tiểu luận kinh tế lượng ECONOMETRICS REPORT

BMI plays a crucial role inanalyzing the status of well-being, measuring the risk of hazardous diseasesresulting from overweight like obesity, cardiovascular diseases, high bloodpressure

FOREIGN TRADE UNIVERSITY

FACULTY OF INTERNATIONAL ECONOMICS

Lecturer: MSc Quynh Thuy Nguyen

TABLE OF CONTENTS

ABSTRACT 1

INTRODUCTION 2

1 Research objective 2

2 Rationale of study 2

3 Object and scope of study 4

4 Structure of scope 4

SECTION I: OVERVIEW OF THE TOPIC 5

1 General definitions and economic theories 5

1.1 General definitions 5

1.2 Economic theories related to the research 7

2 Literature view 9

2.1 Related published researches 9

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

1 Methodology 14

1.1 Method you use to derive the model 14

2 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

1 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

2 Hypothesis Testing 24

2.1 Testing the significance of an individual regression coefficient βj 24

2.3 The T-distribution approach 25

3 The P-value approach 26

4 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

18 or older.

This provides the answer to our question why BMI is one of the mostreliable index reflecting the recent health situation BMI plays a crucial role inanalyzing the status of well-being, measuring the risk of hazardous diseasesresulting from overweight like obesity, cardiovascular diseases, high bloodpressure or from underweight like malnutrition, vitamin deficiencies, etc.However, in reality, to achieve an ideal BMI index, we have to pay moreattention to a number of factors directly affecting it, namely nutritious intake ineach portion, daily eating habit, average workout hours, sex, age, etc So in thisstudy we will gain deeper insight into the primary factors affecting BMI indexand shed light on the optimal approaches to reach standardized BMI, improvethe general public well-being

We would like to give our appreciation to your useful lectures of thiscourse and instruction to fulfill this report Throughout process of making thisreport, our team did try our best to gather data, conduct researches and utilizeavailable materials to analyze the result However, mistakes are inevitable.Therefore, please let us know if there are some ones that must be fixed toachieve more accurate result

1 Research objective

The main purposes of this study is to provide thorough understanding ofBMI index, and analyze fundamental elements contributing to fluctuation ofBMI ranging from nutritious regime, eating habit to workout routine To be morespecific, it also supplies data about every single substance in daily diets,frequency and the typical amount of calorie burned in exercising, the numberand rational distribution of daily meals This study also enables people to foreseethe positive or negative trend of BMI in the future, gives recommendations forthem to propose long-term plan for the sustainable development of public health

2 Rationale of study

There are a few motivations prompting us to do this research:

- The lifestyle in the modern societies pose various threats to our health,particularly for youngster The consumption of junk food has been considerablyincreasing year by year Besides, the rate of children as well as adults becomingobese is so alarming, which has been linked to a lack of physical exercises Onthe contrary, in the most remote areas, many families have to struggle to feedthemselves so malnutrition is a very common tendency The underweight andoverweight is associated with a plenty of dangerous diseases for health:

- Being overweight increases the risk of a number of serious diseases andhealth conditions Below is a list of said risks, according to the Centers forDisease Control and Prevention (CDC):

• High blood pressure

• Higher levels of LDL cholesterol, which is widely considered "badcholesterol," 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 healthyBMI

- 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 thatcan 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 healthyBMI

Therefore, more attention should be placed on and more investigation should

be conducted on a regular basis to get deep understanding of primary elementshaving influences on BMI index From those data and results of this paper, aspecific plan can be set up to regulate the amount of nutrition intake, time forexercise 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 getvariables directly affecting BMI as well as the most accurate consequences Arange of research methodologies was used to investigate current practice and tocapture data about the scope and fundamental contributors in BMI index Using

a software Stata used for statistical analysis; descriptive statistics and summarymethods to analyze the information from the survey

4 Structure of scope

The report has been structured to reflect the different research goals forthe project This report is organized as follows: Sections I will overviewdefinitions Section II will explore methodology of study: Factors that affectBMI 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 dailydiets and workout routine, improving the state of well-being and reaching anideal BMI

SECTION I: OVERVIEW OF THE TOPIC

1 General definitions and economic theories

- Body mass index is a measure of body fat and is commonly used withinthe health industry to determine whether your weight is healthy BMIapplies to both adult men and women and is the calculation of bodyweight in relation to height This article delves into the BMI formula anddemonstrates 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

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

Table 1

1.1.3 Current problems around BMI

It is a common argument that the results the BMI formula provides are toogeneral and do not consider the gender, build, age or ethnicity of a person Forexample, professional athletes are often considered overweight or obese whenusing BMI measurements due to their muscle content, which weighs more thanfat

Similarly, as people age their bone density decreases So, although theymay seem to have a weight within the normal BMI range, their measurementactually needs to be scaled-down to reflect this In a study published in theJournal of Economics in 2008, John Cawley, professor at Cornell University,was able to demonstrate that, relative to percent body fat, BMI appears tomisclassify 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:

• The meaning of partial regression coefficients

β2=

2

3

The extent to which all the independent variables jointly (i.e., the model) explain the variation in the dependent variable

R2 is a non-decreasing function of the number of independent variables

in the model

- Model with more terms may appear to have a better fit

- If there are too many predictors, it will result in over-fitting the model:misleading high R2 and a lessened ability to make predictions

- k is the number of parameters in the model

- “Adjusted”: adjusted for the degree of freedom associated with

the sums of squares

- R 2 and ̅ 2 are related:

- ̅ 2 can be less than zero

- ̅ 2 is used for the following purposes:

+ ̅2 is used to compare the fitness between models with different number of explanatory variables.

The sample size n and the dependent variable must be the same

+ ̅2 is used to consider adding one more variable into the model The variable will be added if:

• Population regression model:

2.1 Related published researches

Obesity is a world-wide health problem across the lifespan that alsoaffects the elderly in developed and emerging countries In these countries, theirpopulations have proportionally greater numbers of older adults living to olderages, and the prevalence of obesity is increasing rapidly even at these oldestages In the United States, the prevalence of obesity in the elderly ranges from42.5% in women aged 60–69 years to 19.5% in those aged 80 years or older Theprevalence of obesity is 38.1% in men aged 60–69 years and 9.6% for those menaged 80 years or older In Europe, the prevalence is slightly lower but it is still asignificant health issue In the United Kingdom for example, 22% of women and12% of men aged 75 years or older are obese These statistics bode ill as theproportion of world’s elderly population continues to increase

Obesity in adulthood is associated with increased mortality, and data fromthe Framingham Heart Study report that obese adults (BMI ≥ 30) at age 40 yearslived 6–7 years less than did their normal-weight counterparts Another studybased on several U.S data sets (US Life Tables (1999), the third National Healthand Nutrition Examination Survey (NHANES III), NHANES I and II, and theNHANES II Mortality Study) also reported that obesity reduces life expectancy,particularly so in younger adults For example, in obese (BMI ≥ 45) white menand women aged 20–30 years, the minimum years of life lost was 13 and 8years, respectively

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The aim of this systematic literature review is to collate, review andcritically assess current scientific and clinical information on the impact ofobesity on mortality in the elderly so as to help clarify and improve ourunderstanding of the complex relationship between the increasing healthproblem of obesity in elderly adults and the risk of mortality This knowledgecan help to reduce the cost of health care and improve the quality of life in thissegment of the world’s population.

2.2 Research hypotheses

H1: 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?

2.3 BMR

Calculate your Basal Metabolic Rate (BMR)

Our bodies are like engines that are constantly running They're alwaysburning fuel or calories (even during sleep) BMR is the number of calories youburn each day simply by being alive

Your Basal Metabolic Rate (BMR) can vary based on your age, sex, size,and genetics To get an accurate picture of the amount of calories you burn perday, start by calculating a value for your BMR

Use the following equations to find your BMR by hand:

• Men: (0.1 × weight) + (6.25 × height*100) - (5 × age) +5

• Women: (0.1 × weight) + (6.25 × height*100) - (5 × age) -161 Doing exercises is an important factor which accelerates the calorie-burning process

2.4 Calories Expenditure of Exercise

• Based on your current weight

• Based on 30 mins duration

2.5 Calories expenditure of Common Foods

Tofu 4 oz 86 360

Table 3

SECTION II: MODEL SPECIFICATION

1 Methodology

1.1 Method you use to derive the model

The process using in this research is called Multiple Linear Regression.This is a linear approach to modeling the statistical relationship of a dependentvariable on one or more explanatory variables Specifically, in our research, it isthe statistically dependent relationship between eating habit, exercising routineand BMI index

Methods used to collect and analyze the data

- Collect: At first we do many types of research: do survey by passing outanswer sheets, gather a number of related researches on WorldBank andreference documents

- Therefore, we decide to use another method to collect our data, which ismail interview It took quite a lot of time to draw up an attractive mail form tosend to our subjects of research but one of the most benefit of this method is that

we can send to many people in a very polite way Nevertheless, the response rate

is often low, it takes a lot of time to wait for outgoing messages and replies,uncontrolled respondents can reply to the wrong target …

- Especially, we get a lot of data from Worldbank, which is a very reliableopen data site The searching is very fast because we only need to sort out thedata and search directly on the Worldbank website This is really convenientbecause we do not have to spending a lot of time and giving us a high level ofconfidence in the accuracy of the numbers

- Analyze: With the assistance of Stata 14 software and the following step

to analyze data

+ Step 1: Data Validation

The purpose of data validation is to find out, as far as possible, whetherthe data collection was done as per the pre-set standards and without any bias It

is a four-step process, which includes…

❖ Fraud, to infer whether each respondent was actually interviewed or not.

❖ Screening, to make sure that respondents were chosen as per the research criteria

❖ Procedure, to check whether the data collection procedure was duly followed

❖ Completeness, to ensure that the interviewer asked the respondent all the questions, rather than just a few required ones

❖ To do this, we would need to pick a random sample of completedsurveys and validate the collected data For example, we sort outpeople into many ranges of age, many kinds of activities to specify tosuitable burned calories After that we can reach out to them throughemail or phone and check their responses to a certain set of questions

+ Step 2: Data Editing

Typically, large data sets include errors To make sure that there are nosuch errors, we conduct basic data checks, check for outliers, and edit the rawresearch data to identify and clear out any data points that may hamper theaccuracy of the results

+ Step 3: Data Coding

This is one of the most important steps in data preparation It refers togrouping and assigning values to responses from the survey For example, some

of the acronyms we use to assign values such as: Height-hght, Weight- wght,

2 Theoretical model specification

2.1 Specification of the model

According to previous published researches, our group has established

a function to analyze the relationships between related variables and the

BMI index as well as the effects of those variables toward the dependent

variable:

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BMI = f(Ag, Gdr, Eht, Avgcalo, Rarcnca)

Where:

BMI: Body Mass Index

Ag: Age

Gdr: Gender

Eht: Eating habit

Avgcalo: Average calories burned per day

Rarcnca: Rate of absorbed calories over necessary calories

 Thus, according to the economic theories, in order to analyze the factors

influencing the BMI index, our group has discussed and decided to choose the regression analysis models

2.1.1 POPULATION REGRESSION MODEL (PRM)

Where:

β0: the intercept term of the model

β1: the regression coefficient of “age”

β2: the regression coefficient of “gender”

β3: the regression coefficient of “eating habit”

β4: the regression coefficient of “average calories burned per day”

β 5 : the regression coefficient of “rate of absorbed calories over necessary calories”

: the disturbance term of the model, represents other factors that affect UEM but not mentioned in the model

+ Explain the variables, proxies to measure and their units

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X1 Age Ag Do survey Year

- 1

amount of water per day, level ofhealthy eating time, numerous ofmeans per day Interval of Eht is[1,4], the higher Eht is, the healthiereating habit they have

Men: (0.1 × weight) + (6.25 ×

height*100) - (5 × age) +5Women: (0.1 × weight) + (6.25 ×height*100) - (5 × age) -161

maintain, and 1500 calories to loseone pound of weight per week Anaverage man needs 2500 calories tomaintain, and 2000 to lose one pound

of weight per week

Table 4

❖ Dependent variables :

Y=BMI

❖ Independent variables :

calories

According to our aforementioned research, many factors can affect your

for you to lose weight or avoid regaining weight that you’ve lost

- Age: Many people gain weight as they age Adults who have a normalBMI often start to gain weight in young adulthood and continue to gain weightuntil they are ages 60 to 65 In addition, children who have obesity are morelikely to have obesity as adults

- Gender: A person’s gender may also affect where the body stores fat.Women tend to build up fat in their hips and buttocks Men usually build up fat 18