The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who do and do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Units (PSUs) and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort.Please refer to the Public-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Wave 4.5 was a special data collection for youth only who were aged 12 to 17 at the time of the Wave 4.5 interview. Wave 4.5 was the fourth annual follow-up wave for those who were members of the Wave 1 Cohort. For those who were sampled at Wave 4, Wave 4.5 was the first annual follow-up wave.Wave 5.5, conducted in 2020, was a special data collection for Wave 4 Cohort youth and young adults ages 13 to 19 at the time of the Wave 5.5 interview. Also in 2020, a subsample of Wave 4 Cohort adults ages 20 and older were interviewed via the PATH Study Adult Telephone Survey (PATH-ATS).Wave 7.5 was a special collection for Wave 4 and Wave 7 Cohort youth and young adults ages 12 to 22 at the time of the Wave 7.5 interview. For those who were sampled at Wave 7, Wave 7.5 was the first annual follow-up wave. Dataset 1002 (DS1002) contains the data from the Wave 4.5 Youth and Parent Questionnaire. This file contains 1,395 variables and 13,131 cases. Of these cases, 11,378 are continuing youth having completed a prior Youth Interview. The other 1,753 cases are "aged-up youth" having previously been sampled as "shadow youth." Datasets 1112, 1212, and 1222, (DS1112, DS1212, and DS1222) are data files comprising the weight variables for Wave 4.5. The "all-waves" weight file contains weights for participants in the Wave 1 Cohort who completed a Wave 4.5 Youth Interview and completed interviews (if old enough to do so) or verified their information with the study (if not old enough to be interviewed) in Waves 1, 2, 3, and 4. There are two separate files with "single wave" weights: one for the Wave 1 Cohort and one for the Wave 4 Cohort. The "single-wave" weight file for the Wave 1 Cohort contains weights for youth who completed an interview in Wave 1 an

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population (CNP) at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the CNP at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the CNP at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This "second replenishment sample" was combined for estimation and analysis purposes with the Wave 7 adult and youth respondents from the Wave 4 Cohorts who were at least age 15 and in the CNP at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Dataset 0002 (DS0002) contains the data from the State Design Data. This file contains 7 variables and 82,139 cases. The state identifier in the State Design file reflects the participant's state of residence at the time of selection and recruitment for the PATH Study. Dataset 1011 (DS1011) contains the data from the Wave 1 Adult Questionnaire. This data file contains 2,021 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1012 (DS1012) contains the data from the Wave 1 Youth and Parent Questionnaire. This file contains 1,431 variables and 13,651 cases. Dataset 1411 (DS1411) contains the Wave 1 State Identifier data for Adults and has 5 variables and 32,320 cases. Dataset 1412 (DS1412) contains the Wave 1 State Identifier data for Youth (and Parents) and has 5 variables and 13,651 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state Federal Information Processing System (FIPS), state abbreviation, and full name of the state). The State Identifier values in these datasets represent participants' state of residence at the time of Wave 1, which is also their state of residence at the time of recruitment. Dataset 1611 (DS1611) contains the Tobacco Universal Product Code (UPC) data from Wave 1. This data file contains 32 variables and 8,601 cases. This file contains UPC values on the packages of tobacco products used or in the possession of adult respondents at the time of Wave 1. The UPC values can be used to identify and validate the specific products used by respondents and augment the analyses of the characteristics of tobacco products used

The Population Assessment of Tobacco and Health (PATH) Study is a nationally representative longitudinal cohort study of tobacco use and how it affects the health of people in the United States. It was launched in 2011 as a collaboration between the National Institutes of Health (NIH) and the Food and Drug Administration (FDA); data collection began in 2013 and is planned through 2024. Participants were recruited by a stratified address-based, area-probability sampling design, oversampling adult tobacco users, young adults (18–24 years), and African American adults. For the baseline wave (Wave 1), the study sampled over 150,000 mailing addresses across the United States to create the national sample of tobacco users and non-users. At Waves 4 and 7, probability samples were recruited from residential addresses not selected during previous waves in the same sampled Primary Sampling Units (PSUs) and segments using similar within-household procedures; these "replenishment samples" were combined for estimation and purposes with adult and youth respondents from their respective waves.

Each case in an Adult data file represents a single, completed interview. Each case in a Youth data file represents one youth and his or her parent's responses about that youth. When multiple youth from the same household were selected to be in the study, the parent(s) completed separate interviews about each youth. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Respondents are asked to complete an interview at each follow-up wave. Additionally, "shadow youth" (youth ages 9 to 11 sampled at Wave 1) are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. Adult interviews covered use of tobacco and nicotine products, peer and family opinions of tobacco use, health and quality of life outcomes, and tobacco product advertising. Youth interviews also included questions about media use and use of other substances; parents were asked about their youth's home and school life as well as their own use of tobacco products.

Questions about the collection, content, weighting, documentation, or structure of PATH Study data may be submitted to PATHDataUserQuestions@Westat.com. NOTE: This email address is not for questions about statistical analysis or analytic guidance. For analytic questions, researchers may wish to consult with statisticians and analysts at their institutions.

The Population Assessment of Tobacco and Health (PATH) Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study was launched in 2011 to inform the FDA's tobacco regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). For Wave 1 (baseline), the PATH Study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco, yielding interviews with 45,971 adult and youth respondents. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent.At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled PSUs and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.Biospecimen Collection Each adult respondent, who completed the interview at Wave 1, was asked to provide at least two biospecimens. Providing biospecimens was voluntary and was not a condition of participation. Respondents were asked to report their use of all nicotine-containing products during the 3-day period prior to the time of any biospecimen collection (Nicotine Exposure Questions (NEQs)) to facilitate interpretation of biomarker results. Of the 32,320 respondents who completed the Adult Interview at Wave 1, 21,801 (67.4 percent) provided a urine specimen and 14,520 (44.9 percent) provided a blood specimen. For the purposes of subsampling adults into the Wave 1 Biomarker Core, adult participants were grouped by tobacco product use at Wave 1 into nine mutually exclusive groups.A sample of 11,522 adults who provided sufficient urine for the planned analyses were selected from the first six tobacco product use groups (see section 3.1 of the Biomarker Restricted-Use Files User Guide) representing people who never used tobacco, currently use tobacco, and formerly used tobacco (within the last 12 months). This group constitutes the original Wave 1 Biomarker Core. Of the 11,522 adults, 7,159 also provided a blood specimen. All urine and blood specimens provided by the Wave 1 Biomarker Core were sent for laboratory analysis.Subsequent to this selection, an additional stratified probability sample of adults who completed the Wave 1 Adult Interview and provided a sufficient amount of urine for the planned analyses at Wave 1 (independent of whether

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of tobacco users and non-users. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled PSUs and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1 and Wave 4 Cohorts. Dataset 0001 (DS0001) contains the data from the Master Linkage file. This file contains 42 variables and 67,276 cases. The file provides a master list of every person's unique identification number and what type of respondent they were for each wave. Dataset 1011 (DS1011) contains the data from the Wave 1 Adult Questionnaire. This data file contains 2,021 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1012 (DS1012) contains the data from the Wave 1 Youth (and Parent) Questionnaire. This file contains 1,431 variables and 13,651 cases. Dataset 1411 (DS1411) contains the Wave 1 State Identifier data for Adults and has 5 variables and 32,320 cases. Dataset 1412 (DS1412) contains the Wave 1 State Identifier data for Youth (and Parents) and has 5 variables and 13,651 cases. The same 5 variables are in each State Identifier dataset, including PERSONID for linking the State Identifier to the questionnaire and biomarker data and 3 variables designating the state (state FIPS, state abbreviation, and full name of the state). Dataset 2011 (DS2011) contains the data from the Wave 2 Adult Questionnaire. This data file contains 2,421 variables and 28,362 cases. Of these cases, 26,447 also completed a Wave 1 Adult Questionnaire. The other 1,915 cases are "aged-up adults" having previously completed a Wave 1 Youth Questionnaire.Dataset 2012 (DS2012) contains the data from the Wave 2 Youth (and Parent) Questionnaire. This data file contains 1,596 variables and 12,172 cases. Of these cases, 10,081 also completed a Wave 1 Youth Questionnaire. The other 2,091 cases are "aged-up youth" having previously been sampled as "shadow youth." Dataset 3011 (DS3011) contains the data from the Wave 3 Adult Questionnaire. This data file contains 2,359 variables and 28,148 cases. Of these cases, 26,241 are continuing adults having completed a prior Adult Questionnaire. The other 1,907 cases are "aged-up adults" having previously completed a Youth Questionnaire. Dataset 3012 (DS3012) contains the data from the Wave 3 Youth (and Parent) Questionnaire. This data file contains 1,492 variables and 11,814 cases. Of these cases, 9,769 are continuing youth having completed a prior Youth Interview. The other 2,045 cases are "aged-up youth" having previously been sampled as "shadow youth." Datasets 3111, 3211, 3112, and 3212 (DS3111, DS3211, DS3112, and DS3212) are data files comprising the weight variables for Wave 3. The weight variables for Wave 1 and Wave 2 are included in the main data files. However, starting with Wave 3, the weight variables have been separated into individual data files. The "all-waves" weight files contain weights for respondents who completed an interview for all waves in which they were old enough to do so or verified their information with the study for waves in which they were not old enough to be interviewed. The "single-wave" weight files contain weights for all respondents in Wave 3 regardless of their

The PATH Study was launched in 2011 to inform the Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). For Wave 1 (baseline), the study sampled over 150,000 mailing addresses across the United States to create a national sample of people who do and do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave, Wave 1, of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete the Youth Interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Units (PSUs) and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Restricted-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts. Dataset 0001 (DS0001) contains the data from the Public-Use File Master Linkage File (PUF-MLF). This file contains 93 variables and 82,139 cases. The file provides a master list of every person's unique identification number and what type of respondent they were in each wave for data that are available in the Public-Use Files and Special Collection Public-Use Files. Dataset 0002 (DS0002) contains the data from the Restricted-Use File Master Linkage File (RUF-MLF). This file contains 202 variables and 82,139 cases. The file provides a master list of every person's unique identification number and what type of respondent they were in each wave for data that are available in the Restricted-Use Files, Special Collection Restricted-Use Files, and Biomarker Restricted-Use Files.

The Population Assessment of Tobacco and Health (PATH) Study began originally surveying 45,971 adult and youth respondents. The PATH Study was launched in 2011 to inform Food and Drug Administration's regulatory activities under the Family Smoking Prevention and Tobacco Control Act (TCA). The PATH Study is a collaboration between the National Institute on Drug Abuse (NIDA), National Institutes of Health (NIH), and the Center for Tobacco Products (CTP), Food and Drug Administration (FDA). The study sampled over 150,000 mailing addresses across the United States to create a national sample of people who use or do not use tobacco. 45,971 adults and youth constitute the first (baseline) wave of data collected by this longitudinal cohort study. These 45,971 adults and youth along with 7,207 "shadow youth" (youth ages 9 to 11 sampled at Wave 1) make up the 53,178 participants that constitute the Wave 1 Cohort. Respondents are asked to complete an interview at each follow-up wave. Youth who turn 18 by the current wave of data collection are considered "aged-up adults" and are invited to complete the Adult Interview. Additionally, "shadow youth" are considered "aged-up youth" upon turning 12 years old, when they are asked to complete an interview after parental consent. At Wave 4, a probability sample of 14,098 adults, youth, and shadow youth ages 10 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 4. This sample was recruited from residential addresses not selected for Wave 1 in the same sampled Primary Sampling Unit (PSU)s and segments using similar within-household sampling procedures. This "replenishment sample" was combined for estimation and analysis purposes with Wave 4 adult and youth respondents from the Wave 1 Cohort who were in the civilian, noninstitutionalized population at the time of Wave 4. This combined set of Wave 4 participants, 52,731 participants in total, forms the Wave 4 Cohort.Dataset 0001 (DS0001) contains the data from the Master Linkage file. This file contains 14 variables and 67,276 cases. The file provides a master list of every person's unique identification number and what type of respondent they were for each wave. At Wave 7, a probability sample of 14,863 adults, youth, and shadow youth ages 9 to 11 was selected from the civilian, noninstitutionalized population at the time of Wave 7. This sample was recruited from residential addresses not selected for Wave 1 or Wave 4 in the same sampled PSUs and segments using similar within-household sampling procedures. This second replenishment sample was combined for estimation and analysis purposes with Wave 7 adult and youth respondents from the Wave 4 Cohort who were at least age 15 and in the civilian, noninstitutionalized population at the time of Wave 7. This combined set of Wave 7 participants, 46,169 participants in total, forms the Wave 7 Cohort. Please refer to the Public-Use Files User Guide that provides further details about children designated as "shadow youth" and the formation of the Wave 1, Wave 4, and Wave 7 Cohorts.Dataset 1001 (DS1001) contains the data from the Wave 1 Adult Questionnaire. This data file contains 1,732 variables and 32,320 cases. Each of the cases represents a single, completed interview. Dataset 1002 (DS1002) contains the data from the Youth and Parent Questionnaire. This file contains 1,228 variables and 13,651 cases.Dataset 2001 (DS2001) contains the data from the Wave 2 Adult Questionnaire. This data file contains 2,197 variables and 28,362 cases. Of these cases, 26,447 also completed a Wave 1 Adult Questionnaire. The other 1,915 cases are "aged-up adults" having previously completed a Wave 1 Youth Questionnaire. Dataset 2002 (DS2002) contains the data from the Wave 2 Youth and Parent Questionnaire. This data file contains 1,389 variables and 12,172 cases. Of these cases, 10,081 also completed a Wave 1 Youth Questionnaire. The other 2,091 cases are "aged-up youth" having previously been sampled as "shadow youth." Dataset 3001 (DS3001) contains the data from the Wave 3 Adult Questionnaire. This data file contains 2,139 variables and 28,148 cases. Of these cases, 26,241 are continuing adults having completed a prior Adult Questionnaire. The other 1,907 cases are "aged-up adults" having previously completed a Youth Questionnaire. Dataset 3002 (DS3002) contains the data from t

Tobacco and nicotine product use among cancer survivors, stratified by age group: Population Assessment of Health and Tobacco (PATH) Study, 2013–2014.

Baseline characteristics of adult respondents (N = 32,320) by cancer status: Population Assessment of Health and Tobacco (PATH) Study, 2013–2014.

Tobacco and nicotine product use stratified by cancer status: Population Assessment of Health and Tobacco (PATH) Study, 2013–2014.

Tobacco and nicotine product use across three categories of cigarette smoking status (current, former, and never smoker): Population Assessment of Health and Tobacco (PATH) Study, 2013–2014.

US Tobacco Use Trends by Age and State

Age and State-wise Trends in US Tobacco Use 2011-2016

By Throwback Thursday [source]

About this dataset

The US Tobacco Use 2011-2016 dataset provides comprehensive information on tobacco use trends in the United States from 2011 to 2016. The data is derived from the CDC Behavioral Risk Factor Survey, which collects data on tobacco use across different age groups and states. The dataset includes variables such as age group, year of data collection, type of tobacco product used, state abbreviation where the data was collected, and the corresponding percentage or number representing the tobacco use data. Additionally, it specifies the unit of measurement for the data value (e.g., percentage or number). This dataset aims to offer valuable insights into patterns of tobacco use in different demographic segments and geographical locations within the United States over a six-year period

How to use the dataset

Step 1: Familiarize yourself with the columns: - Year: Represents the year in which the data was collected. - State Abbreviation: Indicates the abbreviation of the state where the data was collected. - Tobacco Type: Specifies the type of tobacco product used. - Data Value: Represents either a percentage or a number that represents tobacco use data. - Data Value Unit: Indicates whether the measurement is a percentage or a number. - Age Group: Specifies which age group corresponds to each piece of tobacco use data.

Step 2: Identify your area of interest: Consider what specific information you are looking for within this dataset. For example, if you want to examine trends in cigarette smoking among young adults (age group), select relevant columns like Year, State Abbreviation, Data Value (percentage/number), etc. By narrowing down your focus, you can analyze specific trends efficiently.

Step 3: Filter and sort your data: Use filtering features provided by spreadsheet software or coding languages (e.g., Python) to extract only relevant information based on your area of interest. You can filter by year(s), state(s), age group(s), or type(s) of tobacco product used using logical operators such as equal (=) and not equal (!=). This way, you can obtain a subset of data that meets your criteria for analysis conveniently.

Step 4: Analyze trends over time: Utilize line charts or bar graphs to visualize changes in tobacco use percentages or numbers over the years. This will allow you to identify any significant patterns or fluctuations, observing whether there are any consistent trends across different states or age groups.

Step 5: Compare tobacco use between states: To assess the differences in tobacco use across various states, aggregate and compare the data using statistical measures such as averages, medians, and standard deviations. By identifying states with higher or lower tobacco use rates, you can gain insights into potential factors affecting these patterns (e.g., state-specific regulations, cultural norms).

Step 6: Explore variations by age group: Investigate how tobacco use varies among different age groups. Compare percentages/

Research Ideas

• Analyzing trends in tobacco use by age and state: This dataset provides information on tobacco use in the United States from 2011 to 2016, allowing for the analysis of trends over time and differences between states. Researchers or policymakers can use this information to examine changes in tobacco consumption rates and identify patterns or factors influencing tobacco use across different age groups and states.
• Comparing the effectiveness of tobacco control measures: With this dataset, it is possible to assess how different tobacco control measures implemented by states have impacted tobacco consumption rates. By comparing data on tobacco use with specific policies, such as smoke-free laws or increased taxation, researchers can evaluate the effectiveness of these interventions and guide future public health initiatives.
• Investigating disparities in tobacco use: By examining data on age, state, and type of tobacco product used, it is possible to explore disparities in smoking prevalence across different demographic groups and geographic areas. This dataset can be used to identify populations that are more susceptible to smoking or are experiencing higher rates of cigarette usage compared to other groups. This information can inform targeted interventions aimed at reducing these disparities and promoting healthier behaviors among vulnerable populations

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

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Tobacco use is a significant national health concern that frequently co-occurs with chronic pain. Both pain and use of nicotine/tobacco have been linked to greater sleep impairments (i.e., trouble initiating and maintaining sleep), and there is reason to believe that more severe pain may indirectly contribute to greater nicotine dependence via sleep impairments. Therefore, the goal of this study was to examine indirect associations between pain severity and nicotine dependence via sleep impairment severity among adults who use cigarettes and electronic nicotine delivery systems (ENDS). Data were drawn from Wave 6 (March – November 2021) of the Population Assessment of Tobacco and Health Study (PATH), limited to N = 9,682 (54% male; 22% ages 25–24; 77% White) participants who reported regular cigarette smoking and/or ENDS use. Pain severity and sleep impairment were assessed using single items, and nicotine/tobacco dependence was assessed using the Wisconsin Inventory of Smoking Dependence Motives (WISDM). Results indicated positive indirect associations between pain severity and both tobacco and ENDS dependence via sleep impairment severity. Sleep impairment may play an important role in associations between pain severity and nicotine dependence among adults who use cigarettes or ENDS. These findings and future work may warrant the development of interventions that address sleep dysfunction to support nicotine and tobacco cessation, particularly among adults who experience pain.

A survey from the fall of 2024, found that the most used tobacco products among college students in the United States were e-cigarettes or other vape products. At that time, around 76 percent of college students who used tobacco products in the past three months reported they used e-cigarettes or other vape products. The same survey found that among college students who reported ever using a tobacco product, around 25 percent stated they used tobacco daily or almost daily in the past three months, while 28 percent had used just once or twice. What is the most popular kind of tobacco product in the United States? Although e-cigarettes are the most used tobacco product among college students, the most commonly used form of tobacco among U.S. adults is still regular combustible cigarettes. In 2021, around 10 percent of women and 13 percent of men were current cigarette smokers, compared to four percent of women and five percent of men who smoked e-cigarettes. However, e-cigarette use is much more common among younger adults, not just college students. In 2021, around 11 percent of those aged 18 to 24 years used e-cigarettes, while five percent smoked combustible cigarettes. Smoking trends in the United States Smoking in the United States has dramatically decreased over the past few decades. In 1965, it was estimated that around 42 percent of adults in the U.S. smoked, but this number was only about 14 percent in 2019. Nevertheless, as of 2022, almost 29 million people still smoked and are at risk of premature death due to cancer, cardiovascular disease, or stroke, just a few of the risk factors of smoking. The state with the highest percentage of adults who smoke is West Virginia, while Utah has the lowest prevalence of smoking. In 2023, around 20 percent of adults in West Virginia smoked, compared to six percent in Utah.

BackgroundWe assessed longitudinal effects of e-cigarette use on respiratory symptoms in a nationally representative sample of US adults by combustible tobacco smoking status.MethodsWe analyzed Waves 4–5 public-use data from the Population Assessment of Tobacco and Health Study. Study sample included adult respondents who reported no diagnosis of respiratory diseases at Wave 4, and completed Waves 4–5 surveys with no missing data on analytic variables (N = 15,291). Outcome was a validated index of functionally important respiratory symptoms based on 7 wheezing/cough questions (range 0–9). An index score of ≥2 was defined as having important respiratory symptoms. Weighted lagged logistic regression models were performed to examine the association between e-cigarette use status at Wave 4 (former/current vs. never use) and important respiratory symptoms at Wave 5 by combustible tobacco smoking status (i.e., never/former/current smokers), adjusting for Wave 4 respiratory symptom index, sociodemographic characteristics, secondhand smoke exposure, body mass index, and chronic disease.ResultsAmong current combustible tobacco smokers, e-cigarette use was associated with increased odds of reporting important respiratory symptoms (former e-cigarette use: adjusted odds ratio [AOR] = 1.39, 95% confidence interval [CI]: 1.07–1.81; current e-cigarette use: AOR = 1.55, 95% CI: 1.17–2.06). Among former combustible tobacco smokers, former e-cigarette use (AOR = 1.51, 95% CI: 1.06–2.15)—but not current e-cigarette use (AOR = 1.59, 95% CI: 0.91–2.78)—was associated with increased odds of important respiratory symptoms. Among never combustible tobacco smokers, no significant association was detected between e-cigarette use and important respiratory symptoms (former e-cigarette use: AOR = 1.62, 95% CI: 0.76–3.46; current e-cigarette use: AOR = 0.82, 95% CI: 0.27–2.56).ConclusionsThe association between e-cigarette use and respiratory symptoms varied by combustible tobacco smoking status. Current combustible tobacco smokers who use e-cigarettes have an elevated risk of respiratory impairments.

This database contains tobacco consumption data from 1970-2015 collected through a systematic search coupled with consultation with country and subject-matter experts. Data quality appraisal was conducted by at least two research team members in duplicate, with greater weight given to official government sources. All data was standardized into units of cigarettes consumed and a detailed accounting of data quality and sourcing was prepared. Data was found for 82 of 214 countries for which searches for national cigarette consumption data were conducted, representing over 95% of global cigarette consumption and 85% of the world’s population. Cigarette consumption fell in most countries over the past three decades but trends in country specific consumption were highly variable. For example, China consumed 2.5 million metric tonnes (MMT) of cigarettes in 2013, more than Russia (0.36 MMT), the United States (0.28 MMT), Indonesia (0.28 MMT), Japan (0.20 MMT), and the next 35 highest consuming countries combined. The US and Japan achieved reductions of more than 0.1 MMT from a decade earlier, whereas Russian consumption plateaued, and Chinese and Indonesian consumption increased by 0.75 MMT and 0.1 MMT, respectively. These data generally concord with modelled country level data from the Institute for Health Metrics and Evaluation and have the additional advantage of not smoothing year-over-year discontinuities that are necessary for robust quasi-experimental impact evaluations. Before this study, publicly available data on cigarette consumption have been limited—either inappropriate for quasi-experimental impact evaluations (modelled data), held privately by companies (proprietary data), or widely dispersed across many national statistical agencies and research organisations (disaggregated data). This new dataset confirms that cigarette consumption has decreased in most countries over the past three decades, but that secular country specific consumption trends are highly variable. The findings underscore the need for more robust processes in data reporting, ideally built into international legal instruments or other mandated processes. To monitor the impact of the WHO Framework Convention on Tobacco Control and other tobacco control interventions, data on national tobacco production, trade, and sales should be routinely collected and openly reported. The first use of this database for a quasi-experimental impact evaluation of the WHO Framework Convention on Tobacco Control is: Hoffman SJ, Poirier MJP, Katwyk SRV, Baral P, Sritharan L. Impact of the WHO Framework Convention on Tobacco Control on global cigarette consumption: quasi-experimental evaluations using interrupted time series analysis and in-sample forecast event modelling. BMJ. 2019 Jun 19;365:l2287. doi: https://doi.org/10.1136/bmj.l2287 Another use of this database was to systematically code and classify longitudinal cigarette consumption trajectories in European countries since 1970 in: Poirier MJ, Lin G, Watson LK, Hoffman SJ. Classifying European cigarette consumption trajectories from 1970 to 2015. Tobacco Control. 2022 Jan. DOI: 10.1136/tobaccocontrol-2021-056627. Statement of Contributions: Conceived the study: GEG, SJH Identified multi-country datasets: GEG, MP Extracted data from multi-country datasets: MP Quality assessment of data: MP, GEG Selection of data for final analysis: MP, GEG Data cleaning and management: MP, GL Internet searches: MP (English, French, Spanish, Portuguese), GEG (English, French), MYS (Chinese), SKA (Persian), SFK (Arabic); AG, EG, BL, MM, YM, NN, EN, HR, KV, CW, and JW (English), GL (English) Identification of key informants: GEG, GP Project Management: LS, JM, MP, SJH, GEG Contacts with Statistical Agencies: MP, GEG, MYS, SKA, SFK, GP, BL, MM, YM, NN, HR, KV, JW, GL Contacts with key informants: GEG, MP, GP, MYS, GP Funding: GEG, SJH SJH: Hoffman, SJ; JM: Mammone J; SRVK: Rogers Van Katwyk, S; LS: Sritharan, L; MT: Tran, M; SAK: Al-Khateeb, S; AG: Grjibovski, A.; EG: Gunn, E; SKA: Kamali-Anaraki, S; BL: Li, B; MM: Mahendren, M; YM: Mansoor, Y; NN: Natt, N; EN: Nwokoro, E; HR: Randhawa, H; MYS: Yunju Song, M; KV: Vercammen, K; CW: Wang, C; JW: Woo, J; MJPP: Poirier, MJP; GEG: Guindon, EG; GP: Paraje, G; GL Gigi Lin Key informants who provided data: Corne van Walbeek (South Africa, Jamaica) Frank Chaloupka (US) Ayda Yurekli (Turkey) Dardo Curti (Uruguay) Bungon Ritthiphakdee (Thailand) Jakub Lobaszewski (Poland) Guillermo Paraje (Chile, Argentina) Key informants who provided useful insights: Carlos Manuel Guerrero López (Mexico) Muhammad Jami Husain (Bangladesh) Nigar Nargis (Bangladesh) Rijo M John (India) Evan Blecher (Nigeria, Indonesia, Philippines, South Africa) Yagya Karki (Nepal) Anne CK Quah (Malaysia) Nery Suarez Lugo (Cuba) Agencies providing assistance: Iranian Tobacco Co. Institut National de la Statistique (Tunisia) HM Revenue & Customs (UK) Eidgenössisches Finanzdepartement EFD/Département...

The Canadian Tobacco Use Monitoring Survey (CTUMS) was conducted by Statistics Canada from July to December 2007 with the cooperation and support of Health Canada. Statistics Canada has conducted smoking surveys on an ad hoc basis on behalf of Health Canada since the 1960s. These surveys have been done as supplements to the Canadian Labour Force Survey and as random digit dialing telephone surveys. In February 1994, a change in legislation was passed which allowed a reduction in cigarette taxes. Since there was no survey data from immediately before this legislative change, it was difficult for Health Canada or other interested analysts to measure exactly the impact of the change. As Health Canada wants to be able to monitor the consequences of legislative changes and anti-smoking policies on smoking behaviour, the Canadian Tobacco Use Monitoring Survey (CTUMS) was designed to provide Health Canada and its partners/stakeholders with continual and reliable data on tobacco use and related issues. Since 1999, two CTUMS files have been released every year: a file with data collected from February to June and a file with the July to December data. Additionally, there is also a yearly summary. The present file covers the period from July to December 2007. The primary objective of the survey is to provide a continuous supply of smoking prevalence data against which changes in prevalence can be monitored. This objective differs from that of the National Population Health Survey (NPHS) which collects smoking data from a longitudinal sample to measure which individuals are changing their smoking behaviour, the possible factors which contribute to change, and the possible risk factors related to starting smoking and smoking duration. Because the NPHS collects data every two years and releases the data about a year after completing the collection cycle, it does not meet Health Canada's need for continuous coverage in time, rapid delivery of data, or sufficient detail of the most at-risk populations, namely 15 to 24 year olds. The Canadian Tobacco Use Monitoring Survey allows Health Canada to look at smoking prevalence by province-sex-age group, for age groups 15 to 19, 20 to 24, 25 to 34, 35 to 44 and 45 and over, on a semiannual and annual basis. Data will continue to be collected on an on-going basis depending on availability of funds.

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This dataset provides a detailed analysis of smoking trends worldwide, covering essential metrics such as:
- Total smokers and smoking prevalence rates
- Cigarette consumption and brand market share
- Tobacco taxation and smoking ban policies
- Smoking-related deaths and gender-based smoking patterns

Spanning data from 2010 to 2024, this dataset offers valuable insights for health research, policy evaluation, and data-driven decision-making.

📊 Column Descriptions

Sociodemographic and health characteristics of participants included in the analysis, PATH study, Waves 1–5 (2013–2019), n = 18,925 individual participants and 38,638 observations.

The size of the United States E-cigarettes Market was valued at USD 34.49 Million in 2023 and is projected to reach USD 84.83 Million by 2032, with an expected CAGR of 13.72% during the forecast period. Recent developments include: November 2022: A patent for composite tobacco-containing materials from R.J. Reynolds Tobacco Company shows that tobacco can be consumed in a reportedly "smokeless" form. The use of smokeless tobacco products often involves placing processed tobacco or a formulation containing tobacco in the user's mouth., November 2022: Philip Morris asserts that it has acquired 93% of Swedish Match as part of a plan to get access to the American market for cigarettes with lesser hazards. Philip Morris plans to use Swedish Match's American sales team to push nicotine pouches, heated tobacco products, and eventually, e-cigarettes to compete with its former partner Altria Group, Reynolds American, and Juul Labs., June 2022: A patent application for a "Device" submitted by Japan Tobacco Inc. has been published online. The concept is centered on creating a smoking system with a flavor inhaler so that users can inhale tastes and other flavors without really burning anything. As an illustration, the flavor inhaler has a chamber that houses a flavor-producing object and a heater that warms the flavor-producing item in the chamber.. Key drivers for this market are: Enhanced Participation In Water Sports, Popularity Of Beach Culture And Adventure Tourism. Potential restraints include: Presence of counterfeit products. Notable trends are: Increasing Health Concern Among Smoking Population Drives the Market.