The smoking prevalence in the United States was forecast to continuously decrease between 2024 and 2029 by in total *** percentage points. After the ****** consecutive decreasing year, the smoking prevalence is estimated to reach ***** percent and therefore a new minimum in 2029. Shown is the estimated share of the adult population (15 years or older) in a given region or country, that smoke on a daily basis. According to the WHO and World bank, smoking refers to the use of cigarettes, pipes or other types of tobacco.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the smoking prevalence in countries like Canada and Mexico.

As of 2023, the U.S. states with the highest smoking rates included West Virginia, Tennessee, and Louisiana. In West Virginia, around 20 percent of all adults smoked as of this time. The number of smokers in the United States has decreased over the past decades. Who smokes? The smoking rates for both men and women have decreased for many years, but men continue to smoke at higher rates than women. As of 2021, around 13 percent of men were smokers compared to 10 percent of women. Concerning race and ethnicity, smoking is least prevalent among Asians with just five percent of this population smoking compared to 13 percent of non-Hispanic whites. Health impacts of smoking The negative health impacts of smoking are vast. Smoking increases the risk of heart disease, stroke, and many different types of cancers. For example, smoking is estimated to be attributable to 81 percent of all deaths from lung cancer among adults 30 years and older in the United States. Smoking is currently the leading cause of preventable death in the United States.

From 1965 to 2022, the prevalence of cigarette smoking in the U.S. has decreased from about ** percent to ** percent. Cigarette smoking is a known risk factor for many types of cancers, including lung cancer, bladder cancer and pancreatic cancer. Globally, tobacco use is one of the greatest risk factors for preventable diseases. There are several resources in the United States to help individuals quit smoking, including websites, hotlines, medications and text message programs. Smoking prevalence globally Globally, smoking prevalence has also decreased, and is projected to continue to decline through 2025. North America comprises a small percentage of the world’s cigarette smokers. The highest prevalence of tobacco smoking can be found in Europe, followed by the Western Pacific. In the past few decades, there have been stronger efforts made to reduce cigarette consumption in many parts of the world. Cigarettes are taxed separately in many countries and are often required to add health warnings to cigarette packaging for consumers. Smoking cessation measures Smoking prevention measures cover a broad range of targeted cigarette reduction. Common tobacco control policies include warning labels, advertising bans, and smoke-free environments. As of 2022, around ** percent of the world population lived in a place where there were warning labels on tobacco products.

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

...

United States US: Smoking Prevalence: Total: % of Adults: Aged 15+ data was reported at 21.800 % in 2016. This records a decrease from the previous number of 22.300 % for 2015. United States US: Smoking Prevalence: Total: % of Adults: Aged 15+ data is updated yearly, averaging 23.900 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 31.400 % in 2000 and a record low of 21.800 % in 2016. United States US: Smoking Prevalence: Total: % of Adults: Aged 15+ data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of smoking is the percentage of men and women ages 15 and over who currently smoke any tobacco product on a daily or non-daily basis. It excludes smokeless tobacco use. The rates are age-standardized.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

United States US: Smoking Prevalence: Males: % of Adults data was reported at 24.600 % in 2016. This records a decrease from the previous number of 25.100 % for 2015. United States US: Smoking Prevalence: Males: % of Adults data is updated yearly, averaging 26.800 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 34.500 % in 2000 and a record low of 24.600 % in 2016. United States US: Smoking Prevalence: Males: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of smoking, male is the percentage of men ages 15 and over who currently smoke any tobacco product on a daily or non-daily basis. It excludes smokeless tobacco use. The rates are age-standardized.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

In 2022, the prevalence of smoking among white U.S. adults was 12.7 percent. This statistic represents the prevalence of smoking in the United States as of 2022, by race and ethnicity.

As of 2022, around **** million adults in the United States were current cigarette smokers. Although this figure is still high, it is significantly lower compared to previous years. For example, in 2011, there were almost ** million smokers in the United States. Smoking demographics in the U.S. Although smoking in the U.S. has decreased greatly over the past few decades, it is still more common among certain demographics than others. For example, men are more likely to be current cigarette smokers than women, with ** percent of men smoking in 2021, compared to ** percent of women. Furthermore, non-Hispanic whites and non-Hispanic Blacks smoke at higher rates than Hispanics and non-Hispanic Asians, with almost ** percent of non-Hispanic whites smoking in 2022, compared to just under **** percent of non-Hispanic Asians. Certain regions and states also have a higher prevalence of smoking than others, with around ** percent of adults in West Virginia considered current smokers, compared to just *** percent in Utah. The health impacts of smoking The decrease in smoking rates in the United States over the past decades is due to many factors, including policies and regulations limiting cigarette advertising, promotion, and sales, price increases for cigarettes, and widespread awareness among the public of the dangers of smoking. According to the CDC, those who smoke are *** to **** times more likely to develop coronary heart disease and stroke and around ** times more likely to develop lung cancer than nonsmokers. In fact, it is estimated that around ** percent of lung cancer deaths in the United States can be attributed to cigarette smoking, as well as ** percent of larynx cancer deaths. Cigarette smokers are also much more likely to develop chronic obstructive pulmonary disease (COPD), with around ** percent of current smokers in the U.S. living with COPD in 2021, compared to just ***** percent of those who had never smoked.

Smoking rates for each Census Tract in Allegheny County were produced for the study “Developing small-area predictions for smoking and obesity prevalence in the United States.” The data is not explicitly based on population surveys or data collection conducted in Allegheny County, but rather estimated using statistical modeling techniques. In this technique, researchers applied the smoking rate of a demographically similar Census Tract to one in Allegheny County to compute a smoking rate.

Historical dataset showing U.S. smoking rate by year from 2000 to 2022.

The Current Population Survey Tobacco Use Supplement data collection from January 2015 is comprised of responses from two sets of survey questionnaires, the basic Current Population Survey (CPS) and a Tobacco Use Supplement (TUS) survey. The TUS 2014-2015 Wave consists of three collections: July 2014, January 2015, and May 2015. The CPS, administered monthly, is the source of the official government statistics on employment and unemployment. From time to time, additional questions are included on health, education, and previous work experience. The Tobacco Use Supplement to the CPS is a National Cancer Institute sponsored survey of tobacco use that has been administered as part of the US Census Bureau's CPS approximately every 3-4 years since 1992-1993. Similar to other CPS supplements, the Tobacco Use Supplement was designed for both proxy and self-respondents. All CPS household members age 18 and older who completed CPS core items in January 2015 were eligible for the supplement items. A new feature for the 2014-2015 cycle included random selection of self-interviewed respondents in larger households to reduce respondent burden. If the household had only 1 supplement eligible member then that person was selected for self-interview. If the household had only 2 supplement eligible members, then both of them were selected for self-interview. If the household had 3 or 4 supplement eligible members, then 2 of them were randomly selected for self-interview and the remaining were interviewed by proxy. If the household had more than 4 supplement eligible members, then 3 of them were randomly selected for self-interview and the rest of the eligible respondents were interviewed by proxy. Those selected for self-interview were eligible for the entire supplement, whereas proxy respondents were only eligible for an abbreviated interview. Occasionally, those persons to be interviewed by proxy, if available for self- interview, were interviewed directly but asked the abbreviated proxy path questions. Both proxy and self-respondents were asked about their smoking status and the use of other tobacco products. For self-respondents only, different questions were asked depending on their tobacco use status: for former/current smokers, questions were asked about type of cigarettes smoked, measures of addiction, attempts to quit smoking, methods and treatments used to quit smoking, and if they were planning to quit in the future. All self-respondents were asked about smoking policy at their work place and their attitudes towards smoking in different locations. Demographic information within this collection includes age, sex, race, Hispanic origin, marital status, veteran status, immigration status, educational background, employment status, occupation, and income.

US: Smoking Prevalence: Females: % of Adults data was reported at 19.100 % in 2016. This records a decrease from the previous number of 19.600 % for 2015. US: Smoking Prevalence: Females: % of Adults data is updated yearly, averaging 21.100 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 28.400 % in 2000 and a record low of 19.100 % in 2016. US: Smoking Prevalence: Females: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of smoking, female is the percentage of women ages 15 and over who currently smoke any tobacco product on a daily or non-daily basis. It excludes smokeless tobacco use. The rates are age-standardized.; ; World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).; Weighted average;

US Tobacco Use Prevalence

US Tobacco Use Prevalence by Year, State, Type, and Age

By Throwback Thursday [source]

About this dataset

This dataset contains comprehensive information on tobacco use in the United States from 2011 to 2016. The data is sourced from the CDC Behavioral Risk Factor Survey, a reliable and extensive survey that captures important data about tobacco use behaviors across different states in the United States.

The dataset includes various key variables such as the year of data collection, state abbreviation indicating where the data was collected, and specific tobacco types explored in the survey. It also provides valuable insight into the prevalence of tobacco use through quantitative measures represented by numeric values. The unit of measurement for these values, such as percentages or numbers, is included as well.

Moreover, this dataset offers an understanding of how different age groups are affected by tobacco use, with age being categorized into distinct groups. This ensures that researchers and analysts can assess variations in tobacco consumption and its associated health implications across different age demographics.

With all these informative attributes arranged in a convenient tabular format, this dataset serves as a valuable resource for investigating patterns and trends related to tobacco use within varying contexts over a six-year period

How to use the dataset

Introduction:

Step 1: Familiarize Yourself with the Columns

Before diving into any analysis, it is important to understand the structure of the dataset by familiarizing yourself with its columns. Here are the key columns in this dataset:

• Year: The year in which the data was collected (Numeric)
• State Abbreviation: The abbreviation of the state where the data was collected (String)
• Tobacco Type: The type of tobacco product used (String)
• Data Value: The percentage or number representing prevalence of tobacco use (Numeric)
• Data Value Unit: The unit of measurement for data value (e.g., percentage, number) (String)
• Age: The age group to which the data value corresponds (String)

Step 2: Determine Your Research Questions or Objectives

To make effective use of this dataset, it is essential to clearly define your research questions or objectives. Some potential research questions related to this dataset could be:

• How has tobacco use prevalence changed over time?
• Which states have the highest and lowest rates of tobacco use?
• What are the most commonly used types of tobacco products?
• Is there a correlation between age group and tobacco use?

By defining your research questions or objectives upfront, you can focus your analysis accordingly.

Step 3: Analyzing Trends Over Time

To analyze trends over time using this dataset: - Group and aggregate relevant columns such as Year and Data Value. - Plot the data using line graphs or bar charts to visualize the changes in tobacco use prevalence over time. - Interpret the trends and draw conclusions from your analysis.

Step 4: Comparing States

To compare states and their tobacco use prevalence: - Group and aggregate relevant columns such as State Abbreviation and Data Value. - Sort the data based on prevalence rates to identify states with the highest and lowest rates of tobacco use. - Visualize this comparison using bar charts or maps for a clearer understanding.

Step 5: Understanding Tobacco Types

To gain insights into different types of tobacco products used: - Analyze the Tobacco

Research Ideas

• Analyzing trends in tobacco use: This dataset can be used to analyze the prevalence of tobacco use over time and across different states. It can help identify patterns and trends in tobacco consumption, which can be valuable for public health research and policy-making.
• Assessing the impact of anti-smoking campaigns: Researchers or organizations working on anti-smoking campaigns can use this dataset to evaluate the effectiveness of their interventions. By comparing the data before and after a campaign, they can determine whether there has been a decrease in tobacco use and if specific groups or regions have responded better to the campaign.
• Understanding demographic factors related to tobacco use: The dataset includes information on age groups, allowing for analysis of how different age demographics are affected by tobacco use. By examining data value variations across age groups, researchers can gain insights into which populations are most vulnerable to smoking-related issues and design targeted prevention programs an...

County-level smoking data originating from the CDC and produced by Dwyer-Lindgren, Laura and Mokdad, Ali H. and Srebotnjak, Tanja and Flaxman, Abraham D. and Hansen, Gillian M. and Murray, Christopher JL— (2014), “Cigarette smoking prevalence in US counties: 1996-2012,” Population Health Metrics, 12, 5. Original file provided by the above authors available at https://goo.gl/tNbpsS

The male smoking prevalence in the United States was forecast to continuously decrease between 2024 and 2029 by in total *** percentage points. After the ****** consecutive decreasing year, the male smoking rate is estimated to reach ***** percent and therefore a new minimum in 2029. Shown is the estimated share of the male adult population (15 years or older) in a given region or country, that smoke. According to the WHO and World bank, smoking refers to the use of cigarettes, pipes or other types of tobacco, be it on a daily or non-daily basis.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the male smoking prevalence in countries like Canada and Mexico.

United States US: Prevalence of Current Tobacco Use: % of Adults data was reported at 24.300 % in 2022. This records a decrease from the previous number of 24.700 % for 2021. United States US: Prevalence of Current Tobacco Use: % of Adults data is updated yearly, averaging 27.100 % from Dec 2000 (Median) to 2022, with 8 observations. The data reached an all-time high of 31.500 % in 2000 and a record low of 24.300 % in 2022. United States US: Prevalence of Current Tobacco Use: % of Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Health Statistics. The percentage of the population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), “e-cigars”, “e-hookahs”, JUUL and “e-pipes”. The rates are age-standardized to the WHO Standard Population.;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.a.1 [https://unstats.un.org/sdgs/metadata/]. Previous indicator name: Smoking prevalence, total (ages 15+) The previous indicator excluded smokeless tobacco use, while the current indicator includes. The indicator name and definition were updated in December, 2020.

United States US: Prevalence of Current Tobacco Use: Females: % of Female Adults data was reported at 18.700 % in 2022. This records a decrease from the previous number of 18.900 % for 2021. United States US: Prevalence of Current Tobacco Use: Females: % of Female Adults data is updated yearly, averaging 21.200 % from Dec 2000 (Median) to 2022, with 8 observations. The data reached an all-time high of 25.300 % in 2000 and a record low of 18.700 % in 2022. United States US: Prevalence of Current Tobacco Use: Females: % of Female Adults data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Health Statistics. The percentage of the female population ages 15 years and over who currently use any tobacco product (smoked and/or smokeless tobacco) on a daily or non-daily basis. Tobacco products include cigarettes, pipes, cigars, cigarillos, waterpipes (hookah, shisha), bidis, kretek, heated tobacco products, and all forms of smokeless (oral and nasal) tobacco. Tobacco products exclude e-cigarettes (which do not contain tobacco), “e-cigars”, “e-hookahs”, JUUL and “e-pipes”. The rates are age-standardized to the WHO Standard Population.;World Health Organization, Global Health Observatory Data Repository (http://apps.who.int/ghodata/).;Weighted average;This is the Sustainable Development Goal indicator 3.a.1 [https://unstats.un.org/sdgs/metadata/]. Previous indicator name: Smoking prevalence, females (% of adults) The previous indicator excluded smokeless tobacco use, while the current indicator includes it. The indicator name and definition were updated in December, 2020.

The prevalence of electronic cigarette (e-cigarette) use has rapidly increased among young people, while conventional cigarette use has decreased in this age group. However, some evidence suggests that e-cigarette use is likely to induce conventional cigarette smoking. The present study explored the social influence of the prevalence of e-cigarette use in the peer network and in the general population as a potential mechanism by which e-cigarette use affects adolescents’ overall smoking behaviours. For this purpose, we developed an agent-based model in which young agents repeatedly choose to smoke conventional cigarettes and/or e-cigarettes, or to remain non-smokers. The choice is based on the agent’s evaluation of the utility derived from smoking and attitude towards smoking (‘openness’), which is influenced by smoking prevalence in the agent’s peer network and in the broader society. We also assumed a ‘crossover’ effect between the different types of smoking. The model was calibrated with United States National Youth Tobacco Survey data to reflect real-world numbers. We further simulated the prevalence of different types of smoking under counterfactual scenarios with different levels of openness and crossover effects. The models developed successfully reproduced actual prevalence trends in different types of smoking from 2011 to 2014. Openness to smoking is associated with a dramatic increase in e-cigarette smoking and especially in dual smoking, which cancels out the decline in sole conventional smoking. Larger crossover effects are associated with a higher prevalence of conventional smoking. The simulation results indicate that the social influence of the prevalence of e-cigarette use may influence young people to initiate or continue conventional cigarette smoking. Assessing the impact of e-cigarettes in the general population as a ‘healthier’ alternative to conventional smoking may require carefully monitoring trends in young people’s smoking behaviours.

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 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.