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).

📊

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

project use R for graph :

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Tobacco smoking stands as a significant global health crisis, affecting millions worldwide and leading to severe health complications and premature deaths. This issue has persisted for decades, with an estimated 100 million people succumbing prematurely due to smoking-related causes throughout the 20th century, predominantly in affluent nations. However, a decline in the global smoking rate signals a positive shift in global health, potentially enabling millions to enjoy longer, healthier lives.

Annually, smoking is responsible for approximately 8 million premature deaths. These figures highlight the urgent need for effective measures to combat this epidemic. The World Health Organization (WHO) and the Institute for Health Metrics and Evaluation (IHME) provide critical data on the mortality rates associated with tobacco use, emphasizing the gravity of the situation. According to the latest WHO estimates as of November 2023, over 8 million people die each year due to tobacco use, with more than 7 million of these deaths directly linked to smoking. Additionally, around 1.3 million nonsmokers die from exposure to second-hand smoke. The IHME's Global Burden of Disease study further supports these findings, estimating that 8.7 million deaths annually can be attributed to tobacco use, including 7.7 million from smoking and 1.3 million from second-hand smoke exposure, alongside an additional 56,000 deaths from chewing tobacco.

The impact of smoking on mortality is disproportionately higher among men, who account for 71% of premature deaths due to smoking. This disparity underscores the need for targeted interventions that address the specific risks and behaviors associated with smoking among different demographics.

Understanding the vast death toll from tobacco use requires a comprehensive approach that encompasses all forms of tobacco consumption, including smoking and chewing tobacco. The data indicate that the vast majority of tobacco-related deaths are due to smoking, with figures from the IHME suggesting that smoking-related deaths constitute more than 99.9% of all tobacco-use deaths. This emphasizes the critical importance of focusing public health efforts on reducing smoking rates to mitigate the overall impact of tobacco on global health.

The interactive charts and studies provided by organizations like the WHO and IHME offer valuable insights into the global and regional dynamics of smoking-related health issues. These resources allow for a detailed examination of smoking trends and their health consequences, facilitating evidence-based policy-making and public health strategies aimed at reducing smoking prevalence and its associated health burden.

Efforts to combat smoking must take into account the various factors that contribute to its prevalence, including societal norms, economic factors, and the addictive nature of nicotine. Public health campaigns, legislative measures, and support programs for those trying to quit smoking are essential components of a comprehensive strategy to address this issue.

Furthermore, research into the health effects of smoking and the mechanisms by which it contributes to diseases such as cancer, heart disease, and respiratory illnesses is crucial for developing effective treatments and prevention strategies. By understanding the full scope of smoking's impact on health, researchers and policymakers can better target interventions to reduce smoking rates and improve public health outcomes.

In conclusion, the global health crisis posed by tobacco smoking is a multifaceted issue that requires concerted efforts from governments, public health organizations, and communities worldwide. The declining trend in smoking rates offers hope, but the continued high prevalence of smoking-related deaths underscores the need for ongoing action. Through research, public health initiatives, and policy interventions, it is possible to further reduce smoking rates and alleviate the tremendous health burden it imposes on societies around the globe.

The global number of smokers in was forecast to continuously increase between 2024 and 2029 by in total **** million individuals (+**** percent). After the ******** consecutive increasing year, the number of smokers is estimated to reach *** billion individuals and therefore a new peak in 2029. Shown is the estimated share of the 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 number of smokers in countries like Caribbean and Africa.

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.

Smoking is so common, and feels so familiar, that it can be hard to grasp just how large the impact is. Every year, around 8 million people die prematurely as a result of smoking.1 This means that about one in seven deaths worldwide are due to smoking.2 Millions more live in poor health because of it.

Smoking primarily contributes to early deaths through heart diseases and cancers. Globally, more than one in five cancer deaths are attributed to smoking.

This means tobacco kills more people every day than terrorism kills in a year.

Smoking is a particularly large problem in high-income countries. There, cigarette smoking is the most important cause of preventable disease and death. This is especially true for men: they account for almost three-quarters of deaths from smoking.

The impact of smoking is devastating on the individual level. In case you need some motivation to stop smoking: The life expectancy of those who smoke regularly is about 10 years lower than that of non-smokers.

It’s also devastating on the aggregate level. In the past 30 years more than 200 million have died from smoking. Looking into the future, epidemiologists Prabhat Jha and Richard Peto estimate that “If current smoking patterns persist, tobacco will kill about 1 billion people this century.”

It is on us to prevent this.

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;

** Description**

This dataset contains data about lung cancer Mortality and is a comprehensive collection of patient information, specifically focused on individuals diagnosed with cancer. This dataset contains comprehensive information on 800,000 individuals related to lung cancer diagnosis, treatment, and outcomes. With 16 well-structured columns. This large-scale dataset is designed to aid researchers, data scientists, and healthcare professionals in studying patterns, building predictive models, and enhancing early detection and treatment strategies.

🌍 The Societal Impact of Lung Cancer

Lung cancer is not just a disease — it's a global crisis that steals time, health, and hope from millions of people every year. As the #1 cause of cancer deaths worldwide, it takes more lives annually than breast, colon, and prostate cancer combined.

But behind every statistic is a story:

A parent who never saw their child graduate.

A worker who had to leave their job too soon.

A community that lost a leader, a friend, a neighbor.

Why does this matter? Lung cancer often goes undetected until it's too late. It’s aggressive, silent, and devastating — especially in underserved areas where early detection is rare and treatment options are limited. It doesn’t just affect patients. It affects families, economies, and healthcare systems on a massive scale.

This dataset represents more than numbers. It represents 800,000 real-world stories — people who can help us unlock patterns, train models, and advance life-saving research.

By working with this data, you're not just analyzing a dataset — you're stepping into the fight against one of humanity’s deadliest diseases.

Let’s turn insight into impact. (😊The above descriptions is generated with the help of AI, Just wanted to share this dataset That all. Thank you)

Objective: Smoking is a major cause of worldwide morbidity and mortality. Evidence-based intervention programs to help young adults quit smoking are largely lacking; identifying targets for intervention is therefore critical. A candidate target is inhibitory control, with previous studies on Go/No-Go trainings showing behavior change in the food and alcohol domain. The current study examined the mechanisms of change of HitnRun, a Go/No-Go game, in a smoking population that was motivated to quit. Methods: A two-armed experimental study (n = 106) was conducted and young adults (Mage = 22.15; SDage = 2.59) were randomly assigned to either play HitnRun or to read a psychoeducational brochure. Prior to and directly following the intervention period, smoking-specific and general inhibitory control, perceived attractiveness of smoking pictures, and weekly smoking behavior were assessed. Results: Results indicate that Go/No-Go training seems to be effective in decreasing evaluations of smoking stimuli rather than top-down smoking-specific and general control processes. Similar reductions for weekly smoking were found in both groups. Conclusions: We conclude that HitnRun shows some promise, but more research and iterative design is needed to create a multi-component intervention for smoking cessation that is dynamically adjustable to the individual needs of young people.

BackgroundWaterpipe (WP) use is rapidly increasing among young people worldwide due to the widespread misperception that it is safer than cigarette smoking. Health warning labels (HWLs) can effectively communicate tobacco-related health risks but have yet to be developed for WP. This study aimed to optimize and adapt a set of 16 pictorial WP-specific HWLs, developed by an international Delphi study, to the Tunisian context. HWLs were grouped into four themes: WP health risks, WP harm to others, WP-specific harms, and WP harm compared to cigarettes.MethodsUsing a mixed method approach, we conducted ten focus groups combined with a survey among young WP users and nonusers (N = 63; age 18–34 years). In the survey, participants rated the HWLs on several communication outcomes (e.g., reaction, harm perception, effectiveness) and were then instructed to view all HWLs in each theme and rank them in the order of overall perceived effectiveness, from the most to the least effective. Afterward, participants provided in-depth feedback on HWLs and avenues for improvement. Mean effectiveness rating scores and percentages of participants’ top-ranked HWLs were calculated. Discussions were audio-taped, transcribed verbatim, and analyzed thematically.ResultsThe top-ranked HWLs were those showing oral cancers, orally transmitted diseases, and a sick child. Focus group discussion illustrated that these selections were based on participants’ reactions to the direct impact of WP on a person’s physical appearance and evoking guilt over children’s exposure to WP smoke. Suggestions for improvement highlighted the need to use the local dialect and more affirmative statements (e.g., avoiding "may" or "can").ConclusionsThis study is the first in North Africa to attempt to advance HWLs policy as the World Health Organization recommended. The results of this study can be used as a basis for implementing WP-specific health messages in the Eastern Mediterranean Region.

Cancer, the second-leading cause of mortality, kills 16% of people worldwide. Unhealthy lifestyles, smoking, alcohol abuse, obesity, and a lack of exercise have been linked to cancer incidence and mortality. However, it is hard. Cancer and lifestyle correlation analysis and cancer incidence and mortality prediction in the next several years are used to guide people’s healthy lives and target medical financial resources. Two key research areas of this paper are Data preprocessing and sample expansion design Using experimental analysis and comparison, this study chooses the best cubic spline interpolation technology on the original data from 32 entry points to 420 entry points and converts annual data into monthly data to solve the problem of insufficient correlation analysis and prediction. Factor analysis is possible because data sources indicate changing factors. TSA-LSTM Two-stage attention design a popular tool with advanced visualization functions, Tableau, simplifies this paper’s study. Tableau’s testing findings indicate it cannot analyze and predict this paper’s time series data. LSTM is utilized by the TSA-LSTM optimization model. By commencing with input feature attention, this model attention technique guarantees that the model encoder converges to a subset of input sequence features during the prediction of output sequence features. As a result, the model’s natural learning trend and prediction quality are enhanced. The second step, time performance attention, maintains We can choose network features and improve forecasts based on real-time performance. Validating the data source with factor correlation analysis and trend prediction using the TSA-LSTM model Most cancers have overlapping risk factors, and excessive drinking, lack of exercise, and obesity can cause breast, colorectal, and colon cancer. A poor lifestyle directly promotes lung, laryngeal, and oral cancers, according to visual tests. Cancer incidence is expected to climb 18–21% between 2020 and 2025, according to 2021. Long-term projection accuracy is 98.96 percent, and smoking and obesity may be the main cancer causes.

Prevalence of exposure to anti-smoking messages and pro-smoking messages among Chinese adults, Global Adult Tobacco Survey, China, 2018.

Background: Waterpipe tobacco smoking is a traditional method of tobacco use, especially in the Eastern Mediterranean Region (EMR), but its prevalence is growing worldwide, especially among young people. Although often perceived as less harmful than other methods of tobacco use because the smoke passes through water, accumulating evidence shows harmful effects and that some smokers become addicted. Interventions that deglamourise and denormalise use have been recommended but little is known about the range and impact of different health prevention and promotion interventions.Methods: A scoping review of literature was undertaken to explore the breadth of literature and assess the range and impact of community based health promotion interventions for waterpipe smoking. Searches were conducted in Medline, Embase, CINAHL, Psychinfo, and the Cochrane database of systematic reviews. Interventions were classified using a health promotion framework and data extracted on the aspects of prevention/promotion addressed; key strategies employed, evidence of effectiveness or impact on behavior change as well as barriers to implementation and perceived success factors.Results: Ten studies were included in the review. They include brief interventions to increase quit rates; community campaigns to raise awareness and increase knowledge; web based health education and skill development to increase perceived risks and intention to quit; as well as studies that evaluated product labeling and opportunities for policy interventions to create healthy environments.Conclusions: The evidence base is small but growing. Brief interventions for waterpipe users, community campaigns, and web based tailored information can modify perceptions of addiction and increase intentions to quit. Product labeling may be an effective policy tool to curb waterpipe smoking. A range of policy interventions have been identified but not evaluated.

Background: Multiple sclerosis (MS), as an autoimmune disease of the central nervous system (CNS), has a significant burden among people worldwide. Tobacco smoking is one of the most prevalent habits of patients with different diseases including those with MS and among the methods of use, waterpipe tobacco smoking is gaining popularity. Herein, we aimed to systematically evaluate the association between waterpipe smoking and MS. Methods: Relevant studies were identified to be included in this systematic review and meta-analysis through a systematic search in PubMed, Scopus, Web of Science, and Embase. Studies were screened by title/abstract and then by their full text. Extraction of data was performed for relevant studies. Odds ratios (OR) and their 95% confidence intervals (CIs) of the association between waterpipe smoking and MS were used to pool the results observed in each study. Results: After the screening, a total of five studies were included in our systematic review, comprised of 3087 individuals, among which there were 1135 cases with MS. Random-effect meta-analysis revealed that ever-smoking waterpipe had a significant association with MS (OR 1.73, 95% CI 1.38-2.17, p-value

The number of smokers in Mexico was forecast to continuously increase between 2024 and 2029 by in total *** million individuals (**** percent). After the ninth consecutive increasing year, the number of smokers is estimated to reach ***** million individuals and therefore a new peak in 2029. Shown is the estimated share of the 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 number of smokers in countries like Canada and United States.

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Video on Risk factors of Lung Cancer - ![https://youtu.be/0vVRp5eNDlA?feature=shared]

Dataset: 1. GENDER: Gender of the individual (M: Male, F: Female) 2. AGE: Age of the individual 3. SMOKING: Smoking status (2: Yes, 1: No) 4. YELLOW_FINGERS: Presence of yellow fingers (2: Yes, 1: No) 5. ANXIETY: Anxiety level (2: High, 1: Low) 6. PEER_PRESSURE: Peer pressure level (2: High, 1: Low) 7. CHRONIC DISEASE: Presence of chronic disease (2: Yes, 1: No) 8. FATIGUE: Fatigue level (2: High, 1: Low) 9. ALLERGY: Allergy status (2: Yes, 1: No) 10. WHEEZING: Wheezing condition (2: Yes, 1: No) 11. ALCOHOL CONSUMING: Alcohol consumption status (2: Yes, 1: No) 12. COUGHING: Presence of coughing (2: Yes, 1: No) 13. SHORTNESS OF BREATH: Shortness of breath condition (2: Yes, 1: No) 14. SWALLOWING DIFFICULTY: Difficulty in swallowing (2: Yes, 1: No) 15. CHEST PAIN: Presence of chest pain (2: Yes, 1: No) 16. LUNG_CANCER: Lung cancer diagnosis (2: Yes, 1: No)

• Data has 309 rows and 16 columns with floating variables, integer, object which ranges from 0 - 308

• Lung cancer is the uncontrollable growth of abnormal cells in one or both of the lungs. Cigarette smoking causes most lung cancers when smoke gets in the lungs. Lung cancer kills 1.8 million people each year, more than any other cancer. It has an 80-90% death rate, and is the leading cause of cancer death in men, and the second leading cause of cancer death in women.

• The global cancer burden is estimated to have risen to 18.1 million new cases and 9.6 million deaths in 2018. One in 5 men and one in 6 women worldwide develop cancer during their lifetime, and one in 8 men and one in 11 women die from the disease. Worldwide, the total number of people who are alive within 5 years of a cancer diagnosis, called the 5-year prevalence, is estimated to be 43.8 million.

Background Analyzing long-term trends in Ischemic stroke (IS), Subarachnoid hemorrhage (SAH), Intracerebral hemorrhage (ICH) mortality from smoking in China from 1992 to 2021, To provide scientific advice on stroke prevention and treatment in China. Methods The data of smoking-related stroke and death subtypes in China during 1992-2021 were collected from the Global Burden of Disease 2021. Joinpoint regression model and age-period-cohort (APC) mortality model were used for trend analysis. Results The age-standardized mortality rate (ASMR) of stroke and subtypes caused by smoking showed a decreasing trend in China from 1992 to 2021. The decline was greater for women than for men. According to APC model analysis, the age effect showed that ICH and IS showed an increasing trend, while SAH increased first and then decreased. The results of the cohort effect were similar to those of the period effect, with RR(relative risk) decreasing for all subtypes. The local drift showed that the stroke and subtypes in male showed a “U” shaped trend, the is trend in female was relatively stable, and SAH and ICH showed a downward trend. Conclusion Over the past 30 years, the burden of stroke and stroke subtype deaths attributable to smoking in China has decreased. However, future efforts should focus on preventing intracerebral hemorrhage (ICH). Strengthening tobacco control legislation, particularly targeting older men and young people, is crucial for further reducing smoking-related stroke risk.