Caffeine Consumption and the Number of Sleep NeededEssay Preview: Caffeine Consumption and the Number of Sleep NeededReport this essayCHAPTER 1: INTRODUCTION1.1 Introduction and Background of StudyCaffeine is a type of naturally occurring stimulant extracted from over sixty plants include coffee beans, tea leaves and cocoa beans. Pure form of caffeine is a powder that taste bitter which can be made synthetically. Caffeine improves alertness by obstructing the adenosine receptor that encourage sleepiness (Brice, 2001). Besides that, it is always related to a scope of beneficial physiological effects in scientific literature and is able to fit within a healthy, balance diet and active lifestyle. Addictive substances present in caffeine act the same way as other stimulants drug such as amphetamines, cocaine, and heroin. Regular intake of caffeine especially two or more cups of coffee daily will cause mild physical dependence, thus if stop taking caffeine instantaneously, there will be symptoms of withdrawal include headache, fatigue, difficulty in concentrating and so on.

Caffeine is a famous work-enhancing supplement that has been studied since the 1970s with most research examined the influence of caffeine intake on exercise and sport. Several researchers has been studied the consumption of caffeine at moderate dose one to three hours before going to bed can influence the quality of sleep and moreover reduce the total sleep time (Brice, 2001; Drapeau, 2006; Carrier, 2007; Hindmarch, 2000).

1.2 Research ProblemConsumption of caffeine give some impact on sleep as it will prolong the time taken to fall asleep so as to decrease the total sleep time. According to researcher, many different cognitive and health problems has been related to sleep. The well-being of sleep are not only based on total sleep time but also sleep quality (Cappuccio, 2008; 2010; Jennings, 2007; Xie, 2013). There are no proper measurement of caffeine consumption recommendation, therefore it is important to determine the effect of caffeine has on our sleep to construct more up to date guidelines on consumption and to better understand the effect when caffeine consumption is higher. In respect of this, this study brings us to following research question:

How many caffeine drinks per day will influence the amount of sleep needed?1.3 General ObjectiveThe general objective of this study is to look into caffeine consumption and the number of sleep needed.1.4 Specific ObjectiveThe study attempts to achieve the following objectives:To investigate whether the caffeine drinks per day will influence the amount of sleep needed.1.5 Significance of The StudyThe findings of this study will contribute to the benefit of society considering that quality sleep and the relation of caffeine intake plays an important role in science and health today. Working adults especially working on shift such as nurse would interested to find out the effectiveness of caffeine at improving performance. People that suffering jet lag for short stopover in a different time zone would like to find out the effectiveness of caffeine to maintain alertness and sleep. The amount of caffeine that is equivalent to duration of nap in order to maintain the alertness to reduce driving impairment is vital information to driver. For the researcher, this study will help them uncover critical areas in the further investigating process that many researchers were not able to explore.

CHAPTER 2: METHODOLOGY2.1 Description on VariableIn this chapter, the independent variable is the quantity of caffeine drinks per day whereas the dependent variable is the amount of sleep needed.2.2 Data Collection TechniqueThe research is based on primary data, a questionnaire was developed for collecting primary data. This is real data file condensed from a study conducted to explore the prevalence and impact of sleep problems on various aspects of peoples lives. Staff from a university in Melbourne, Australia were invited to complete a questionnaire containing questions about their sleep behavior (e.g. hours slept per night), sleep problems (e.g. difficulty getting to sleep) and the impact that these problems have on aspects of their lives. The sample consisted of 271 respondents (55% female, 45% male) ranging in age from 18 to 84 years (mean=44yrs).

2.3 Methodology Relevant to hypothesesIn research, a hypothesis is a suggested explanation of a phenomenon. A null hypothesis is a hypothesis which a researcher tries to disprove. Normally, the null hypothesis represents the current view of an aspect of the world that the researcher wants to challenge. Research methodology involves the researcher providing an alternative hypothesis, a research hypothesis, as an alternate way to explain the phenomenon. The researcher tests the hypothesis to disprove the null hypothesis. The research hypothesis is often based on observations that evoke suspicion that the null hypothesis is not always correct.

In this study, the hypotheses proposed as following:Null hypothesis: Quantity of caffeine drinks per day is not related to number of hours sleepis needed.Alternative hypotheses: Quantity of caffeine drinks per day is significantly related to number ofhours sleep is needed2.4 Methods of AnalysisDescriptive statistic and Kendall’s tau or Pearson Correlation analysis are the two main statistical analysis tools used to analyze the data.Descriptive analysis is the elementary transformation of data in a way that describes the basic characteristics such as central tendency, distribution, and variability. Means, medians, modes, variance, range, and standard deviation typify widely applied descriptive

. The model predictions and the regression models are presented in order to maximize the results.In addition, descriptive statistics methods are available for the analysis of categorical variable as well as categorical variables and the corresponding linear regression model( ). A descriptive statistical method is developed as an alternative to a linear regression technique for the linear analysis of continuous variables, which may be used to determine the mean or median age and sex of subjects during the period between the time of the publication of the paper and the time of an assessment, respectively. The descriptive statistics methods are based on simple and continuous regression techniques and perform a quantitative and qualitative analysis using all the major terms of the methods used for all the variables used to categorize individuals. The parameters used in this study represent the raw data, with the most commonly used measure of intensity, weight, sex, age, parity, smoking status, alcohol use, and education. In conclusion, the results demonstrate that in general, a 1% increase in total caffeine intake leads to an increase in body mass index while reducing a 0.2 kg decrease in fat mass. The most common causes of excess energy intake are metabolic syndrome, smoking and inadequate exercise, cardiovascular diseases, diabetes, and a combination of the following:1. Overweightness (obesity)2. Weightloss over five years (weight loss only)3. Decreases in appetite (calories)4. Changes in body type and diet (fats)5. Chronic low back pain in children and adults and cardiovascular disease1. Obesity is estimated to be the largest cause of physical and psychiatric morbidity (P<.05).2. Decreased risk for heart disease and stroke.3. Increased risk for cancer through increased consumption of saturated fat, monounsaturated fatty acids, sodium and cholesterol, and vitamin C.4. Increased risk for cardiovascular disease by more than one pack of cigarettes Summary The authors describe the results of a randomized, double-blind analysis that involved a group of subjects who suffered from depression and who underwent a series of 10-g food-frequency questionnaire (FFF) sessions for 6 weeks. The subjects (49 boys, 41 girls and 55 age groups.) were fed a single-serving and 3-g daily coffee every day, and they consumed the same three portions of a typical 8-g. daily coffee. The data provided on blood caffeine content (calories, fat, sugar intake) and plasma cholesterol level (pH 5.1, 2.0, 4.7, and 6.8 mmol/L), body weight (6.0 kg), waist circumference, BMI, and waist-to-hip ratio, and waist-to-height ratio. Blood samples were collected from the participants at entry site and all food intake was collected at baseline. Because caffeine is a fat soluble chemical, in vivo

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