Comparing the *** selected regions regarding the smoking prevalence , Myanmar is leading the ranking (***** percent) and is followed by Serbia with ***** percent. At the other end of the spectrum is Ghana with **** percent, indicating a difference of ***** percentage points to Myanmar. 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).

The share of individuals who currently smoke cigarettes, cigars, cigarillos or a pipe in Greece was around 42 percent in 2020, which makes the Mediterranean country have the highest proportion of smokers in the EU.

Tobacco taxation

In an effort to reduce smoking prevalence among the populace, governments across Europe impose ever-higher tax rates on tobacco, making cigarettes much more expensive for consumers to purchase and hence, compelling them to reduce their consumption. For instance, Finland had the highest cigarette excise tax rate in 2019 at around 68 percent. Other countries like the Netherlands and Germany impose a slightly lower tax rate of 54 and 52 percent, respectively. The German government generated approximately 14.7 billion euros in revenues from tobacco taxation in 2020. With tobacco taxes making up the lion’s share of the price of a pack of cigarettes, European governments hope this will trigger a significant reduction in consumer demand.

To what extent did higher taxes contribute to reducing cigarette consumption in Europe?

With rising tobacco taxation across the European continent in the last years (albeit in varying rates), cigarette consumers have either quit smoking, reduced their intake or switched to e-cigarettes and non-combustible tobacco alternatives. In fact, only 28 percent of individuals consume tobacco in France today, a country once notorious for its prevalent tobacco consumption. This trend has been reflected over the years with a significant drop in the volume of cigarettes annually sold in France: In 2005, more than 54,000 tons of cigarettes were sold, but that figure dropped to nearly 36,000 tons by 2020. During the same time period, the price of the most sold brand of cigarettes in France more than tripled.

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.

Support for Health Equity datasets and tools provided by Amazon Web Services (AWS) through their Health Equity Initiative.

📊

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

This statistic depicts the prevalence of tobacco smokers worldwide from 2000 to 2025, by country income group. According to the data, it is projected that the prevalence of tobacco smokers in high-income countries will drop from 33.6 percent in 2000 to 20.5 percent in 2025.

According to the data, it is projected that the prevalence of tobacco smoking among those living in Africa will decrease from around 14.5 percent in 2000 to 7.4 percent in 2025. This statistic depicts the prevalence of tobacco smoking worldwide from 2000 to 2020 and projections for 2025, by region.

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 | ...

In 2021, Jordan had the highest rate of daily smokers in the Middle East and North Africa (MENA) region at almost ** percent, followed by Turkey, and the West Bank and Gaza strip respectively. The majority of countries in the region had daily smoking rates between ** and ** percent.

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

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

Israel rose 0.6points of Smoking Prevalence in 2019, compared to a year earlier.

ObjectiveTo systematically review current smoking prevalence among adults in sub-Saharan Africa from 2007 to May 2014 and to describe the context of tobacco control strategies in these countries.Data SourcesFive databases, Medline, Embase, Africa-wide Information, Cinahl Plus, and Global Health were searched using a systematic search strategy. There were no language restrictions.Study Selection26 included studies measured current smoking prevalence in nationally representative adult populations in sub-Saharan African countries.Data ExtractionStudy details were independently extracted using a standard datasheet. Data on tobacco control policies, taxation and trends in prices were obtained from the Implementation Database of the WHO FCTC website.ResultsStudies represented 13 countries. Current smoking prevalence varied widely ranging from 1.8% in Zambia to 25.8% in Sierra Leone. The prevalence of smoking was consistently lower in women compared to men with the widest gender difference observed in Malawi (men 25.9%, women 2.9%). Rwanda had the highest prevalence of women smokers (12.6%) and Ghana had the lowest (0.2%). Rural, urban patterns were inconsistent. Most countries have implemented demand-reduction measures including bans on advertising, and taxation rates but to different extents.ConclusionSmoking prevalence varied widely across sub-Saharan Africa, even between similar country regions, but was always higher in men. High smoking rates were observed among countries in the eastern and southern regions of Africa, mainly among men in Ethiopia, Malawi, Rwanda, and Zambia and women in Rwanda and rural Zambia. Effective action to reduce smoking across sub-Saharan Africa, particularly targeting population groups at increased risk remains a pressing public health priority.

As of 2023, Turkey had the highest share of adults who smoked daily in Europe, at almost ** percent. In Ukraine there was also a high prevalence of daily smokers reported at ** percent. On the other hand, smoking is less popular in Nordic countries, with Sweden, Norway, and Iceland having fewer than *** percent of their populations smoking daily. Attempts to quit smoking In a European survey addressed to smokers in 2020, Bulgaria and Romania had the largest share of smokers who reported never attempting to quit smoking, at around **************. Meanwhile, roughly ****** percent of smokers in the United Kingdom attempted to quit smoking in the past. In a separate survey, many smokers in Europe were aware of the cancer risks of smoking and had attempted to cut down on the habit as a result. Overall, young people across Europe were less likely to quit smoking, with ** percent of those aged 15 to 24 reporting never attempting to quit. Smoking among youth Roughly a third of school students in Lithuania had tried smoking cigarettes by the age of 13, out of whom *** percent were daily smokers. Among a slightly higher age group, by the age of ** years, Slovakia held the highest share of youth trying cigarettes in their lifetime at ** percent, with ** percent having smoked a cigarette within the past month. In almost every European country, more than half of school students surveyed said it easy to obtain cigarettes, with Denmark coming at the top of the list with ** percent of its students. Nevertheless, smoking has generally declined among European youths over the past decades; down from ** percent of ** year olds smoking in 1999 to ** percent by 2019.

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;

The European Health Interview Survey (EHIS) aims at measuring on a harmonised basis and with a high degree of comparability among Member States (MS) the health status (including disability), health determinants (lifestyle) of the EU citizens and use of health care services and limitations in accessing it.

The general coverage of the survey is the population aged 15 or over living in private households residing in the territory of the country.

EHIS was developed between 2003 and 2006. It consists of four modules on health status, health determinants, health care, and background variables (socio-demographic characteristics of the population).

Three waves of EHIS have currently been implemented. The first wave of EHIS (EHIS wave 1 or EHIS round 2008) was conducted between 2006 and 2009 in 17 EU Member States as well as Switzerland and Turkey.

The second wave (EHIS wave 2 or EHIS round 2014) was conducted between 2013 and 2015 in all EU Member States, Iceland, Norway and Turkey according to the Commission Regulation 141/2013.

The third wave of EHIS was conducted in 2019. All Member States participated in the EHIS wave 3 in accordance with the Commission Regulation (EU) No. 2018/255. A derogation regarding the data collection period was granted for some countries: the data collection period was 2018 for Belgium, 2018-2020 for Austria and Germany, and 2019-2020 for Malta.

The questionnaire consists of the same four modules for all the EHIS waves and over the years, some changes to the questionnaire have been implemented to satisfy specific users’ needs. Also, countries are allowed to include additional questions in the specific submodules or even specific sub-modules in the survey if this does not have an impact on the results of the compulsory variable

EHIS includes the following topics:

Health status
This topic includes different dimensions of health status and health-related activity limitations:

• General health status (Minimum European health module): self-perceived health, chronic morbidity and disability (activity limitation)
• Disease-specific morbidity
• Accidents and injuries
• Health-related absenteeism from work
• Physical and sensory functional limitations (also cognitive limitations in wave 3)
• Difficulties in personal care activities / activities of daily living (such as eating and washing) and help received/needed
• Household activities / Instrumental activities of daily living (such as preparing meals and shopping) and help received/needed
• Pain
• Aspect of mental health (psychological distress and mental well-being in the first wave, depressive symptoms in the second and third waves)
• Work-related health problems (only in the first wave).

Health care
This topic covers the use of different types of medicines and formal and informal health and social care services, which are complemented by data on health-related expenditure, and limitations in access to and satisfaction with health care services:

• Hospitalisation (in-patient and day care)
• Consultations with doctors and dentists
• Visits to specific health professionals (such as physiotherapists or psychologists)
• Use of home care services
• Use of medicines (prescribed and non-prescribed)
• Healthcare preventive actions (such as influenza vaccination, breast examination, cervical smear test and blood tests)
• Unmet needs for health care
• Out-of-pocket payments for medical care (only in the first wave)
• Satisfaction with services provided by healthcare providers (only in the first wave)
• Visits to specific categories of alternative medicine practitioners (only in the first wave).

Health determinants
This topic includes various individual and environmental health determinants:

• Height and weight
• Physical activity/exercise
• Consumption of fruits, vegetables and juice
• Drinking sugar-sweetened soft drinks (only in the third wave)
• Tobacco smoking behaviour and exposure to tobacco smoke
• Use of e-cigarettes or similar electronic devices (only in the third wave)
• Alcohol consumption
• Social support
• Provision of informal care or assistance (only in the second and third waves)
• Illicit drug use (only in the first wave)
• Environment (home and workplace exposures, criminality exposure) (only in the first wave).

Background variables on demography and socio-economic characteristics.

All indicators are expressed as percentages within the population and statistics are broken down by age and sex and one other dimension such as educational attainment level, income quintile group, degree of urbanization, country of birth, country of citizenship, level of disability (activity limitation).

Smoking estimates by age group from 2010 to 2014. This is presented at a UK level, and broken down by England, Wales, Scotland and Northern Ireland.

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...

As of 2019, around two percent of individuals aged 15 years and older in Panama were daily smokers, making Panama one of the countries with the lowest prevalence of daily tobacco smokers worldwide. This statistic illustrates the 20 countries with the lowest prevalence of daily smokers worldwide as of 2019.

Country data for socioeconomic inequalities in mortality and smoking/obesity prevalence by year.

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