DOCSLIB.ORG

Directory of Public Use Data on Tobacco Use in Canada

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Directory of Public Use Data on Tobacco Use in Canada Directory of Public Use Data on Tobacco Use in Canada June 2015 A project of the Ontario Tobacco Research Unit. Table of Contents ACKNOWLEDGEMENTS ........................................................................................................... iv INTRODUCTION .......................................................................................................................... 1 DATA SOURCES ........................................................................................................................... 2 Statistics Canada..................................................................................................................................... 2 Statistics Canada Website .................................................................................................................................... 2 The Daily ......................................................................................................................................................... 2 Summary Tables .............................................................................................................................................. 2 Community Profiles ........................................................................................................................................ 2 The Census ...................................................................................................................................................... 2 CANSIM Database .......................................................................................................................................... 2 Publications by Statistics Canada .................................................................................................................... 3 Health Indicators ............................................................................................................................................. 3 Data Liberation Initiative (DLI) ........................................................................................................................... 3 Custom Data Orders ............................................................................................................................................. 3 Research Data Centres (RDCs) ............................................................................................................................ 3 Depository Services Program (DSP) ..................................................................................................... 3 CADRISQ ................................................................................................................................................ 4 Canadian Opinion Research Archive (CORA) .................................................................................... 4 Institute for Social Research (ISR) ....................................................................................................... 4 Inter-University Consortium for Political and Social Research (ICPSR) ......................................... 4 Ontario Data Documentation Extraction Service and Infrastructure (ODESI) ............................... 4 Population Health Data Repository (PHDR) ....................................................................................... 5 Social Program Evaluation Group (SPEG) .......................................................................................... 5 Tobacco Informatics Monitoring System (TIMS) ............................................................................... 5 Other Websites ........................................................................................................................................ 6 Centers for Disease Control and Prevention (CDC)............................................................................................. 6 National Technical Information Service (NTIS) .................................................................................................. 6 Roper Center for Public Opinion Research .......................................................................................................... 6 Marketing and Survey Research Companies ....................................................................................... 6 Gallup Canada Inc. ............................................................................................................................................... 6 Hill and Knowlton ................................................................................................................................................ 6 Ipsos Reid Group, Inc. ......................................................................................................................................... 6 PUBLIC USE DATA ON TOBACCO USE IN CANADA ........................................................... 7 Aboriginal Peoples Survey (1991, 2001, 2006, 2012) ......................................................................... 14 Attitudes Toward Restrictions on Smoking, Ontario (1983, 1991)* ................................................ 18 Attitudes Toward Smoking in Brant County (1994)* ....................................................................... 21 CAMH Monitor (1977-2014)* ............................................................................................................. 22 Campbell’s Survey on Well-Being in Canada* (1988) ...................................................................... 26 Canada Fitness Survey* (1981) ........................................................................................................... 29 i Canada Health Monitor (1988 – 1998)................................................................................................ 31 Canada Health Survey (1978) .............................................................................................................. 36 Canada’s Alcohol and Other Drugs Survey (CADS) (1994) ............................................................. 39 Canadian Addiction Survey (CAS) (2004) ......................................................................................... 42 Canadian Alcohol and Drug Use Monitoring Survey (CADUMS)(2008-2012) .............................. 44 Canadian Community Health Survey (CCHS) (2000-2014) ............................................................. 46 Canadian Gallup Poll (1951, 1956-1957, 1963-1964, 1971, 1974, 1976-1979, 1981- 2000) ............. 60 Canadian Health Measures Survey [(2007-2009 (cycle 1); 2009-2011 (cycle 2); 2012-2013 (cycle 3)] ........................................................................................................................................................... 61 Canadian Heart Health Databases (1986-1992) ................................................................................. 63 Canadian Tobacco Use Monitoring Survey (CTUMS) (1999-2012) ................................................ 65 Community Intervention Survey (1994)* ........................................................................................... 71 CROP ..................................................................................................................................................... 73 Cultural Factors in Tobacco Use Among Ethnic Groups in Toronto (1996)* ................................ 74 Decima Quarterly (1980-1995) ............................................................................................................ 76 Environics Environmental Monitor (1987-1992, 1994-2001) ............................................................ 77 Environics Focus Canada (1977-1988, 1991-1994, 1996-1999, 2001, 2003-2005, 2007) .................. 78 Evaluation of the Workplace Smoking Bylaw in the City of Toronto (1988)*................................ 79 General Social Survey (1985, 1991,1995, 1996, 2007) ........................................................................ 81 Health Activity and Limitation Survey (HALS) (1986, 1991) .......................................................... 85 Health Behaviours in School-Aged Children (HBSC) (1989/1990, 1993/1994, 1997/1998, 2001/2002, 2005/2006, 2009/2010, 2014) .............................................................................................. 86 Health Canada: Smoking in BC and NL (2005) ................................................................................ 92 Health Canada: Smoking in QC, ON and SK (2005) ........................................................................ 93 Health Promotion Survey (HPS) (1985, 1990) (Montreal and NWT, 1986) .................................... 94 International Youth Survey (2006) ..................................................................................................... 99 Joint Canada/United States Survey of Health (JCUSH) (2003) ..................................................... 100 Maternity Experiences Survey (MES) (2006) .................................................................................. 102 National Alcohol and Drug Survey (NADS) (1989) ......................................................................... 104 National Angus Reid Poll (1991, 1994-1995) .................................................................................... 107 National Longitudinal Survey of Children and Youth (NLSCY) (1994, 1996, 1998, 2000, 2002, 2004, 2006, 2008) ................................................................................................................................
Load more

Recommended publications
  • 10 Questions Opinion Polls
    Questions you might have on 10opinion polls 1. What is an opinion poll? An opinion poll is a survey carried out to measure views on a certain topic within a specific group of people. For example, the topic may relate to who Kenyans support in the presidential race, in which case, the group of people interviewed will be registered voters. 2. How are interviewees for an opinion poll selected? The group of people interviewed for an opinion poll is called a sample. As the name suggests, a sample is a group of people that represents the total population whose opinion is being surveyed. In a scientific opinion poll, everyone has an equal chance of being interviewed. 3. So how come I have never been interviewed for an opinion poll? You have the same chance of being polled as anyone else living in Kenya. However, chances of this are very small and are estimated at about 1 in 14,000. This is because there are approximately 14 million registered voters in Kenya and, for practical and cost reasons, usually only between 1,000 and 2,000 people are interviewed for each survey carried out. 4. How can such a small group be representative of the entire population? In order to ensure that the sample/survey group is representative of the population, the surveyors must ensure that the group reflects the characteristics of the whole. For instance, to get a general idea of who might win the Kenyan presidential election, only the views of registered voters in Kenya will be surveyed as these are the people who will be able to influence the election.
    [Show full text]
  • Random Selection in Politics
    Random selection in politics Lyn Carson and Brian Martin Published in 1999 by Praeger Publishers, Westport, CT Available for purchase from Praeger This is the text submitted to Praeger in February 1999. It differs from the published version in minor ways, including formatting, copy-editing changes, page numbering (100 pages instead of 161) and omission of the index. This version prepared August 2008 Contents 1. Introduction 1 2. Random selection in decision making 10 3. Direct democracy 26 4. Citizen participation without random selection 36 5. Citizen participation with random selection: the early days 43 6. Citizen participation with random selection: yesterday, today, and tomorrow 52 7. Sortition futures 65 8. Strategies 76 Appendix: Examples of citizen participation 84 Bibliography 93 Acknowledgments Brownlea, John Burnheim, Ned Crosby, Many people we’ve talked to find the Jim Dator, Mary Lane, Marcus Schmidt, idea of random selection in politics and Stuart White. Their input was unnatural and unwelcome. This didn’t valuable even when we decided on an deter us! Fortunately, there were a few alternative approach. Helpful comments enthusiasts who got and kept us going. were also received from Ted Becker, Alan Davies, Fred Emery, and Merrelyn Stephen Healy, Lars Klüver, and Ken Emery provided the original inspiration Russell. Others who provided many years ago as well as ongoing information are acknowledged in the conversations. text. The process of obtaining comments Ted Becker encouraged us to write has been stimulating because not all this book. On drafts, we received readers go with us all the way on extensive comments from Arthur randomness.
    [Show full text]
  • 13 Collecting Statistical Data
    13 Collecting Statistical Data 13.1 The Population 13.2 Sampling 13.3 Random Sampling 1.1 - 1 • Polls, studies, surveys and other data collecting tools collect data from a small part of a larger group so that we can learn something about the larger group. • This is a common and important goal of statistics: Learn about a large group by examining data from some of its members. 1.1 - 2 Data collections of observations (such as measurements, genders, survey responses) 1.1 - 3 Statistics is the science of planning studies and experiments, obtaining data, and then organizing, summarizing, presenting, analyzing, interpreting, and drawing conclusions based on the data 1.1 - 4 Population the complete collection of all individuals (scores, people, measurements, and so on) to be studied; the collection is complete in the sense that it includes all of the individuals to be studied 1.1 - 5 Census Collection of data from every member of a population Sample Subcollection of members selected from a population 1.1 - 6 A Survey • The practical alternative to a census is to collect data only from some members of the population and use that data to draw conclusions and make inferences about the entire population. • Statisticians call this approach a survey (or a poll when the data collection is done by asking questions). • The subgroup chosen to provide the data is called the sample, and the act of selecting a sample is called sampling. 1.1 - 7 A Survey • The first important step in a survey is to distinguish the population for which the survey applies (the target population) and the actual subset of the population from which the sample will be drawn, called the sampling frame.
    [Show full text]
  • MRS Guidance on How to Read Opinion Polls
    What are opinion polls? MRS guidance on how to read opinion polls June 2016 1 June 2016 www.mrs.org.uk MRS Guidance Note: How to read opinion polls MRS has produced this Guidance Note to help individuals evaluate, understand and interpret Opinion Polls. This guidance is primarily for non-researchers who commission and/or use opinion polls. Researchers can use this guidance to support their understanding of the reporting rules contained within the MRS Code of Conduct. Opinion Polls – The Essential Points What is an Opinion Poll? An opinion poll is a survey of public opinion obtained by questioning a representative sample of individuals selected from a clearly defined target audience or population. For example, it may be a survey of c. 1,000 UK adults aged 16 years and over. When conducted appropriately, opinion polls can add value to the national debate on topics of interest, including voting intentions. Typically, individuals or organisations commission a research organisation to undertake an opinion poll. The results to an opinion poll are either carried out for private use or for publication. What is sampling? Opinion polls are carried out among a sub-set of a given target audience or population and this sub-set is called a sample. Whilst the number included in a sample may differ, opinion poll samples are typically between c. 1,000 and 2,000 participants. When a sample is selected from a given target audience or population, the possibility of a sampling error is introduced. This is because the demographic profile of the sub-sample selected may not be identical to the profile of the target audience / population.
    [Show full text]
  • Third Party Election Spending and the Charter
    ELECTIONSPENDING AND THE CHARTER 429 LIBERTE, EGALITE, ARGENT: THIRD PARTY ELECTION SPENDING AND THE CHARTER 0 ANDREW GEDDIS Both the federal government and the courts have le gouvernementfederal et /es cours de Justice ont brought about changes in election law. The author apportedes modificationsa la loi electorate.l 'auteur reviews these recent changes In the legal landscape revolt le.r recents changementsdans le cadre legal that surroundelection mies. Inparticular third party entourant/es reg/es electorates, tout particulierement electionspending. Thequestions of "whatrules exist" /es depenseselectorates de tiers. la question,a savoir and "who shall make them" are particularly « quelles sont les reg/es qui existent II et « qui les importantto the discussionas this area of law tries to me/Ira en place ,, est particulierement importante reconcile individual interestsin liberty and equality dans celle discussionetant donne que ce domainedu in a democracy.The trio of SupremeC our/ of Canada droit teme de reconcilierles interets individuelset la decisions, Libman v. Quebec (A.G.), Thomson notion de liberte et d'egalite d'une democralie.Les Newspapersv. Canada (A.G.) and Sauve v. Canada trois dkisions de la Cour supreme du Canada. (Chief Electoral Officer), reveal ambiguity In the notamment Libman c. le Quebec (A.G.). Thomson Court's rationalefor limiting Individual liberty at Newspapersc. le Canada (A.G.)et Sauve c. le Canada electiontime. Thisambiguity Is broachedIn the recent (Directeur general des elections), manlfestent Supreme Court of Canada case of Harper v. Canada I 'amblg1111erelativement au raisonnementde la Cour (A.G.)where the Courtaccepted that Parliamentmay de limiter la liberte individuellependant un scrutm.
    [Show full text]
  • Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25Th Congressional Election
    Rochester Institute of Technology RIT Scholar Works Theses 12-23-2014 Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election Heather Knappen Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Knappen, Heather, "Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election" (2014). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election By Heather Knappen A Thesis Submitted in Partial Fulfillment of the Graduation Requirements for the Degree of Master of Science Department of Science, Technology and Public Policy College of Liberal Arts Rochester Institute of Technology Rochester, New York December 23, 2014 II Capturing the Effects of Public Opinion Polls on Voter Support in the NY 25th Congressional Election by Heather Knappen Masters of Science Science, Technology and Public Policy Thesis Submitted in Partial Fulfillment of the Graduation Requirements for the College of Liberal Arts/Public Policy Program at ROCHESTER INSTITUTE OF TECHNOLOGY Rochester, New York June 2014 Submitted by: Heather Knappen Signature Date Accepted by: Ron Hira, Thesis Advisor Department of Public Policy, R.I.T Signature Date Franz Foltz, Committee Member Department of Public Policy, R.I.T Signature Date Eric Hittinger, Committee Member Department of Public Policy, R.I.T Signature Date III Table of Contents Abstract ..........................................................................................................................................
    [Show full text]
  • 8 Analyzing and Interpreting Polls
    8 Analyzing and Interpreting Polls Thus far, we have considered how public opinion surveys are conducted, how they are reported in the media, and how they influence elections and campaigns. This chapter focuses on the end products of public opinion surveys: the analysis and interpretation of poll data. Interpreting a poll is more an art than a science, even though statistical analysis of poll data is central to the enterprise. An investigator examining poll results has tremendous leeway in deciding which items to analyze, which sample subsets or breakdowns to present, and how to interpret the statistical results. Take, as an example, a poll with three items that mea- sure attitudes toward stem cell research. The investigator may construct an index from these three items, as discussed in Chapter 3. Or the inves- tigator may emphasize the results from one question, perhaps because of space and time constraints and the desire to keep matters simple or because those particular results best support the analyst’s own policy pref- erences. Another possibility is to examine the results from the entire sam- ple and ignore subgroups whose responses deviate from the overall pattern. Again, time and space limitations or the investigator’s own pref- erences may influence the choices. Finally, two investigators may interpret identical poll results in sharply different ways depending on the perspec- tives and values they bring to their data analysis; the glass may be half full or half empty. The analysis and interpretation of poll data entail a high degree of Dosubjectivity not and judgment.copy, Subjectivity, post, in this or context, distribute does not mean deliberate bias or distortion but simply professional judgments about the importance and relevance of information.
    [Show full text]
  • Handout 6: Summarizing Categorical Data with Counts and Relative Frequencies STAT 100 – Spring 2016
    Handout 6: Summarizing Categorical Data with Counts and Relative Frequencies STAT 100 – Spring 2016 In this handout, we will consider some methods that are appropriate for summarizing data measured on categorical variable(s). Definition Categorical Data: A set of measurements that take on values that are one of several possible categories. Example: Poll on Immigration Reform Between January 31 and February 2, 2014, a CNN/ORC opinion poll surveyed a random sample of 1,010 adults nationwide. Respondents were asked the following question: “What should be the main focus of the U.S. government in dealing with the issue of illegal immigration: developing a plan that would allow illegal immigrants who have jobs to become legal U.S. residents, or developing a plan for stopping the flow of illegal immigrants into the U.S. and for deporting those already here?” FREQUENCIES AND RELATIVE FREQUENCIES In this example, one categorical variable of interest is the opinion of each respondent (i.e., whether they answered Legal residency, Stop flow/deport, or Unsure). Our first step in organizing these data is to count how often each value occurs. These counts are shown in the following table. Count Legal residency 548 Stop flow/deport 412 Unsure 50 Total 1,010 Next, instead of reporting the number of responses that fell in each category, calculate the percentage of responses in each category. Find these percentages and put them in the table below. Count Percentage Legal residency 548 Stop flow/deport 412 Unsure 50 Total 1,010 1 Handout 6: Summarizing Categorical Data with Counts and Relative Frequencies STAT 100 – Spring 2016 Counts and percentages of this kind have formal names in statistics: Definitions Frequency: This is the number of times that a value occurs in a data set (i.e., the count).
    [Show full text]
  • The Science of Opinion Polls, Lesson Plan
    Oireachtas education Senior cycle Politics and society The science of opinion polls Lesson plan Leaving certificate Politics and Society: Objective 9 - “develop the capacity to analyse and interpret qualitative and quantitative social and political research data and to use such data carefully in forming opinions and coming to conclusions”. This exercise would take three classes and ideally would include a double class. Learning intentions Co-curricular At the end of the lesson students will understand English (social and media literacy) • what people need to consider when Mathematics (ability to interpret and evaluating public opinion polls analyse data) • how to examine how polling is conducted and analyse current polls • how to develop political literacy Resources Film: We the Voters - The Poll https://vimeo.com/180771527 Dance Pew Research Center - Why 2016 https://www.youtube.com/watch?v=sfBAPn7-hDg election polls missed their mark Ted-Ed - Pros and cons of public https://www.youtube.com/watch?time_continue=3&v=u opinion polls bR8rEgSZSU DNews - What is the Science https://www.youtube.com/watch?v=LbzYKfUpG7o Behind Polls? Oireachtas education | Lesson plan: The science of opinion polls 1 Oireachtas education Senior cycle Introduction Ask students either who their favourite musician is, or what their favourite food is. Write responses on the board and ask the class to vote on one. Ask them if they could expect to get the same result if they asked all the students in the school? Everyone in the province? The whole country? Let them know that they are going to take a deeper look at public opinion research and polling.
    [Show full text]
  • Changing Attitudes Toward the COVID-19 Vaccine Among North Carolina Participants in the COVID-19 Community Research Partnership
    Project Report Changing Attitudes toward the COVID-19 Vaccine among North Carolina Participants in the COVID-19 Community Research Partnership Chukwunyelu H. Enwezor 1,* , James E. Peacock, Jr. 1, Austin L. Seals 2, Sharon L. Edelstein 3, Amy N. Hinkelman 4 , Thomas F. Wierzba 1, Iqra Munawar 1, Patrick D. Maguire 5, William H. Lagarde 6, Michael S. Runyon 7, Michael A. Gibbs 7, Thomas R. Gallaher 8, John W. Sanders III 1,† and David M. Herrington 2,† 1 Department of Internal Medicine, Section on Infectious Diseases, Wake Forest School of Medicine, Winston-Salem, NC 27517, USA; [email protected] (J.E.P.J.); [email protected] (T.F.W.); [email protected] (I.M.); [email protected] (J.W.S.III) 2 Department of Internal Medicine, Section on Cardiovascular Medicine, Wake Forest School of Medicine, Winston-Salem, NC 27517, USA; [email protected] (A.L.S.); [email protected] (D.M.H.) 3 Biostatistics Center, George Washington University Milken School of Public Health, Washington, DC 20052, USA; [email protected] 4 Jerry M. Wallace School of Osteopathic Medicine, Campbell University, Lillington, NC 27546, USA; [email protected] 5 New Hanover Regional Medical Center, Wilmington, NC 28401, USA; [email protected] 6 Citation: Enwezor, C.H.; Peacock, Wake Med Health and Hospitals, Raleigh, NC 27610, USA; [email protected] 7 J.E., Jr.; Seals, A.L.; Edelstein, S.L.; Atrium Health, Charlotte, NC 28204, USA; [email protected] (M.S.R.); Hinkelman, A.N.; Wierzba, T.F.; [email protected] (M.A.G.) 8 Vidant Health, Greenville, NC 27834, USA; [email protected] Munawar, I.; Maguire, P.D.; Lagarde, * Correspondence: [email protected] W.H.; Runyon, M.S.; et al.
    [Show full text]
  • Random Sampling Random Sampling – a Guide for Teachers (Years 11–12)
    1 Supporting Australian Mathematics Project 2 3 4 5 6 12 11 7 10 8 9 A guide for teachers – Years 11 and 12 Probability and statistics: Module 23 Random sampling Random sampling – A guide for teachers (Years 11–12) Dr Sue Finch, University of Melbourne Professor Ian Gordon, University of Melbourne Editor: Dr Jane Pitkethly, La Trobe University Illustrations and web design: Catherine Tan, Michael Shaw Full bibliographic details are available from Education Services Australia. Published by Education Services Australia PO Box 177 Carlton South Vic 3053 Australia Tel: (03) 9207 9600 Fax: (03) 9910 9800 Email: [email protected] Website: www.esa.edu.au © 2013 Education Services Australia Ltd, except where indicated otherwise. You may copy, distribute and adapt this material free of charge for non-commercial educational purposes, provided you retain all copyright notices and acknowledgements. This publication is funded by the Australian Government Department of Education, Employment and Workplace Relations. Supporting Australian Mathematics Project Australian Mathematical Sciences Institute Building 161 The University of Melbourne VIC 3010 Email: [email protected] Website: www.amsi.org.au Assumed knowledge ..................................... 4 Motivation ........................................... 4 Content ............................................. 6 Random sampling in finite populations ......................... 6 Mechanisms for generating random samples ...................... 8 Populations and sample frames .............................
    [Show full text]
  • 1 Public Opinion Polls Wolfgang Donsbach Dresden University of Technology [email protected] 5,615 Words Abstract T
    In: Gianpietro Mazzoleni (ed.) (2014): Encyclopedia of Political Communication. Malden et al: Wiley (in preparation) Public Opinion Polls Wolfgang Donsbach Dresden University of Technology [email protected] 5,615 Words Abstract The entry describes the methodological and theoretical foundations as well as some societal and political issues around public opinion polls. After a brief historical account of the elements that have led to modern public opinion research the entry addresses problems of validity and accuracy, particularly in the context of election polls. The author then describes citizens’ relationship to the polls in terms of their cooperativeness and in terms of possible effects of published opinion polls on the electorate. The use of polls by politicians and governments is regarded under the notion of ‘responsiveness’. The entry concludes with a critical outlook on the future of opinion polls in democracies. Main text The term ‘public opinion poll’ describes a social research method used to measure the opinion of the citizens via interviews with representative samples of the whole population. The terms “opinion poll”, “survey” or “survey research” are often used as synonyms because some authors want to avoid the term “public opinion” because of its ambiguous connotation in the social sciences and political philosophy (see below). Most scholars would agree that a public opinion poll is defined by three criteria, each of which follows from the three terms. First, the term “public” indicates that survey questions relate in their majority to public issues ( public affairs), i.e. topics that are of relevance to the wider community and discussed in the public sphere, particularly in the news media.
    [Show full text]