U.S. Tobacco Use Data

Prevalence and Trends by State

By Health [source]

About this dataset

This dataset provides insight into the prevalence and trends in tobacco use across the United States. By breaking down this data by state, you can see how tobacco has been used and changed over time. Smoking is a major contributor to premature deaths and health complications, so understanding historic usage rates can help us analyze and hopefully reduce those negative impacts. Drawing from the Behavioral Risk Factor Surveillance System, this dataset gives us an unparalleled look at both current and historical smoking habits in each of our states. With this data, we can identify high risk areas and track changes throughout the years for better health outcomes overall

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How to use the dataset

This dataset contains information on the prevalence and trends of tobacco use in the United States. The data is broken down by state, and includes percentages of smokers, former smokers, and those who have never smoked. With this dataset you can explore how smoking habits have changed over time as well as what regions of the country have seen more or less consistent smoking trends.

To begin using this dataset, you will first want to familiarize yourself with the columns included within it and their associated values. There is a “State” column that provides the US state for which each row refers to; there are also columns detailing percentages for those who smoke every day (Smoke Everyday), some days (Smoke Some Days), previously smoked (Former Smoker) and those who have never smoked (Never Smoked). The “Location 1” column indicates each geographic region that falls into one of either four US census divisions or eight regions based upon where each state lies in relation to one another.

Once you understand the data presented within these columns, there are a few different ways to begin exploring how tobacco use has changed throughout time including plotting prevalence data over different periods such as decades or specific years; compiling descriptive statistics such as percentiles or mean values; contrasting between states based on any relevant factors such as urban/rural population size or economic/political standing; and lastly looking at patterns developing throughout multiple years via various visualisations like box-and-whisker plots amongst other alternatives.

This wide set of possibilities makes this dataset interesting enough regardless if you are looking at regional differences across single points in time or long-term changes regarding national strategies around reducing nicotine consumption. With all its nuances uncovered hopefully your results can lead towards further research uncovering any aspect about smoking culture you may find fascinating!

Research Ideas

• Comparing regional and state-level smoking rates and trends over time.
• Analyzing how different demographics are affected by state-level smoking trends, such as comparing gender or age-based differences in prevalence and/or decreasing or increasing rates of tobacco use at the regional level over time.
• Developing visualization maps that show changes in tobacco consumption prevalence (and related health risk factors) by location on an interactive website or tool for public consumption of data insights from this dataset

Acknowledgements

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

License

License: Open Database License (ODbL) v1.0 - You are free to: - Share - copy and redistribute the material in any medium or format. - Adapt - remix, transform, and build upon the material for any purpose, even commercially. - You must: - Give appropriate credit - Provide a link to the license, and indicate if changes were made. - ShareAlike - You must distribute your contributions under the same license as the original. - Keep intact - all notices that refer to this license, including copyright notices. - No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material. - No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: BRFSS_Prevalence_and_Trends_Data_Tobacco_Use_-_Four_Level_Smoking_Data_for_1995-2010.csv | Column name | ...

Annual data on the proportion of adults in Great Britain who smoke cigarettes, cigarette consumption, the proportion who have never smoked cigarettes and the proportion of smokers who have quit by sex and age over time.

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;

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...

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_26dc9d0415ebc42309c8fbcf209d3e07/view

Indonesia ID: Smoking Prevalence: Total: % of Adults: Aged 15+ data was reported at 39.400 % in 2016. This records an increase from the previous number of 39.000 % for 2015. Indonesia ID: Smoking Prevalence: Total: % of Adults: Aged 15+ data is updated yearly, averaging 37.600 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 39.400 % in 2016 and a record low of 32.900 % in 2000. Indonesia ID: 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 Indonesia – Table ID.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;

Annual data and annual historic data on the proportion of adults who currently smoke, the proportion of ex-smokers and proportion of those who have never smoked, by sex and age.

Bangladesh BD: Smoking Prevalence: Males: % of Adults data was reported at 44.700 % in 2016. This records a decrease from the previous number of 45.100 % for 2015. Bangladesh BD: Smoking Prevalence: Males: % of Adults data is updated yearly, averaging 47.000 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 55.900 % in 2000 and a record low of 44.700 % in 2016. Bangladesh BD: 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 Bangladesh – Table BD.World Bank.WDI: Social: 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;

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

Number and percentage of persons being current smokers, by age group and sex.

This dataset contains three smoking related indicators. Rates of self reported four-week smoking quitters Smoking quit rates per 100,000 available from the HNA. - These quarterly reports present provisional results from the monitoring of the NHS Stop Smoking Services (NHS SSS) in England. This report includes information on the number of people setting a quit date and the number who successfully quit at the 4 week follow-up. Data for London presented with England comparator. PCT level data available from NHS. Number of Deaths Attributable to Smoking per 100,000 population by borough Deaths attributable to smoking, directly age-sex standardised rate for persons aged 35 years +. Causes of death considered to be related to smoking are: various cancers, cardiovascular and respiratory diseases, and diseases of the digestive system. Numbers of adults smoking by borough Prevalence of smoking among persons aged 18 years and over. - Population who currently smoke, are ex-smokers, or never smoked by borough. This includes cigarette, cigar or pipe smokers. Data by age is also provided for London with a UK comparator. Relevant links: http://www.hscic.gov.uk/Article/1685 http://www.apho.org.uk/default.aspx?QN=HP_DATATABLES

Number and percentage of smokers and non-smokers based on changes in smoking between 1994/1995 and 2004/2005, 2006/2007, 2008/2009 and 2010/2011, by age group and sex.

Portugal PT: Smoking Prevalence: Males: % of Adults data was reported at 30.000 % in 2016. This records a decrease from the previous number of 30.400 % for 2015. Portugal PT: Smoking Prevalence: Males: % of Adults data is updated yearly, averaging 31.600 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 37.600 % in 2000 and a record low of 30.000 % in 2016. Portugal PT: 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 Portugal – Table PT.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;

Network statistics from the five sample datasets.

Colombia CO: Smoking Prevalence: Males: % of Adults data was reported at 13.500 % in 2016. This records a decrease from the previous number of 14.200 % for 2015. Colombia CO: Smoking Prevalence: Males: % of Adults data is updated yearly, averaging 16.000 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 27.400 % in 2000 and a record low of 13.500 % in 2016. Colombia CO: 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 Colombia – Table CO.World Bank.WDI: Social: 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;

BackgroundWe aimed to clarify the relationship between coronavirus disease 2019 (COVID-19) reinfection and basic disease and smoking status.MethodsThe electronic health records of 165,320 patients with COVID-19 from January 1, 2020, to August 27, 2021, were analyzed. Data on age, race, sex, smoking status (never, current, former), and basic disease were analyzed using Cox proportional hazard models.ResultsIn total, 6,133 patients (3.7%) were reinfected. The overall reinfection rate for never, current, and former smokers was 4.2, 3.5, and 5.7%, respectively. Although the risk of reinfection was highest among former smokers aged ≥65 years (7.7% [422/5,460]), the reinfection rate among current smokers aged ≥65 years was 6.2% (341/5,543). Among reinfected patients, the number of basic diseases was higher in former smokers (2.41 ± 1.16) than in current (2.28 ± 1.07, P = 0.07) and never smokers (2.07 ± 1.05, P < 0.001). Former smokers who are older may have been exposed to factors that increase their risk of symptomatic COVID-19 reinfection.

Laos LA: Smoking Prevalence: Females: % of Adults data was reported at 7.300 % in 2016. This records a decrease from the previous number of 7.700 % for 2015. Laos LA: Smoking Prevalence: Females: % of Adults data is updated yearly, averaging 9.100 % from Dec 2000 (Median) to 2016, with 9 observations. The data reached an all-time high of 17.900 % in 2000 and a record low of 7.300 % in 2016. Laos LA: 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 Laos – Table LA.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;

This data is derived from the Maternity Indicators dataset which is provided to the Welsh Government by Digital Health and Care Wales (DHCW). The Maternity Indicators dataset was established in 2016. It combines records from a mother’s initial assessment with a child’s birth record and enabled Welsh Government to monitor its initial set of outcome indicators and performance measures (Maternity Indicators) which were established to measure the effectiveness and quality of Welsh maternity services. The Maternity Indicators dataset allows us to analyse characteristics of the mother’s pregnancy and birth process. The process for producing this data extract is complex largely because there can be multiple initial assessment data and records for both initial assessments and births are not always complete. Full details of every data item available in the Maternity Indicators dataset are available through the NHS Wales Data Dictionary: http://www.datadictionary.wales.nhs.uk/#!WordDocuments/datasetstructure20.htm

This table contains 11760 series, with data for years 1994 - 1998 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (not all combinations are available): Geography (5 items: Territories; Northwest Territories; Yukon; Northwest Territories including Nunavut ...), Age group (14 items: Total; 12 years and over; 15-19 years; 12-19 years; 12-14 years ...), Sex (3 items: Both sexes; Females; Males ...), Smoking (7 items: Total population for the variable smoking; Daily smoker; Former smoker; Occasional smoker ...), Characteristics (8 items: Number of persons; Coefficient of variation for number of persons; Low 95% confidence interval - number of persons; High 95% confidence interval - number of persons ...).

This report contains results from the latest survey of secondary school pupils in England in years 7 to 11 (mostly aged 11 to 15), focusing on smoking, drinking and drug use. It covers a range of topics including prevalence, habits, attitudes, and wellbeing. This survey is usually run every two years, however, due to the impact that the Covid pandemic had on school opening and attendance, it was not possible to run the survey as initially planned in 2020; instead it was delivered in the 2021 school year. In 2021 additional questions were also included relating to the impact of Covid. They covered how pupil's took part in school learning in the last school year (September 2020 to July 2021), and how often pupil's met other people outside of school and home. Results of analysis covering these questions have been presented within parts of the report and associated data tables. It includes this summary report showing key findings, excel tables with more detailed outcomes, technical appendices and a data quality statement. An anonymised record level file of the underlying data on which users can carry out their own analysis will be made available via the UK Data Service later in 2022 (see link below).