically significant contribution to the model. Step 5: Make conclusion 2. In this study, descriptive analysis and multiple regression analysis were employed to identify the risk factors.

Data analysis was presented in this study based on a total of households. The descriptive statistics revealed that the households spend on food with minimum of and maximum of birr while, the mean of household for food expenditure was Table 2. The present or absent of auto correlation checked by Durbin Watson test DW. From Table 2. Durbin Watson test is equal to 1. Durbin Watson test revealed that absence of autocorrelation for the assumption of multiple linear regressions.

Errors must be uncorrelated. Error of the Estimate Durbin-Watson. Based on the analysis of variance tables we have to test the overall test of the regression model. The overall model is statistically significance for the data.

Regression 1. Error t-test Sig. The number of family dependents has a positive effect on the food expenditure per monthly. The amount of family expenditure is also quite influencing household consumption where the more the number of house members is borne in one household, and then the burden of poor households will be heavier because there are more and less productive members.

This can be understood because more family members are increasing the household expenditure, especially for the daily needs of each individual in the family. There is difference in food expenditure per month individual who had single marital status being significant affected.

Income per month has a positive effect on the expenditure of households in study area. This shows greater income for households, so the ability to consume is greater so that the opportunity to prosper the household is also greater. After fitted the model one important point to keep in mind is that these assumptions are for the population and we work only with a sample. So the main issue is to take a decision about the population on the basis of a sample of data. Several diagnostic methods to check the violation of regression assumption are based on the study of model residuals with the help of various types of graphics.

Normality assumption usually checked by histogram. Fig 1 displayed that the residual of the average mark students was normally distribution with mean 0 and variance 1 dependent variable normally and independently distribution with mean 8. As result of the normality was satisfied. Data satisfied normality assumption see Fig 1.

From Fig 2 plots were random scatter of points it is not in systematic pattern. This shows that the standardized residual are uncorrelated with the fitted value.

Therefore, the plot is random or non-systematic pattern there is no problem constant variance in the model see Fig. Table 5 summarized that there is absence of Multicolinearity. VIF for each continuous predictor variables were less than 10 see Table 5. Model is good fitted. A total of households were included in the present study using simple random sampling technique from the Andenet Kebele. Descriptive statistics revealed that the households spend on food per monthly with minimum of and maximum of birr while, the mean of household for food expenditure was However, age, occupation, religion, mother education level, father education level, is there high price of food, reason for high price change and decision making were not found to be significant effect to household food expenditure per monthly at study area see Table 4.

The overall model is statistically significance for the data see Table 3. Normality, Constant variance, absence of Multicolinearity, linearity and absence of autocorrelation were satisfied due to formal tests and diagnostic plots see Fig 1.

Fig 2. Table 5. Study recommend that government of Ethiopia especially Tepi Town should design and implement policies that raise disposable income of households so that households work to earn more money and make their living standard better. It is advisable for households to improve their income level per month by involving in various different activities that help them generate additional income. Wambua, K. Omoke, and T. Pahlevi, D. Andita, E. Gumilar, F. Nursafitri, and S.

Town and A. Mubarak, A. Khalifah, A. Mandela, and A. Iram and M. Wigraiphat, V. Limsombunchai, and T. Ahmed, L. Ying, M. Bashir, M. Abid, and F.

Dula and W. Joshi and N. Ishdorj, C. Iii, and J. Food Econ. Marnisah, A. Karim, A. Sanmorino, and T.