Coffee and physical activity6 Coffee and Income6 Conclusion6 Research question7 Research objectives7 Methodology7 Research approach and design7 Research setting8 Study population and sample8 Data Collection9 Data collection instrument9 Data collection procedure9 Reliability and validity10 Reliability10 Validity10 Ethical considerations10 Conclusion10 Data11 Estimation and Results14 Conclusion and Recommendations16 Bibliography17 Appendix 119 Questionnaire instructions. 19 Instructions on how to complete the questionnaire19 Coffee questionnaire20 Personal information:20 Abstract
The following paper discusses the main determinants of coffee consumption at Westminster International University in Tashkent. Determinants such as income of respondent, ethnicity, religion, smoking habits and other factors are investigated. Data was collected using online methods of surveying and self-administrated questionnaires. Results proved to be significant and revealed a negative correlation between coffee consumption, active lifestyle and marital status. In contrast, positive correlation between coffee consumption income and age was found. Other factors as smoking, religion, education years proved to be insignificant.
Introduction Being the third most consumed beverage in the world after water and tea, coffee is valued for its distinct aroma, flavor and energizing effect. Found in Ethiopia in the 9th century, coffee first became popular in the Arab world, was then promoted in Europe and consequently developed into one of the most traded commodities in the world(John K. Francis, 2007). World annual per capita consumption was equal to 1. 3 kg/person in 2011. America and Europe are the largest coffee consumers on per capita basis, accounting for 3. 9 and 3. 7 kg/person respectively, in comparison to Asian countries where the average constituted 0. kg/person (World Resources Institute, 2011). Nevertheless, the western coffee consumption habits are slowly starting to spread in Asia, especially in Uzbekistan, where coffee is considered as a fashionable hot drink rather than an everyday necessity. The consumption of both instant and insoluble coffeein Uzbekistan is limited to urban areas and is generally increasing alongside with the rising living standards (Euromonitor, 2011). Furthermore, the rising number of coffee shops and the popularity of coffee houses such as Cafe Jum, Julius Meinl, Book Cafe, KafeKafe and Coffee Clubare good indicators of the growing popularity of coffee.
Literature Review Evidence from various studies identify that living standards are not the only determinant of coffee consumption behavior. Smoking, smoking cessation, alcohol, age, gender, level of physical activity and income also play a sufficient role in one’s consumption patterns. In their comprehensive research on coffee and associated lifestyle factors published in 2010 Hewlett and Wadsworth discovered a link between caffeinated drink consumption, smoking and alcohol. The findings revealed that those drinking coffee were more likely to be smokers aged between 30 and 70.
Another review on coffee consumption behavior in Karnataka, India published in 2008 by Varun indicated a positive correlation between education, family size and income on coffee demand in urban areas, whereas in the rural areas, the price was the main determinant influencing consumption. The rationale for the linkage of the determinants and coffee consumption is reviewedand discussed belowbased on a wide range of researches and surveys. The studies concerning coffee consumption behaviorwere obtained from EBSCO, JStor, Emerald and Google Scholar databases.
Those researches included in the literature review are published in English, report coffee consumption behavior; show correlation with at least some of the lifestyle factors and provide a detailed review of the applied methodology and statistical analysis. Coffee and Smoking Seven studies concluded that higher cigarette consumption among persistent smokers is linked to highercoffee consumption. The investigation on coffee consumption patterns among army personnel byZavela et al. (1990) revealed a positive correlation between female cigarette and alcohol consumption and male cigarette and coffee consumption.
Furthermore, the researchers identified that non-smokers tend to be abstemious to coffee and alcohol consumption. In contrast, Koksal et al. (2011) in their pseudo-panel analysis of US household data came to the conclusion that that coffee consumption and consumption of cigarettes and alcohol are not correlated due to the statistical insignificance of the cross price elasticities of coffee. However,even though there is no serial complementary relation in the observed population, the authors do not exclude the possibility that coffee and cigarettes are complements for some individuals. Studies by Salazar et al. and Garcia et al. hat analyzed the responses from about 120’000 participants both, stated that more than 50% of female smokers drank at least 6 cups of coffeeper day, whereas only 30% of smoking men consumed at least 6 cups of coffee on a daily basis. Digging even further into the research of the relation of smoking and coffee, Klesges et al. conducted a large epidemiologic study with more than 7500 respondents. The researchers labeled those consuming from one to four cigarettes per day as light smokers, those smoking from five to twenty cigarettes as moderate smokers and those smoking at least twenty one cigarettes per day as heavy smokers.
Further analysis revealed that light and moderate smokers where 2. 34 and 2. 84 times more likely to drink coffee than non-smokers, whereas heavy smokers where 4. 23 times more likely to be coffee consumers. The comparison of the student sample with the general public sample by Brice et al. illustrated that smokers in both samples were likely to drink more coffee in comparison to non-smokers. In the student sample (121 respondent) smokers on average consumed 76 mg more caffeine than their fellow non-smokers. In the general public sample (122 respondent) smokers consumed 92 mg more than non-smokers.
The majority of the academic papers revealed a positive correlation between smoking and coffee consumption (except the Koksal et al. study). However, some of the mentioned above studies might be a subject to bias as most of the respondents were asked to self-report coffee consumption and smoking habits. Furthermore, studies by Zavela et al. and Brice et al. had small samples that did not completely represent the whole population and may therefore also be addressed as biased at some point. Nevertheless, despite the presented results, none of the researches, except for Benowitz et al. 2003) addressed the actual reason for the coffee/smoking relation. According to the researchers smokers prefer coffee due to the fact that smoking increases caffeine metabolism and coffee contains the highest its highest dose among all other beverages. In order to confirm the positive correlation between the amount of cigarettes smoked and coffee consumed it is important to research the reverse side of the relation. Do those people that quit smoking consume less coffee? Coffee and Smoking cessation Several studies review the relation between smoking cessation and coffee consumption andall of them reveal a positive correlation.
A cross-sectional study by Fernandez et al. described a total sample of 2621 respondents and found that lower coffee consumption was associated with quitting smoking. However, the results might be effect-modified as the health reasons for quitting where not taken into consideration during data collection. The research on smoking relapse conducted by Krall et al. revealed that people who quit smoking but where drinking at least 6 cups of coffee daily where 2. 33 times more likely to start smoking again. A similar study of 116 men by Kauffman et al. eviewed that those who don’t drink a lot of coffee where 12 times more likely to quit smoking successfully. Furthermore, education and age where identified as the factors positively affecting smoking cessation and where adjusted in order to make the effect of coffee consumption clearer. Coffee and alcohol Correlations between coffee consumption and alcohol consumption are mostly explained by ones attitude towards health. Therefore, usually alcohol drinkers are less concerned by their health and on average consume more coffee than non-drinkers.
Researches by Talcott et al. and Stevenson et al. prove this statement as according to their findings, alcohol drinkers were 1. 52 times more likely to drink coffee. Schwarz et al. investigated even further and researched the relation between different alcohol drinks with coffee and tea consumption in a sample of 2400 respondents aged from twenty five to sixty four. The findings of the authors revealed that among beer, wine and other beverages only wine had a positive correlation with coffee consumption. Again the above studies have some limitations as some of them o not reveal the health conditions of the respondents. As mentioned above health is a serious determinant that can affect both alcohol intake and coffee consumption. Furthermore, self-administered means of collecting information were used. Therefore, the collected data might be prone to bias. Coffee and physical activity The majority of the reviewed surveys associated high coffee consumption with low physical activity. According to the research by Hewlett et al. less coffee consumption was associated with being younger and a less than healthy lifestyle. Thune et al. onducted a survey with more than 10000 respondents that indicated that both males and females with sedentary jobs consumed more coffee than those that were physically more active. Therefore, coffee consumption may be associated with less leisure time activities and a sedentary job. It is important to mention the work of Mosdol et al. that researched how the changes in coffee consumption affected ones physical activity. The respondents were placed in three groups by coffee consumption. The first group didn’t drink coffee at all, the second consumed 1 to 3 cups per day and the third group drank at least 4 cups.
Furthermore, 3 physical activity level groups were established. The results revealed that those participants that increased the amount of cups consumed per day were less likely to do physical exercise. Therefore, the higher is the coffee intake, the less physically active an individual is. From the methodological point of view, the limitations of the mentioned above surveys where again connected to the fact that mostly the participants were asked to self-report their levels of physical activity and coffee consumption. Furthermore, the studies researched the relation between the two variables at a single point of time.
All of the limitations combined make it hard to identify the real connection between coffee consumption and physical activity. Coffee and Income It is evident that the relation between coffee consumption and income varies from region to region. Therefore, coffee consumption in some states comprises a significantly lower proportion of total consumption in comparison with other countries. Hewlett et al. (1990) identified that the income elasticity is positive and less than one for all of the goods investigated (coffee, tea, alcohol). Interestingly, the study by Varun et al. evealed that urban households purchase a larger amount of coffee and tea in contrast to rural households. Furthermore, total family income plays a more significant role in consumer decisions in urban areas, whereas family size was the major factor in rural areas. Conclusion Based on the reviewed literature most important coffee consumption determinants were identified. Therefore, a significant correlation between smoking and coffee consumption was found. Additional research revealed that smokers on average consume more than non-smokers and those who quit smoking.
Furthermore, the probability of smoking relapse was higher for those ex-smokers that consumed a higher amount of caffeine. The biological relation between coffee metabolism and smoking was recognized as one of the factors to explain the correlation. Coffee consumption and alcohol intake were linked to an individual’s personal healthcare choices. Therefore, high consumption of alcohol was correlated with an unhealthy lifestyle and consequently, with a higher consumption of coffee. Unhealthy lifestyle was also proved to be the factor relating coffee intake with lower physical activity.
Income and coffee consumption were proven to change from region to region, with people in urban areas with higher incomes drinking more coffee in comparison with the people in rural areas. Most importantly, a research gap was found. As can be seen from the above review, none of the researchers investigated coffee consumption patterns in Uzbekistan and almost none of them investigated university student’s coffee consumption behavior. Therefore, it is important to fulfill this gap and conduct a survey of coffee consumption patterns among students in Uzbekistan.
However, due to the scarcity of resources this research will focus on the coffee consumption determinants in Westminster International University in Tashkent (WIUT). Research question What are the main coffee consumption determinants for the students of the Westminster International University in Tashkent? Research objectives * To identify the main factors affecting coffee consumption behavior of WIUT students * To discover whether the findings about the positive relation between smoking and coffee consumption are applicable to WIUT tudents * To interpret the discovered relations between key determinants and coffee consumption Methodology Research approach and design During the research a quantitative approach was implemented. Given (2008) describes a quantitative research as an empirical investigation of a social phenomenon by the use of statistical, mathematical or computational techniques. Usually a quantitative approach is applied when it is necessary to statistically describe and test relations between certain variables and examine cause effect relations.
A descriptive (correlational) survey was used to collect primary data to describe the population. The descriptive survey interprets the relationships among a set of variables to develop trends and patterns in the data. Variables in this kind of a survey are not manipulated and are studied as they occur. The survey obtains data from a population sample by means of self-report, when participants respond to a number of questions identified by the researcher. In the current research, information was gathered by the use of self-administered questionnaires distributed online and individually for each participant.
A descriptive quantitative approach was applied because it helps to identify the causes of the interrelations in the variables. The main advantage of the employed approach is precision that is achieved through reliable quantitative measurement, when the collected data is not manipulated. However, there are some limitations due to the objectivity of self-reports, as respondents may provide the researcher with unauthentic information that is not accurate. Research setting
The study was conducted at the Westminster International University in Tashkent that is located in the highly dense urban area in the center of the capital of Uzbekistan. Approximately 1700 students and 90 teachers attend the university. The majority of the students are locals aged from 17 to 25, most of which are a registered in the Facebook social network. Study population and sample A population is a set of all the elements that come within the study sample criteria. The sampling frame consisted of young adults aged 17 to 23 that are full-time bachelor’s degree students who study on levels 3, 4, 5 or 6 of the university.
Master’s degree students and teachers were not included in the frame as they represent an older age group that does not fit into the aim of the research to study consumption patterns among students. Due to the lack of time, resources and the impossibility of implementation, the census approach, when data is collected from everyone in the population,was excluded from the research. Instead, the simple random sampling approach was applied. Under this approach the sample is collected by randomly choosing the respondents from the sampling frame.
The simple random sampling approach was used because the research sample size was equal to 300, the sample frame was easily accessible via the computer database, and interactions with the respondents were not an issue. The sample size decisions were based on a 95% confidence level that the data represents the characteristics of the whole population and the 3-5% acceptable margin of error that expresses the amount of random sampling error in the results. According to the optimal sample size calculations and the table adapted from Saunders et al. (2003, p. 56) and assuming a 100% response rate the optimal sample size was identified to be equal to 300. The collected sample was compared with the student statistics from the university and was provento represent the characteristics of the university population. Data Collection Data collection instrument A self-administered questionnaire was chosen as the data collection instrument for the research. A typical questionnaire is usually a mean of collecting primary data and consists of a series of questions that are aimed at gathering information from the respondents.
The decision to apply questionnaires as a data gathering tool was made largely due to the following factors: * High response rates as the questionnaires were distributed online via social networks and distributed to the respondents to complete and were consequently collected personally by the researcher * Less time and resources to administer, as all of the online replies where automatically monitored and both online and manual responses wereprocessed by computer software * Anonymity, as the respondents personal identification details (e. g. ame, student ID, etc) were not required * Less prone to bias as they were presented in a consistent manner * Most of the questions were closed, which made further statistical analysis easier However, the main disadvantage from the self-administered questionnaire is that it might not reflect the true state of the respondent and valuable information might be lost as the answers are usually brief. The questionnaire was conducted in English and consisted of two sections. Section 1 was aimed at getting demographic data such as age, gender, education years, religion, etc.
Section 2 mostly consisted of closed questions and was aimed at determining ones coffee consumption habits and related information. The examples of the questionnaire with instructions on how to complete it areprovided in Appendix 1. Data collection procedure The questionnaires were distributed in two ways: * Via social networks such as Facebook and Odnoklassniki * Personally to respondents at the university In order to avoid resemblance in the online and manual responses, the sample was divided into two groups by study level.
Therefore, the first group, consisting of level 5 and level 6 students was questioned online, whereas the level 3 and 4 students were asked to fill manual questionnaires. The data was collected in a one month period. Reliability and validity Reliability Reliability is a measure of consistency with which an instrument, in the case of the current research a questionnaire measures the attributes it was designed to measure. Therefore, a questionnaire may be assumed to be reliable if it will give the same results when applied to the same group of people.
The questionnaire was firstly pretested on a group of 50 people that answered the questionnaire twice in different environments, the results revealed consistency in responses. The two sets of responses can were compared statistically using weighted Kappa for categorical data and Spearman’s Rank Correlation Coefficient for continuous data. However, it is important to minimize measurement errors related to reliability. Hence, data collector bias was reduced by allocating two researchers to be the only ones to manage the questionnaire.
The environment where data was gathered was made comfortable by ensuring silence, privacy and confidentiality for the respondents. Validity In contrast to reliability validity is a measure of how a questionnaire is employed and refers the extent to which the questionnaire represents studied variables. In order to ensure validity, the questionnaire was based on the review of literature. In addition, all questionnaires distributed manually were delivered by the appointed administering researchers.
Furthermore, the questions were formulated in a simple language to assure clarity, guidelines were provided in order to ensure the ease of understanding the questions. The manual questionnaires were completed in the presence of the researchers to make sure that the questionnaires were not filled by third parties. However, it was hard to administer this aspect of the online questionnaire as the researchers were unable to monitor the process of filling. Ethical considerations In order to protect the human rights of the respondents, ethical aspects of the research were taken into consideration.
Therefore, before handling in the questionnaire the researchers informed the participants about the aims of the study. Anonymity and confidentiality were maintained, as the personal information of the respondents was not disclosed, and the collected information was kept confidential. Self-determination was sustained by providing the respondents with a choice on whether to participate in the research or not. Scientific honesty, being an important ethical part of the research was also maintained as the researchers and analysts did not manipulate, change or alter the collected data.
Conclusion The research implemented a descriptive, quantitative approach. Self-administered questionnaire was used to collect information from 300 respondents on the territory of the Westminster International University in Tashkent. The sample included young adults aged 17 to 23 studying on the levels 3,4,5 and 6 of the university. Reliability, validity and ethical considerations were taken into account while administering the research. Data Descriptive statistics and results are shown in Figure 1. Variable| Observations| Mean| Std. Dev. | Min| Max| | | | | | | ID| 297| 149| 85. 8073| 1| 297| age| 297| 20. 60269| 3. 388732| 16| 40| gender| 297| . 5454545| . 49877| 0| 1| marital| 297| . 0909091| . 287965| 0| 1| ethnicity| 297| . 8855219| . 3189284| 0| 1| | | | | | | religion| 296| . 9054054| . 2931498| 0| 1| city| 296| . 7668919| . 4235265| 0| 1| educyears| 296| 13. 93581| 2. 639838| 4| 45| Montly Income| 195| 575451. 3| 1027561| 0| 1. 00e+07| Work| 294| . 452381| . 4985759| 0| 1| | | | | | | Smoke| 297| . 2255892| . 4186752| 0| 1| Sport| 296| . 7466216| . 4356823| 0| 1| Drinking Coffee| 297| . 8114478| . 3918127| 0| 1| Coffee consumption| 283| 27. 9929| 34. 79035| 0| 225| Price Coffee| 266| 3449. 286| 4854. 957| 0| 18000| | | | | | | Weather| 296| . 5067568| . 500801| 0| 1| Morning| 296| . 5236486| . 5002862| 0| 1| Food| 296| . 5101351| . 5007438| 0| 1| Winter| 294| . 5816327| . 4941322| 0| 1| Company| 296| . 5236486| . 5002862| 0| 1| | | | | | | ln Income| 131| 13. 26666| . 8222373| 11. 51293| 16. 1181| LN Coffee| 259| 2. 844612| 1. 142757| 0| 5. 416101| LN Price| 242| 7. 805468| . 9738078| 2. 302585| 11. 0021| Figure 1 The sample collected was used with the help of the STATA statistical and econometrical tool.
Qualitative data representing dummy variables as religion, ethnicity, employment status, smoking habits, sport, marital status and all other vectors of dummy variables were transformed to quantitative data. The list of dummy variables and their quantitative meaning is represented in Figure 2. Variable| Observations| Represented as 1| Represented as 0| | | | | gender| 297| Male| Female| marital| 297| Married| Single/Widow| ethnicity| 297| Asian| Other| | | | | religion| 296| Muslim| Other| city| 296| Tashkent| Other| Work| 294| Employed| Unemployed| | | | | Smoke| 297| Smoker| Non-smoker|
Sport| 296| Sport| Non-sport| Drinking Coffee| 297| Coffee Drinker| Non-coffee drinker| | | | | Weather| 296| Weather Influence| Weather doesn't influence| Morning| 296| Morning hours preffered| No preference over time| Food| 296| Coffee consumed with food| No preference regarding food| Winter| 294| Winter time preffered| No preferene over time| | | | | Figure 2 As descriptive statistics show, the sample number was decreased to 297 due to the exclusion of some answers with irrelevant and unreal results, i. e. , those surveys that were spoiled by giving extraordinary high levels of coffee consumption or income.
Mean income of a WIUT students was estimated to be 575’451 UZS with the standard deviation of 1’072’000 UZS to both sides. Again, such a big dispersion indicates low reliability of the data that will be discussed further. The composition of the sample regarding gender, as well as with respect to age grouping and ethnicity is shown in Figures 3 to 8. Figure 4. Employment Status Figure 4. Employment Status Figure 3. Gender Distribution Figure 3. Gender Distribution Figure 6. Religion Figure 6. Religion Figure 5. Smoking habits Figure 5. Smoking habits Figure 8. Age distribution Figure 8. Age distribution Figure 7. Active Lifestyle Figure 7.
Active Lifestyle Estimation and Results Estimations were found using the method of weighted least squares and finding corresponding coefficients for respective variables. In order to avoid the problem of heteroscedascity, robust method of weighted least squares instead ordinary least squares method was applied. Nevertheless, in order to show the difference between ordinary least squares and weighted least squares methods both models were used in the results section. In Regression 1 Ordinary Least Squares Method was employed, while Regression 2 used the Weighted Least Squares Robust method to avoid the problem of heteroscedascity.
Furthermore, due to the existence of zero-expenditures problem in some cases and not giving accurate information regarding income of students all income information was respectively changed to logarithmic scale. Moreover, since coffee consumption is discrete, it was also changed to logarithmic scale in order to avoid zero expenditure problems during estimation. Therefore, the final model of weighted least squares model can be shown by the following function. lncoffee= ? +? logincome+jik+? where k is the j number of dummy variables such as city, ethnicity, education, gender, employment status, smokers and other variables described before.
As it was said usage of the logarithmic scale helps to avoid the issues associated with zero expenditure. Results. The following table shows estimates for both models using Weighted Least Squares and Ordinary Least Squares (Robust) methods. The difference between two model is not cardinal. The most obvious difference is in the estimations of standard error, since usage of the robust method gives smaller standard errors. Results found a vivid relationship between active lifestyle (sport) and drinking coffee. People who do sports tend to consume less coffee than those leading a less active lifestyle.
Furthermore, estimations revealed an interesting correlation for those individuals that are single. In this case, as it was said earlier dummy variable 1 represents a married person. Negative coefficient for marital status indicates that on average married people consume less coffee than singles or widows. In this case the reference group was singles and both coefficients were significant at 99% confidence level, rejecting null hypothesis that marital status and sport activities do not relate to coffee consumption among students of WIUT. | Regression 1| Regression 2| | coef| se| coef| se|
Age| 0,039| 0,027| 0,039*| 0,022| Gender(1/0)| -0,102| 0,205| -0,102| 0,218| Marital status (1/0)| -0,894***| 0,319| -0,894***| 0,269| Ethnicity| 0,163| 0,294| 0,163| 0,252| Religion| 0,117| 0,336| 0,117| 0,253| City where you were born:| -0,263| 0,219| -0,263| 0,209| Education years (school+ lyceum +university):| -0,007| 0,042| -0,007| 0,047| Do you have a part-time or full-time work? | 0,263| 0,190| 0,263| 0,224| Do you smoke? | 0,158| 0,244| 0,158| 0,238| Do you do sport? | -0,611***| 0,207| -0,611***| 0,198| Does weather influence your decision to drink coffee? 0,170| 0,186| 0,170| 0,203| Do you prefer to drink coffee in morning hours (7:00 to 11:00) or in any other t| 0,159| 0,198| 0,159| 0,234| Do you usually drink coffee with food/snack? | 0,212| 0,175| 0,212| 0,180| Do you drink more coffee during winter or any other period? | -0,239| 0,207| -0,239| 0,234| logincome| 0,230*| 0,121| 0,230*| 0,122| _cons| -0,730| 1,539| -0,730| 1,551| Number of observations| 119| 119| Adjusted R2| 0,136| 0,136| note: *** p;0. 01, ** p;0. 05, * p;0. 1| | | | With a smaller confidence level, the importance of income was proved.
In this case, positive coefficient of logincome with respect to logcoffee indicates that increase in income tend to result in an increase in coffee consumption. Furthermore, application of logarithmic scale as it was mentioned earlier, helped to avoid zero-expenditure problems, however shrank the available size of the sample down from 297 to 119. This occurred due to the responses of the participants who didn’t give correct responses on the income questions. Interestingly enough, results for age were important at 90% confidence interval while applying the robust method of standard error calculation.
All other dummy variables including weather, consumption of coffee with snack, employment status, city, religion are concluded to be insignificant. Conclusion and Recommendations As estimations have indicated some significant results were obtained particularly concerning the research proposal in determination of coffee consumption behavior at WIUT. Mainly, the importance of income and marital status, with sedentary lifestyle proved that WIUT student’s coffee consumption pattern and addictions were quite similar to those revealed in the study by Zavela.
The difference and usefulness of the results nevertheless might not be as good as it might have been in the case of a broader and better collected sample. First of all, collection of data not via survey, but corresponding actual spending on coffee and finding out total monthly expenditure would have been much more appropriate for the analysis. In that case, reliability of the data would be guaranteed and more precise results might be obtained. Also, quite limited and more or less similar population of WIUT population can’t be interpreted as proxy for any Uzbekistan university students, or even for Tashkent city students.
In order for the sample to be more representative data from each university should be collected using not a self-administered survey, but more fundamental methods. However, considering high cost and the lack of time, sufficient data collection might be a hard problem. Bibliography ------------------------------------------------- Brice C. F. and Smith A. P. (2002). Factors associated with caffeine consumption. International Journal of Food Sciences and Nutrition, 53, 55-64. Current Worldwide Annual Coffee Consumption per capita. (n. d. ). ChartsBin. com - Visualize your data. Retrieved March 11, 2013, from http://chartsbin. om/view/581 Fernandez E. , Vecchia C. L. , Avanzo B. D. , Braga C. , Negri E. and Franceschi S. (1997). Quitting smoking in Northern Italy: A cross-sectional analysis of 2621 subjects. European Journal of Epidemiology, 13, 267-273. Given, L. M. (2008). The Sage encyclopedia of qualitative research methods. Los Angeles, Calif. : Sage Publications. ------------------------------------------------- Hewlett, P. , & Wadsworth, E. (2013). Tea, coffee and associated lifestyle factors. British Food Journal, 114(3), 416-427. ------------------------------------------------- John K. Francis. "Coffeaarabica L. RUBIACEAE".
Factsheet of U. S. Department of Agriculture, Forest Service. Retrieved 2007-07-27. ------------------------------------------------- Kauffman R. M. , Ferketich A. K. , Wee A. G. , Shultz J. M. , Kuun P. and Wewers M. E. (2008). Factors associated with smokeless tobacco cessation in an Appalachian population. Addictive Behaviors, 33, 821-830. ------------------------------------------------- Klesges R. C. , Ray J. W. and Klesges L. M. (1994). Caffeinated coffee and tea intake and its relationship to cigarette smoking: An analysis of the second national health and nutrition examination survey (NHANES II).
Journal of Substance Abuse, 6, 407-418. Koksal, A. , ;Wohlgenant, M. (2011). RATIONALLY ADDICTED TO CIGARETTES, ALCOHOL AND COFFEE? A PSEUDO PANEL APPROACH . Department of Agricultural and Resource Economics, North Carolina State University , 1, 1-21. Krall E. A. , Garvey A. J. and Garcia R. I. (2002). Smoking relapse after 2 years of abstinence: findings from the VA normative aging study. Nicotine and Tobacco Research, 4, 95-100. Krall E. A. , Garvey A. J. and Garcia R. I. (2002). Smoking relapse after 2 years of abstinence: findings from the VA normative aging study.
Nicotine and Tobacco Research, 4, 95-100. ------------------------------------------------- Matter, S. (n. d. ). Coffee in Uzbekistan. Global Market Research and Analysis for Industries, Countries, and Consumers. Retrieved March 11, 2013, from http://www. euromonitor. com/coffee-in-uzbekistan/report Mosdol A. , Christenseen B. , Retterstol L. and Thelle D. S. (2002). Induced changes in the consumption of coffee alter ad libitum dietary intake and physical activity level. British Journal of Nutrition, 87, 261-266. Salazar-Martinez E. , Willett W. C. , Ascherio A. Manson J. E. , Leitzmann M. F. , Stampfer M. J. and Hu F. B. (2004). Coffee consumption and risk for type 2 diabetes mellitus. Annals of Internal Medicine, 140, 1-8. Saunders, M. (2003). Research methods for business students. Harlow, England New York: Prentice Hall. Schwarz B. , Bischof H. P. and Kunze M. (1994). Coffee, Tea and Lifestyle. Preventive Medicine, 23, 377-384 Stevenson J. S. and Masters J. A. (2005). Predictors misuse and abuse in older women. Journal of Nursing Scholarship, 37(4), 329-335. Talcott G. W. , Poston W. S. C. II and Haddock C. K. (1998).
Co-occurrent use of cigarettes, alcohol, and caffeine in a retired military population. Military Medicine, 163, 133-138. Thune I. , Njolstad I. , Lochen M. L. and Forde O. H. (1998). Physical activity improves the metabolic risk profiles in men and women. Archives of Internal Medicine, 158, 1633-1640. ------------------------------------------------- VARUN, T. (2008). CONSUMPTION BEHAVIOUR OF COFFEE AND TEA IN KARNATAKA. Thesis submitted to the University of Agricultural Sciences, 1, 1-95. Appendix 1 Questionnaire instructions. For the researchers when introducing the survey to the respondents Dear Mr/Ms __________
As a part of our coursework on Research Methods, we were assigned to conduct a research on coffee consumption among students in WIUT. As part of the research we composed a questionnaire in order to identify your coffee consumption patterns. The questionnaire is anonymous and confidential. No personal information is required. Could you please take your time and answer the questions 1 to 16? Instructions on how to complete the questionnaire The questionnaire is confidential. No name or ID is required. Please fill in the personal information box first. Pay attention to the guidelines in the brackets after the questions.
In the education years line please fill in the years you spent at school, lyceum or university either combined or separately. Yes/No questions have an additional field for commentaries. Fill in the comments section only if you have any additional information to share. Coffee questionnaire The questionnaire is confidential. No name or ID is required. Please fill in the personal information box first. Pay attention to the guidelines in the brackets after the questions. In the education years line please fill in the years you spent at school, lyceum or university either combined or separately.
Yes/No questions have an additional field for commentaries. Fill in the comments section only if you have any additional information to share. | Personal information: Age:| ????? | Gender (Male/Female):| ????? | Marital status (Married/Single):| ????? | Ethnicity: | ????? | Religion:| ????? | City where you were born:| | Education years (school+ lyceum +university):| ????? | Monthly income (in UZS):| ????? | | Criteria| Yes/No| Comments| 1| Do you have a part-time or full-time work? | Yes No| ????? | 2| Do you smoke? | Yes No| | 3| Do you do sport? | Yes No| ????? | 4| Do you drink coffee? YesNo| ????? | 5| How much coffee do you consume per month? (in cups)| | 6| How much do you usually pay for a cup of coffee? (UZS per cup)| | 7| How much are you willing to pay for a cup of coffee? (UZS per cup)| ????? | 8| Does weather influence your decision to drink coffee? | Yes No| ????? | 9| Do you prefer to drink coffee in morning hours (7:00 to 11:00) or in any other time? ( Yes for morning hours, No for any other)| Yes No| ????? | 10| Other than coffee, which hot/cold beverages do you regularly purchase? | | 11| How much do you usually pay for a cup of tea? UZS per cup)| ????? | 12| How much are you willing to pay for a cup of tea? (UZS per cup)| ????? | 13| Do you usually drink coffee with food/snack? (Yes if you do, No if you don’t)| Yes No| ????? | 14| Do you drink coffee during winter or any other period? (Yes for Winter, No for other)| Yes No| ????? | 15| Do you usually drink coffee while you are with friends/company or alone? (Yes with friends/company, No alone)| Yes No| ????? | 16| Do you prefer university coffee or any other coffee outside? ( Yes for university, No for outside)| Yes No| ????? | Any other comments: ????? | |