Calorie
A calorie measures energy expenditure and storage, playing a crucial role in weight management To lose weight, one must consume fewer calories than burned; to gain weight, one should intake more Maintaining weight requires a balance between calorie intake and expenditure Factors such as gender and age also influence these dynamics The body utilizes calories from food to support its basal metabolic rate (BMR), digestion, and physical activity.
Exercising
More physical activity increases the number of calories your body uses for energy or
“burns off.” The burning of calories through physical activity, combined with reducing the number of calories you eat, creates a “calorie deficit” that results in weight loss.
Exercising plays an important role in losing, maintaining, even raising weight.
Therefore, university students who do not have the exercise habits in comparison with the ones who practice physical exercise everyday might have a higher number of weight or body fat.
Gender
Research indicates that men are more likely to be overweight or obese than women, despite both genders exhibiting unhealthy dietary habits, reflected in low mean Healthy Eating Scores (HES) Notably, men consume more than 6 oz (168 g) of animal protein daily compared to women Conversely, a larger percentage of female students frequently eat potato chips, fatty snacks, and sweets, indulging in sugary treats more than twice a day.
Sleeping hours
Insufficient sleep can lead to weight gain, as individuals who average less than five hours of sleep per night are nearly 30% more likely to become overweight compared to those who enjoy seven hours of rest Prioritizing adequate sleep is crucial for maintaining a healthy weight.
Insufficient sleep disrupts your body's insulin response, making it difficult to process fats in your bloodstream, which leads to increased fat storage Therefore, rather than simply losing weight through sleep, inadequate rest negatively affects your metabolism and can contribute to weight gain.
Meal frequency
Preliminary research indicates that eating frequently, such as eight times a day, can lead to increased hunger and cravings, while consuming fewer meals, like three times a day, may promote a greater sense of fullness Conversely, limiting meals to once or twice daily can hinder weight loss efforts and negatively impact health due to inadequate nutrition University students often fall short of the recommended meal frequency, which can stem from misguided weight loss strategies or simply a lack of motivation to maintain a balanced diet.
From the correlation matrix above, we can make some thoughts about if it has the correlation relationship among variables or not, but we could not give out the conclusion.
● Y weight Mean: The average weight of 40 surveyed VJCC K57 students is54,788 kilograms
● Y weight Minimum: The minimum weight among 40 surveyed VJCC K57 students is 44 kilograms
● Y weight Median: fitted value of dependent variable Y weight 53.5 kilograms
● Y weight Maximum: The maximum weight among 41 surveyed VJCC K57 students is 75 kilograms
● Std Dev (Standard Deviation): is a measure of how spread the numbers are, equals to the square root of sample variance The Std Dev of Y weight here is 7,7789
The Coefficient of Variation (C.V.) is calculated by dividing the standard deviation by the sample mean, serving as an indicator of measurement precision A high C.V value suggests that the mean is not accurately measured In this case, the C.V for Y weight is 0.14198.
➢ From the summary statistic chart, we can see that it might be the representative sample for Weight depends on the five variables
● Setup dependent and independent variables:
Y : The weight of VJCC K57 students
X 1 : The amount of calories a VJCC K57 student takes in a day
X 2 : The number of hours per week a VJCC K57 student spends on doing exercises
X 3 : The number of hours per day a VJCC K57 student spends on sleeping
X 4 : The number of meals a VJCC K57 student has per day
X 5 : The gender of a VJCC K57 student (1 if male, 0 if female)
R 2 = 0,879901 : It means that the five regressors explain 84,6% of the variance of Weight
SER = 2.887228 : It estimates standard deviation of error u i A relative low spread of scatter plot means that prediction of Weight base on these variables might be reliable.
Multicollinearity
We can see from the chart that all the VIF values of the variables are less than 10.
➢ All the variables do not show the collinearity problem.
Normality
From the Histogram, it seems to be quite normal distribution with the 2 relatively equal tails.
From Kurtosis and Skewness data above, we see that it might not be normal distribution as when looking with the naked eyes.
However, by the Jarque-Bera test , we can identify whether the assumption of normal distribution is right or not.
H 1 : ui does not follow normal distribution
It can be seen from the figures that p-value = 0,56734 >> α = 0,05
● With the common α = 5% for the 2-tail test, we are able to give the conclusion not to reject the assumption H 0.
● Therefore, we accept the assumption that u i follows the normal distribution.
Heteroscedasticity
F test of the overall significance of model
We can check F test by looking at the P-value ( F) from the chart above P-value (F) = 1.10e-14 2.04 p-value = 5.97e-06 < 0.05 = α
H 1 : β 2≠ 0 – a linear relationship is recorded between X 2 and Y
● From the chart above, t-ratio of X 2 =-0.06104 ∈ ( -2.00;2.00 ) p-value = 0.3565 > 0.05 = α
● Moreover, no * means that X 2 does not have the statistical significance
➢ At 5% level of significance, we have enough evidence not to reject H 0, that no linear relationship is recorded between X 2 and Y.
Testing 3 : H 0: β 3=0 – no linear relationship between X 3 and Y
H 1: β 3 ≠ 0 – a linear relationship is recorded between X 3 and Y
● From the chart above, t-ratio of X 3 = -0,06536 ∈ ( -2,00;2,00 ) p-value = 0.9517 > 0.05 = α
● Moreover ,no * means that X 3 does not have the statistical significance
➢ At 5% level of significance, we have enough evidence not to reject H 0, that no linear relationship is recorded between X 3 and Y.
Testing 4 : H 0 : β 4=0 – no linear relationship between X 4 and Y
H 1 : β 4 ≠ 0 – a linear relationship is recorded between X 4 and Y
● From the chart above, t-ratio of X 4 = 3,451 > 2,4 p-value = 0.0015 < 0.05 = α
● However ,*** means that the statistical significance of X 4 equals to 1%
➢ At 1% level of significance, we have enough evidence to reject H 0, that a linear relationship is recorded between X 4 and Y.
Testing 5 : H 0 : β 5=0 – no linear relationship between X 5 and Y
H 1 : β 5 ≠ 0 – a linear relationship is recorded between X 5 and Y
● From the chart above, t-ratio of X 5 = 3.439 > 2.04 p-value = 0.0016 < 0.05 = α
➢ At 1% level of significance, we have enough evidence to reject H 0, that a linear relationship is recorded between X 5 and Y.
The analysis indicates that the weight of VJCC K57 students is significantly influenced by three key factors: daily calorie intake, the number of meals consumed each day, and gender.
Adjusted regression model
Our study analyzes data from 40 VJCC K57 students, focusing on gender, daily calorie intake, number of meals, exercise duration, sleep duration, and weight We exclude exercise hours and sleep hours from our analysis, retaining daily calorie intake, number of meals, and gender The findings are presented through an adjusted OLS regression model.
The estimated OLS regression is:
^ Weight = 22,7204 + 0,0115 C + 2,08948 M+ 4,28871 G For the purpose of the research, let:
● The OLS estimate of the intercept is 22.7204
The OLS estimate indicates that for each additional calorie consumed daily, a VJCC K57 student’s weight is expected to increase by 0.0115 kilograms.
The OLS estimate indicates that each additional meal consumed daily by a VJCC K57 student results in an average weight increase of 2.09 kilograms.
The OLS estimate indicates that gender significantly impacts the weight of VJCC K57 students, with a coefficient of 4.28871 This means that VJCC K57 boys weigh, on average, 4.28871 kilograms more than their female counterparts.
● R 2 = 0.876686 : It means that the three regressors explain 87.66% of the variance of Weight
● SER = 2.843184 : It estimates standard deviation of error u i A relative low spread of scatter plot means that prediction of Weight base on these variables might be reliable.
Finding and supplement
Follow medbroadcast.com
There are some ways to improve the weight without too much long-term effort :
● Medical intervention: Medications may be part of a weight management program.Medications aren't "magic cures" leading to permanent weight loss.
They're generally used in combination with a proper diet and exercise program.
Weight-loss medications are primarily intended for individuals classified as obese, defined as having a BMI over 30, or those with a BMI of 27 who also face additional heart disease risk factors, such as high cholesterol or diabetes While some medications are approved for short-term use only, one notable example available in Canada is orlistat, which works by blocking the absorption of fat in the intestines.
Surgery for obesity is typically pursued only after other weight management strategies have failed Various types of obesity surgeries exist, primarily aimed at reducing stomach size to limit food intake Commonly used terms for these procedures include gastric surgery, gastric bypass surgery, and laparoscopic band.
Research indicates a connection between sleep duration and body weight, revealing that both children and adults who do not get sufficient sleep are more likely to be overweight compared to those who enjoy adequate rest.
A study involving approximately 60,000 women over 16 years revealed significant findings regarding sleep duration and obesity risk At the study's onset, all participants were healthy and not obese However, after 16 years, women who slept 5 hours or less per night faced a 15% increased risk of becoming obese compared to those who slept 7 hours Additionally, short sleepers had a 30% higher likelihood of gaining 30 pounds during the study period, underscoring the importance of adequate sleep for weight management.
There are several possible ways that sleep deprivation could increase the chances of becoming obese Sleep-deprived people may be too tired to exercise, decreasing the
Insufficient sleep can lead to increased calorie intake, as individuals are awake longer and have more chances to eat Additionally, sleep deprivation disrupts the balance of hormones that regulate appetite, causing those who lack sleep to feel hungrier compared to those who enjoy adequate rest each night.
Regular physical activity is essential for effective weight management and enhances overall health while lowering the risk of diseases like certain cancers, heart disease, and osteoporosis You don't need to join a gym; simple changes like taking the stairs, walking or cycling to work, and enjoying lunchtime walks with coworkers can significantly increase your activity level The key is to incorporate enjoyable exercises into your daily routine to promote a healthier lifestyle.
While the duration of exercise and sleep among VJCC K57 students may not directly impact their weight, these behaviors could have become habitual, leading to the body developing self-adaptive mechanisms However, research indicates that maintaining an appropriate balance of exercise and sleep is crucial for overall health and can significantly influence weight management.
After doing survey about effects on weight of K57 VJCC and using Gretl to solve data given, we have drawn to some conclusions below:
Gender influences the weight of VJCC K57 students due to differing body compositions Consuming three or more balanced meals daily, as opposed to fewer meals, can effectively manage appetite and promote a sense of fullness.
(According to www.health.harvard.edu)
To effectively influence the weight of VJCC K57, adjusting calorie intake is crucial On average, individuals require approximately 2000 calories daily to sustain energy for regular activities To gain or lose weight, one can simply increase or decrease their calorie consumption according to their specific body condition and goals.
VJCC K57 students are advised to pay attention to their daily calorie intake and meal frequency While factors such as physical exercise and sleep duration may not show significant statistical impact, it is essential for K57 students to ensure they get at least 6-7 hours of sleep each night and engage in regular physical activities to maintain a fit body and promote a healthy lifestyle.
For individuals struggling with obesity, extreme diets may not effectively lead to weight loss Instead, focusing on a balanced, nutritious diet that maintains a moderate calorie intake is crucial Ensuring that calorie consumption is lower than calorie expenditure, combined with regular physical activity to boost metabolism, adequate hydration, and sufficient sleep each day, can significantly aid in achieving weight loss goals.
For individuals who are underweight, it's essential to incorporate healthy calories into their diet to promote weight gain without making drastic changes This can be achieved by adding nutritious toppings such as nuts or seeds, incorporating cheese, and including wholesome side dishes.
Incorporate nutrient-dense foods such as almonds, sunflower seeds, ripe mangoes, bananas, and whole-grain toast into your diet to promote healthy weight gain Focus on high-calorie fruits that provide essential nutrients, while steering clear of unhealthy, high-calorie options that contribute to poor digestion and obesity.
A meta-analysis conducted by Ballor and Kessey (1991) investigates the factors influencing exercise-induced changes in body mass, fat mass, and fat-free mass among both males and females The study, published in the International Journal of Obesity, emphasizes the significant variations in how exercise impacts different individuals, highlighting the importance of understanding these factors for effective weight management and fitness strategies For further details, the article can be accessed through Europe PMC.
J S Garrow, C D Summerbell (1995) Meta-analysis: Effect of exercise, with or without dieting, on the body composition of overweight subjects European
Francesco P Cappuccio, MD, FRCP, Frances M Taggart, PhD, Ngianga-Bakwin
Kandala, PhD, Andrew Currie, MB ChB, Ed Peile, FRCP,Saverio Stranges,
In her 2008 study, MD, PhD Michelle A Miller conducted a meta-analysis examining the relationship between short sleep duration and obesity in both children and adults The research, published in the journal Sleep, highlights the significant correlation between insufficient sleep and increased obesity rates, emphasizing the importance of adequate sleep for maintaining a healthy weight This comprehensive analysis, found in Volume 31, Issue 5, pages 619-626, provides crucial insights for healthcare professionals and parents alike, urging a focus on sleep hygiene as a preventive measure against obesity **Reference:**Miller, M A (2008) Meta-analysis of Short Sleep Duration and Obesity in Children and Adults Sleep, 31(5), 619-626 Retrieved from [academic.oup.com](https://academic.oup.com/sleep/article/31/5/619/2454190?fbclid=IwAR164TLp0q00aNe8F7YzJbfUnUod7fg-XzAIYAdy1aM-HtmcZuyIKFSFwgc)
Brad Jon Schoenfeld, Alan Albert Aragon, James W Krieger (2015) Effects of meal frequency on weight loss and body composition: a meta-analysis Nutrition