tiểu luận kinh tế lượng ECONOMETRICS REPORT

FOREIGN TRADE UNIVERSITY FACULTY OF INTERNATIONAL ECONOMICS -  - ECONOMETRICS REPORT Class: KTEE218.1 GROUP 11 Name Đàm Thanh Bình Students’ ID 1814450016 Thái Mỹ Hạnh 1814450038 Phạm Khắc Dương 1814450025 Nguyễn Thị Hằng 1814450106 Đoàn Thanh Tùng 1814450072 Lecturer: MSc Quynh Thuy Nguyen Hanoi, 26th September 2019 TABLE OF CONTENTS ABSTRACT INTRODUCTION Research objective 2 Rationale of study Object and scope of study 4 Structure of scope SECTION I: OVERVIEW OF THE TOPIC General definitions and economic theories 1.1 General definitions 1.2 Economic theories related to the research Literature view 2.1 Related published researches 2.2 Research hypotheses 10 2.3 BMR 10 2.4 Calories Expenditure of Exercise 11 2.5 Calories expenditure of Common Foods 12 SECTION II: MODEL SPECIFICATION 14 Methodology 14 1.1 Method you use to derive the model 14 Theoretical model specification 15 2.1 Specification of the model 15 2.2 Describe the data 19 SECTION III: ESTIMATED MODEL and statistical inferences 22 Estimated model: 22 1.1Estimation result: 22 1.2 Sample regression model (SRM) 22 1.3Explain the meanings of estimated coefficients 23 1.4 The coefficient of determination 24 Hypothesis Testing 24 2.1 Testing the significance of an individual regression coefficient βj 24 2.2 The confidence interval approach 25 2.3 The T-distribution approach 25 The P-value approach 26 Testing the overall significance 27 4.1 The F-test of significance approach 27 4.2 The P-value approach 27 Conclusion: 28 REFERENCES 30 INDIVIDUAL ASSESSMENT 31 ABSTRACT In the last a few decades, BMI index has been becoming one of the growing concerns all over the world, especially to the health conscious as well as health public researchers BMI is a measurement of a person's leanness or corpulence based on their height and weight, and is intended to quantify tissue mass It is widely used as a general indicator of whether a person has a healthy body weight for their height Specifically, the value obtained from the calculation of BMI is used to categorize whether a person is underweight, normal weight, overweight, or obese depending on what range the value falls between This is the World Health Organization's (WHO) recommended body weight based on BMI values for adults It is used for both men and women, age 18 or older This provides the answer to our question why BMI is one of the most reliable index reflecting the recent health situation BMI plays a crucial role in analyzing the status of well-being, measuring the risk of hazardous diseases resulting from overweight like obesity, cardiovascular diseases, high blood pressure or from underweight like malnutrition, vitamin deficiencies, etc However, in reality, to achieve an ideal BMI index, we have to pay more attention to a number of factors directly affecting it, namely nutritious intake in each portion, daily eating habit, average workout hours, sex, age, etc So in this study we will gain deeper insight into the primary factors affecting BMI index and shed light on the optimal approaches to reach standardized BMI, improve the general public well-being We would like to give our appreciation to your useful lectures of this course and instruction to fulfill this report Throughout process of making this report, our team did try our best to gather data, conduct researches and utilize available materials to analyze the result However, mistakes are inevitable Therefore, please let us know if there are some ones that must be fixed to achieve more accurate result INTRODUCTION Research objective The main purposes of this study is to provide thorough understanding of BMI index, and analyze fundamental elements contributing to fluctuation of BMI ranging from nutritious regime, eating habit to workout routine To be more specific, it also supplies data about every single substance in daily diets, frequency and the typical amount of calorie burned in exercising, the number and rational distribution of daily meals This study also enables people to foresee the positive or negative trend of BMI in the future, gives recommendations for them to propose long-term plan for the sustainable development of public health Rationale of study There are a few motivations prompting us to this research: - The lifestyle in the modern societies pose various threats to our health, particularly for youngster The consumption of junk food has been considerably increasing year by year Besides, the rate of children as well as adults becoming obese is so alarming, which has been linked to a lack of physical exercises On the contrary, in the most remote areas, many families have to struggle to feed themselves so malnutrition is a very common tendency The underweight and overweight is associated with a plenty of dangerous diseases for health: - Being overweight increases the risk of a number of serious diseases and health conditions Below is a list of said risks, according to the Centers for Disease Control and Prevention (CDC): • High blood pressure • Higher levels of LDL cholesterol, which is widely considered "bad cholesterol," lower levels of HDL cholesterol, considered to be good cholesterol in moderation, and high levels of triglycerides • Type II diabetes • Coronary heart disease • Stroke • Gallbladder disease • Osteoarthritis, a type of joint disease caused by breakdown of joint cartilage • Sleep apnea and breathing problems • Certain cancers (endometrial, breast, colon, kidney, gallbladder, liver) • Low quality of life • Mental illnesses such as clinical depression, anxiety, and others • Body pains and difficulty with certain physical functions • Generally, an increased risk of mortality compared to those with a healthy BMI - Being underweight has its own associated risks, listed below: • Malnutrition, vitamin deficiencies, anemia (lowered ability to carry blood vessels) • Osteoporosis, a disease that causes bone weakness, increasing the risk of breaking a bone • A decrease in immune function • Growth and development issues, particularly in children and teenagers • Possible reproductive issues for women due to hormonal imbalances that can disrupt the menstrual cycle Underweight women also have a higher chance of miscarriage in the first trimester • Potential complications as a result of surgery • Generally, an increased risk of mortality compared to those with a healthy BMI Therefore, more attention should be placed on and more investigation should be conducted on a regular basis to get deep understanding of primary elements having influences on BMI index From those data and results of this paper, a specific plan can be set up to regulate the amount of nutrition intake, time for exercise and outdoors activities, which can help control weight, height and lead a healthier lifestyle 3 Object and scope of study In this study, we will concentrate on young people at ages ranging from 18 to 22 both female and male These are the most adequate and ideal ages to get variables directly affecting BMI as well as the most accurate consequences A range of research methodologies was used to investigate current practice and to capture data about the scope and fundamental contributors in BMI index Using a software Stata used for statistical analysis; descriptive statistics and summary methods to analyze the information from the survey Structure of scope The report has been structured to reflect the different research goals for the project This report is organized as follows: Sections I will overview definitions Section II will explore methodology of study: Factors that affect BMI index and analyze dependent and independent variables in the OLS model Section III will explain result we get from the Stata and test initial hypotheses Finally, give some recommendations and effective way to positively alter daily diets and workout routine, improving the state of well-being and reaching an ideal BMI SECTION I: OVERVIEW OF THE TOPIC General definitions and economic theories 1.1 General definitions 1.1.1 Definition and formula of BMI a Definition of BMI - The BMI formula uses your weight (in kg or pounds) and your height (in meters or inches) to form a simple calculation that provides a measure of your body fat The formula for BMI was devised in the 1830s by Belgian mathematician Adolphe Quetelet and is universally expressed in kg/m2 - Body mass index is a measure of body fat and is commonly used within the health industry to determine whether your weight is healthy BMI applies to both adult men and women and is the calculation of body weight in relation to height This article delves into the BMI formula and demonstrates how you can use it to calculate your own BMI b Formula of BMI The first formula we've listed is the metric BMI formula, using kilograms and meters The second one is the imperial BMI formula, which uses units of pounds and inches • Metric BMI Formula: BMI = ℎ ( [ℎ • Imperial BMI Formula: ) ℎ ( )]2 ℎ ( ) BMI = 703 × [ℎ ℎ ( )]2 1.1.2 BMI categorization The BMI statistical categories below are based on BMI scores and apply to adults of age 20 years and upwards The World Health Organisation (WHO) regards a healthy adult BMI to be between 18.5 and 25 BMI BMI Category Less than 15 Very severely underweight Between 15 and 16 Severely underweight Between 16 and 18.5 Underweight Between 18.5 and 25 Normal (healthy weight) Between 25 and 30 Overweight Between 30 and 35 Moderately obese Between 35 and 40 Severely obese Over 40 Very severely obese Table 1.1.3 Current problems around BMI It is a common argument that the results the BMI formula provides are too general and not consider the gender, build, age or ethnicity of a person For example, professional athletes are often considered overweight or obese when using BMI measurements due to their muscle content, which weighs more than fat Similarly, as people age their bone density decreases So, although they may seem to have a weight within the normal BMI range, their measurement actually needs to be scaled-down to reflect this In a study published in the Journal of Economics in 2008, John Cawley, professor at Cornell University, was able to demonstrate that, relative to percent body fat, BMI appears to misclassify substantial fractions of individuals as obese or non-obese 1.2 Economic theories related to the research a The three-variable model • Population regression function: E (Y X2i, X3i) = β1 + β2X2i + β3X3i • Stochastic form Yi = β1 + β2X2i + β3X3i + ui Where: Y: dependent variable X2, X3: independent variables β 1: intercept term β 2, β 3: partial regression coefficients ui: disturbance • The meaning of partial regression coefficients - β measures the change in the conditional mean value of Y, E(Y X2i, X3i), per unit change in X2, holding the value of X3 constant β2= - If we increase X2 by one unit and keep other variables constant, the expected value of Y increase by β2 units - Similarly, β3 measures the change in the mean value of Y, E(Y), per unit change in X3, holding the value of X2 constant β3= b Coefficient of determination R and the adjusted R2 • The multiple coefficient of determination R2 The extent to which all the independent variables jointly (i.e., the model) explain the variation in the dependent variable 2 ∑ R = =1- =1- =1 ∑ =1 • Problems with R2 2.2 The confidence interval approach According to the results from Stata using the Ordinary Least Squares regression analysis method, we obtained the confidence interval for the regression coefficients of each variable at a significance level of 5% as below: For the variable Eht, the value of belongs to the confidence interval [−0.0570135, 1.594981], which means we don’t have enough evidence to reject H0 Therefore, the regression coefficient of Eht isn’t statistically significant at a significance level of 5% For the remain variables, which are Ag, Gdr, Avgcalo, Rarcnca and constant, the value of doesn’t belong to the confidence interval of each variable Therefore, the regression coefficients of these variables are statistically significant at a significance level of 5% 2.3 The T-distribution approach Specify the critical T-value tc = = = 1,984 n = 150: the number of observations or sample size /2 − 0.025 144 k = 6: the number of variables α = 0.05: the significant level, for two-tailed test, ⁄2 = 0.025 ̂  According to the test statistic= of each variable at the −0 ̂ ( ) significance level of 5%, we have: - For the Ag: | | = 2.66 > 1.984, we can reject H0; therefore, the regression coefficient of Ag is statistically significant at a significance level of 5% - For the Gdr: |ts| = 5.73 > 1.984, we can reject H0; therefore, the regression coefficient of Gdr is statistically significant at a significance level of 5% - For the Eht: |ts| = 1.84 < 1.984, we don’t have evidence to reject H0; therefore, the regression coefficient of Eht isn’t statistically significant at a significance level of 5% 25 - For the Avgcalo : |ts| = 3.67 > 1.984, we can reject H0; therefore, the regression coefficient of Avgcalo is statistically significant at a significance level of 5% - For the Rarcnca: |ts| = 3.83 > 1.984, we can reject H0; therefore, the regression coefficient of Rarcnca is statistically significant at a significance level of 5% - For the variable constant: |ts| = 0.79 < 1.984, we don’t have evidence to reject H0; therefore, the regression coefficient of constant isn’t statistically significant at a significance level of 5% The P-value approach The P-value (probability value) is the lowest significance level at which the Null Hypothesis H0 can be reject We have: Level of α significant of model (α) equals to 5% This hypothesis is two-tail test => Therefore the factor is statistically significant if it has P-value smaller than 5% or 0.05 - For the variable Ag, its P-value is approximately equal to 0.002, which is smaller than 0.05 - For the variables Eht, its P-value is approximately equal to 0.068, which is more than 0.05 - For the variables constant, its P-value are approximately equal to 0.432, which is more than 0.05 - For the variable Gdr, Avgcalo, Rarcnca, their P-value is approximately equal to 0.000, which are smaller than 0.05 In conclusion, by approaching three methods to test the significance of individual regression coefficients, we can conclude that the regression coefficients of Ag, Gdr, Avgcalo, Rarcnca are statistically significant 26 Testing the overall significance State the Hypotheses: 0: { 1= 2= 3= 4= 5=0 : (equal { =0 ) : + 2 + + + ≠0 : ≠0 4.1 The F-test of significance approach The F-test of overall significance indicates whether your linear regression model provides a better fit to the data than a model that contains no explanatory variables Specify the critical F-value Fc= = = 2.3 n: the number of observations or sample size, n = 150 − −1 144 k: the number of variables, k = Calculate the test statistic = ( − ) = 0.3474×(150−6) = 15.33 > (6−1)(1−0.3474) ( −1)(1− ) 2.3 => From the result of , we can reject null hypotheses Therefore, the overal model is statistically significant at the level of significance of 5% 4.2 The P-value approach According to the result obtained from the OLS regression analysis by Stata, we have the P-value that P (Fs > Fc) = 0.000 < 0.05 As a result, we can reject H0 and conclude that the overall model is statistically significance at a significance level of 5% In conclusion, by approaching two methods to test the significance of the whole model, we can conclude that the overall model is statistically fitted at a significance level of 5% 27 CONCLUSION: By analyzing data, running the model and conducting tests, overcoming the phenomena of the model, we can summarize the following key issues: Sample Regression Model: ̂ = -3.09 + 0.35.Ag + 2.44.Gdr + 0.77.Eth + 0.0034.Avgcalo + 7.42.Rarcnca Or: ̂ = − 3.09 + 0.35 × + 2.44 × + 0.77 × + 0.0034 × + 7.42 × Thus, the above steps helped to answer the question raised in the Research Hypothesis: Are the factors such as Age, Gender, Eating habit, Average calories burned per day and Rate of absorbed calories over necessary calories influenced more or less on the BMI of 18-22 years old people? And how does it affect? The variable “Avgcalo” has the strongest relationship and the variable “Gdr” has the weakest relationship with the dependent variable “BMI” This shows that people who burn more calories through activities like playing sports, doing workout or hand-working seem to have a better BMI than people with less working out Possibly, they are so busy with the office work with hour and hour of sitting in front of the screen and not have time for doing outside exercise In contrast, people’s gender or genetic factors has low effect on their BMI As a student studying in Foreign Trade University, we should know how important the BMI is in our body development We not only need to have smart brains but we also need a good BMI means a healthy and balance bodies After this research, we have some recommendations for you, me, our families, friends and relatives to have good BMI We all know that exercise is an essential part in our daily lives, but we may not know why or what exercise can for us There is no doubt that having a regular exercising routine brings us a healthy and balanced lifestyle It’s important to remember that we have evolved from nomadic ancestors who spent all their time moving around in search of food and shelter, travelling large 28 distances on a daily basis Our bodies are designed and have evolved to be regularly active There are many benefits of regular exercise and maintaining fitness and these include: + First of all, exercise increases your energy levels Exercise improves both the strength and the efficiency of your cardiovascular system to get the oxygen and nutrients to your muscles When your cardiovascular system works better everything seems easier and you have more energy for the fun stuff in life + Secondly, regular exercise improves muscle strength Staying active keeps muscles strong and joints, tendons and ligaments flexible, allowing you to move more easily and avoid injury Strong muscles and ligaments reduce your risk of joint and lower back pain by keeping joints in proper alignment They also improve coordination and balance + Thirdly, exercise can help you to maintain a healthy weight The more you exercise, the more calories you burn In addition, the more muscle you develop, the higher your metabolic rate becomes, so you burn more calories even when you’re not exercising + Last but not least, Exercise improves a good brain function Exercise increases blood flow and oxygen levels in the brain It also encourages the release of the brain chemicals (hormones) that are responsible for the production of cells in the hippocampus, the part of the brain that controls memory and learning This, in turn, boosts concentration levels and cognitive ability, and helps reduce the risk of cognitive degenerative diseases such as Alzheimer’s  Therefore, each of us should build our own consistent and feasible exercise routine to control an ideal BMI Due to the length of the essay and the limited time it takes, our team only came up with a few solutions as above Over all, we hopes to present more detailed solutions for improving BMI and introduce more knowledge about the understanding of having a good exercising routine significantly reflect our health in a remarkable way 29 REFERENCES http://www.z-table.com/ https://www.healthline.com/nutrition/how-many-calories-per-day https://humansofdata.atlan.com/2018/09/qualitative-quantitative-dataanalysis-methods/ https://www.bigskyassociates.com/blog/bid/356764/5-Most-ImportantMethods-For-Statistical-Data-Analysis https://www.wikihow.com/Calculate-Calories-Burned-in-a-Day https://data.worldbank.org/country/vietnam https://www.omnicalculator.com/health/bmr https://www.cdc.gov/nccdphp/dnpao/growthcharts/training/bmiage/page5_1.h tml https://www.princeton.edu/~otorres/Regression101.pdf 10 https://www.wikihow.com/Calculate-Food-Calories 11 https://www.businessinsider.com/how-to-calculate-calories-burnedexercise-met-value-2017-8 12 WHO - BMI classification 13 Ogden CL, Fryar CD, Carroll MD, Flegal KM Mean bodyweight, height, and body mass index, United States 1960Y2002.Adv Data 14 Troiano RP, Frongillo EA Jr, Sobal J, Levitsky DA The rela-tionship between body weight and mortality: a quantitativeanalysis of combined information from existing studies Int JObes Relat Metab Disord 15 Larsson I, Lindroos AK, Peltonen M, Sjostrom L Potassium perkilogram fatfree mass and total body potassium: predictionsfrom sex, age, and anthropometry Am J Physiol EndocrinolMetab 30 INDIVIDUAL ASSESSMENT Thanh Tung Thanh Binh Nguyen Hang My Hanh Khac Duong Thanh Tung X 9.75 10 9.5 9.5 Thanh Binh 9.5 X 10 9.5 9.25 Nguyen Hang 9.75 10 X 9.75 9.5 My Hanh 9.5 9.75 9.5 X 9.75 Khac Duong 9.75 9.75 9.75 9.75 X Total 9.625 9.81 9.875 9.625 9.5 31 APPENDIX BMI Ag Gdr 17,1563 18 Eht Avgcalo Rarcnca 2,1 1572 1,0623 17,1563 18 2,2 2162 0,8647 17,1563 18 2209 1,0196 17,5064 18 1,7 1587 0,9459 17,5771 18 3,7 2348 0,8942 17,9282 18 1,8 2208 0,8938 17,9982 18 2,5 2023 0,9513 18,1955 18 1,9 2425 0,9407 18,2563 18 1719 0,9761 18,2563 18 2,3 2458 0,8316 18,3594 18 1416 1,1881 19,0039 18 3,3 2118 0,8648 19,0311 18 2,5 2024 0,9583 19,2234 18 1,7 1612 1,3237 19,2570 18 2,9 2061 0,8745 19,4771 18 1,9 2236 1,0965 19,5918 18 3,6 2734 0,6959 19,8141 18 1908 1,0060 19,8352 18 1970 0,8664 20,1771 18 2,5 2073 1,0294 20,3428 18 1,6 1910 0,9801 20,5151 18 3,2 2652 0,6526 32 20,6131 20,6575 18 18 2,2 1916 1,2015 2079 0,8756 20,7564 18 3,6 2495 0,7724 20,8980 18 2129 0,9223 20,9275 18 2,4 1985 1,0297 21,1389 18 2,7 2207 0,8877 21,4996 18 3,7 2590 0,8242 21,8300 18 2221 0,9351 21,8787 18 2,4 2217 1,0361 21,9289 18 3,5 2294 0,9693 22,0317 18 2241 0,8651 22,2063 18 1,8 1876 0,9671 22,2222 18 1,9 1931 1,0776 22,4600 18 2,5 1650 1,0314 22,6667 18 2,8 1710 1,1604 22,8928 18 3,4 2363 1,0476 22,9210 18 3,4 2250 0,7892 23,1206 18 2,3 2469 0,7821 23,2434 18 2,1 2018 1,0246 23,3377 18 3,2 2368 0,9384 23,5078 18 3,7 2839 0,9294 23,8751 18 2,6 1735 0,9997 24,1415 18 2,6 2415 0,9966 25,0399 18 3,2 2240 0,8198 25,6896 18 2156 0,9493 33 16,4560 16,7062 19 19 0 2,8 2,3 1664 1,0792 1552 0,9417 17,1563 19 2054 0,9226 17,6254 19 1,7 1612 1,1901 17,7999 19 3,8 1749 0,9742 18,2899 19 3,1 1814 1,1622 18,3768 19 2,2 1965 0,8740 19,1990 19 2056 0,8995 19,4771 19 2,4 1792 1,1411 20,3223 19 2,5 2182 0,9248 20,3428 19 2,3 1778 1,2084 20,4294 19 3,4 2247 1,0669 20,5442 19 2,1 1655 1,2859 20,5761 19 2,5 2044 0,8877 20,9366 19 2,6 2080 0,9678 20,9572 19 2,6 1722 1,0048 21,2183 19 3,3 2029 0,9869 22,7615 19 1,9 1970 1,0178 23,3341 19 2,9 2298 0,8474 24,9680 19 2,1 2056 0,8795 25,2363 19 3,2 2034 1,0306 26,5731 19 2,1 2123 0,8549 27,9904 19 3,2 2573 0,8513 16,5289 20 2,6 2056 0,9226 17,1468 20 3,2 1585 0,9098 34 17,5064 17,8465 20 20 0 2,5 3,4 2005 0,9110 1766 1,0709 18,3594 20 2,4 1750 0,9811 18,3594 20 2,5 1959 1,0507 18,4265 20 2,1 1573 1,0972 19,0451 20 2,6 1701 1,0496 19,2974 20 1779 1,1772 19,3962 20 2,3 1587 1,0488 19,5354 20 2138 0,7705 19,7210 20 2,9 1768 0,9822 19,9792 20 2,1 1777 1,2029 20,1348 20 2,1 1746 1,1190 20,1733 20 2,7 2072 0,9376 20,1733 20 2,9 1660 1,1330 20,2395 20 2,3 1731 1,0593 20,3223 20 3,2 2312 0,8056 20,5151 20 3,1 2019 0,8678 20,5289 20 2,9 2181 0,7974 20,6575 20 2,2 2011 1,0281 22,0604 20 3,2 2125 1,0592 22,0741 20 2,7 2058 1,0864 22,1526 20 2,1 2167 0,9139 22,1591 20 2,6 1711 0,8499 23,2434 20 2222 0,9182 23,6203 20 3,5 2196 0,9560 35 23,7118 23,8367 20 20 2,7 2,8 1960 0,8996 1983 0,8371 23,9390 20 2141 0,9775 24,6770 20 3,2 2018 0,9404 25,1024 20 3,2 2334 0,8468 26,2227 20 2,7 2049 1,0041 26,5021 20 2,7 2072 0,9902 26,5731 20 3,2 2002 0,9146 27,3588 20 3,5 2020 1,0170 16,7573 21 2,4 1549 1,1651 17,5781 21 2,3 1623 0,9644 18,5901 21 1519 1,1914 19,1406 21 3,1 2031 1,0863 19,4870 21 2,7 1853 1,0773 20,0000 21 2,3 1772 1,1076 20,0692 21 3,7 2320 0,8125 20,0773 21 2,1 1630 1,0197 20,0777 21 2,6 2072 1,1127 20,2812 21 3,3 2743 0,7906 20,7756 21 1955 1,0076 21,3382 21 2,8 1807 1,2792 21,9363 21 1,9 1698 1,1281 22,0604 21 3,1 1988 0,9195 22,4480 21 2,6 1969 0,9047 22,5466 21 2,8 1976 1,1130 36 23,2912 23,3011 21 21 1 2,8 3,1 2144 0,8699 2021 0,8309 24,1217 21 2,6 2022 1,0956 25,1024 21 3,6 2183 0,8938 28,1337 21 2,7 2070 1,3521 17,0068 22 2,5 2080 0,9967 17,1753 22 3,1 2001 0,9915 19,0677 22 2,2 1685 1,1856 19,3821 22 1,7 1658 1,0028 20,3428 22 1,9 1654 1,1640 20,5049 22 1,9 1840 1,2938 20,8086 22 2,7 2142 0,9314 20,8889 22 2,5 1751 1,0802 21,4903 22 1,7 1607 1,2822 21,5019 22 1877 1,1857 21,7738 22 2,1 2038 0,9561 22,0492 22 2,5 1924 1,1235 22,5069 22 3,1 2170 1,1294 22,6627 22 3,7 2443 0,6979 23,6713 22 2,5 1896 0,9687 23,9395 22 3,1 2146 0,9995 23,9869 22 3,4 2786 0,7370 24,2587 22 2,2 2012 1,0996 24,4561 22 1,7 1875 1,0508 24,5351 22 2,4 1897 0,9176 37 26,0790 26,4024 22 22 1 2,1 3,5 2003 0,9707 2775 0,9000 27,2173 22 2,4 1993 1,1935 38 39 ... appreciation to your useful lectures of this course and instruction to fulfill this report Throughout process of making this report, our team did try our best to gather data, conduct researches and utilize... information from the survey Structure of scope The report has been structured to reflect the different research goals for the project This report is organized as follows: Sections I will overview... Obesity in adulthood is associated with increased mortality, and data from the Framingham Heart Study report that obese adults (BMI ≥ 30) at age 40 years lived 6–7 years less than did their normal-weight