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

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Percentages are weighted to population characteristics. Data are not available if it did not meet BRFSS stability requirements.For more information on these requirements, as well as risk factors and calculated variables, see the Technical Documents and Survey Data for a specific year - http://www.cdc.gov/brfss/annual_data/annual_data.htm.Recommended citation: Centers for Disease Control and Prevention (CDC). Behavioral Risk Factor Surveillance System. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, [appropriate year].

Percentages are weighted to population characteristics. Data are not available if it did not meet BRFSS stability requirements.For more information on these requirements, as well as risk factors and calculated variables, see the Technical Documents and Survey Data for a specific year - http://www.cdc.gov/brfss/annual_data/annual_data.htm.Recommended citation: Centers for Disease Control and Prevention (CDC). Behavioral Risk Factor Surveillance System. Atlanta, Georgia: U.S. Department of Health and Human Services, Centers for Disease Control and Prevention, [appropriate year].

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.

Overview: The QuitNowTXT text messaging program is designed as a resource that can be adapted to specific contexts including those outside the United States and in languages other than English. Based on evidence-based practices, this program is a smoking cessation intervention for smokers who are ready to quit smoking. Although evidence supports the use of text messaging as a platform to deliver cessation interventions, it is expected that the maximum effect of the program will be demonstrated when it is integrated into other elements of a national tobacco control strategy. The QuitNowTXT program is designed to deliver tips, motivation, encouragement and fact-based information via unidirectional and interactive bidirectional message formats. The core of the program consists of messages sent to the user based on a scheduled quit day identified by the user. Messages are sent for up to four weeks pre-quit date and up to six weeks post quit date. Messages assessing mood, craving, and smoking status are also sent at various intervals, and the user receives messages back based on the response they have submitted. In addition, users can request assistance in dealing with craving, stress/mood, and responding to slips/relapses by texting specific key words to the QuitNow. Rotating automated messages are then returned to the user based on the keyword. Details of the program are provided below. Texting STOP to the service discontinues further texts being sent. This option is provided every few messages as required by the United States cell phone providers. It is not an option to remove this feature if the program is used within the US. If a web-based registration is used, it is suggested that users provide demographic information such as age, sex, and smoking frequency (daily or almost every day, most days, only a few days a week, only on weekends, a few times a month or less) in addition to their mobile phone number and quit date. This information will be useful for assessing the reach of the program, as well as identifying possible need to develop libraries to specific groups. The use of only a mobile phone-based registration system reduces barriers for participant entry into the program but limits the collection of additional data. At bare minimum, quit date must be collected. At sign up, participants will have the option to choose a quit date up to one month out. Text messages will start up to 14 days before their specified quit date. Users also have the option of changing their quit date at any time if desired. The program can also be modified to provide texts to users who have already quit within the last month. One possible adaptation of the program is to include a QuitNowTXT "light" version. This adaptation would allow individuals who do not have unlimited text messaging capabilities but would still like to receive support to participate by controlling the number of messages they receive. In the light program, users can text any of the programmed keywords without fully opting in to the program. Program Design: The program is designed as a 14-day countdown to quit date, with subsequent six weeks of daily messages. Each day within the program is identified as either a pre-quit date (Q- # days) or a post-quit date (Q+#). If a user opts into the program fewer than 14 days before their quit date, the system will begin sending messages on that day. For example, if they opt in four days prior to their quit date, the system will send a welcome message and recognize that they are at Q-4 (or four days before their quit date), and they will receive the message that everyone else receives four days before their quit date. As the user progresses throughout the program, they will receive messages outlined in the text message library. Throughout the program, users will receive texts that cover a variety of content areas including tips, informational content, motivational messaging, and keyword responses. The frequency of messages incre

aCurrent smokers smoked at least 100 cigarettes in their lifetime and smoked “every day” or “some days” now.bDaily smokers smoked “every day” now, or if they smoked “some days,” they smoked on >25 days in the past 30 days.cNondaily smokers smoked “some days” now and smoked on ≤25 days in the past 30 days.dVery light daily smokers are daily smokers who smoked ≤5 cigarettes per day.eVery light nondaily smokers are nondaily smokers who smoked ≤3 cigarettes per day.fInfrequent smokers are nondaily smokers who smoked on ≤8 days in the past 30 days.gSmoking respondent reported that he/she had stopped smoking for more than one day because he/she was trying to quit smoking in the past 12 months.hPoverty status is a ratio of family income to the appropriate poverty threshold (given family size and number of children) defined by the US Census Bureau. “Poor” adults reported a family income below the poverty threshold. “Near poor” adults had a family income of 100–199% of the poverty threshold. “Not poor” adults reported a family income of 200% of the poverty threshold or greater.iLifetime abstainers had fewer than 12 drinks in lifetime; Former drinkers had at least 12 drinks in lifetime, but none in past year; Current light drinkers drank 1–3 drinks per week in past year; Current moderate drinkers drank 4–14 drinks per week for male and 4–7 drinks per week for female; Current heavy drinkers drank >14 drinks per week for male and >7 drinks per week for female.jBinge drinkers drank ≥5 drinks on at least one day in the past 12 months.Note. CI = confidence interval.

Purpose For the purpose of informing tobacco intervention programs, this dataset was created and used to explore how online social networks of smokers differed from those of nonsmokers. The study was a secondary analysis of data collected as part of a randomized control trial conducted within Facebook. (See "Other References" in "Metadata" for parent study information.) Basic description of 4 anonymized data files of study participants. fbr_friends: Anonymized Facebook friends networks, basic ego demographics, basic ego social media activity fbr_family: Anonymized Facebook family networks, basic ego demographics, basic ego social media activity fbr_photos: Anonymized Facebook photo networks, basic ego demographics, basic ego social media activity fbr_groups: Anonymized Facebook group networks, basic ego demographics, basic ego social media activity Each network comprises the ego, the ego's first degree connections, and the (second degree) connections between the ego's friends. Missing data and users who did not have friend, family, photo, or group networks were cleaned from the data beforehand. Each data file contains the following columns of data, taken with participant knowledge and consent participant_id: Nonidentifying ids assigned to different study participants. is_smoker: Binary value (0,1) that takes on the value 1 if participant was a smoker and 0 otherwise. gender: One of three categories: male, female, or blank, which signified Other (different from missing data). country: One of four categories: Canada (ca), US (us), Mexico (mx), or Other (xx). likes_count: Numeric data indicating number of Facebook likes the participant had made up to the date the data was collected. wall_count: Numeric data indicating number of Facebook wall posts the participant had made up to the date the data was collected. t_count_page_views: Numeric data indicating number of pages participant had visited in the UbiQUITous app up to the date the data was collected. yearsOld: Numeric data indicating age in years of the participant; right censored at 90 years for data anonymity. vertices: Number of people in the participant's network. edges: Number of connections between people in the network. density: The portion of potential connections in a network that are actual connections; a network-level metric; calculated after removing ego and isolates. mean_betweenness_centrality: An average of the relative importance of all individuals within their own network; a network-level metric; calculated after removing ego and isolates. transitivity: The extent to which the relationship between two nodes in a network that are connected by an edge is transitive (calculated as the number of triads divided by all possible connections); a network-level metric; calculated after removing ego and isolates. mean_closeness: Average of how closely associated members are to one another; a network-level metric; calculated after removing ego and isolates. isolates2: Number of individuals with no connections other than to the ego; a network-level metric. diameter3: Maximum degree of separation between any two individuals in the network; a network-level metric; calculated after removing ego and isolates. clusters3: Number of subnetworks; a network-level metric; calculated after removing ego and isolates. communities3: Number of groups, sorted to increase dense connections within the group and decrease sparse connections outside it (i.e., to maximize modularity); a network-level metric; calculated after removing ego and isolates. modularity3: The strength of division of a network into communities (calculated as the fraction of ties between community members in excess of the expected number of ties within communities if ties were random); a network-level metric. Detailed information on network metrics in the associated manuscript: "An exploration of the Facebook social networks of smokers and non-smokers" by Fu, L, Jacobs MA, Brookover J, Valente TW, Cobb NK, and Graham AL.

Prevalence is measured as the proportion of daily smokers in each province who were considering quitting. Smoking is a health behaviour that deteriorates health. Smoking is the most important cause of preventable illness, disability and premature death.

Data for cities, communities, and City of Los Angeles Council Districts were generated using a small area estimation method which combined the survey data with population benchmark data (2022 population estimates for Los Angeles County) and neighborhood characteristics data (e.g., U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates). Adults included in this indicator are current cigarette smokers. Current smokers are defined as adults who smoked at least 100 cigarettes in their lifetime and currently smoke.Tobacco use is a leading preventable cause of premature death and disability. Cities and communities can curb tobacco use by adopting policies to regulate tobacco retail and reduce exposure to secondhand smoke in outdoor public spaces, such as parks, restaurants, or in multi-unit housing.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

IntroductionLight and intermittent smoking (LITS) has become increasingly common. Alcohol drinkers are more likely to smoke. We examined the association of smokefree law and bar law coverage and alcohol use with current smoking, LITS, and smoking quit attempts among US adults and alcohol drinkers.MethodsCross-sectional analyses among a population-based sample of US adults (n = 27,731) using restricted data from 2009 National Health Interview Survey and 2009 American Nonsmokers' Rights Foundation United States Tobacco Control Database. Multivariate logistic regression models examined the relationship of smokefree law coverage and drinking frequency (1) with current smoking among all adults; (2) with 4 LITS patterns among current smokers; and (3) with smoking quit attempts among 6 smoking subgroups. Same multivariate analyses were conducted but substituted smokefree bar law coverage for smokefree law coverage to investigate the association between smokefree bar laws and the outcomes. Finally we ran the above analyses among alcohol drinkers (n = 16,961) to examine the relationship of smokefree law (and bar law) coverage and binge drinking with the outcomes. All models controlled for demographics and average cigarette price per pack. The interactions of smokefree law (and bar law) coverage and drinking status was examined.ResultsStronger smokefree law (and bar law) coverage was associated with lower odds of current smoking among all adults and among drinkers, and had the same effect across all drinking and binge drinking subgroups. Increased drinking frequency and binge drinking were related to higher odds of current smoking. Smokefree law (and bar law) coverage and drinking status were not associated with any LITS measures or smoking quit attempts.ConclusionsStronger smokefree laws and bar laws are associated with lower smoking rates across all drinking subgroups, which provides further support for these policies. More strict tobacco control measures might help reduce cigarette consumption and increase quit attempts.

Summary statistics of the mean percent of daily males and females smokers for 38 states and District of Columbia, 1999–2012.

The basic purpose of the Health Interview Survey (HIS) is to obtain information about the amount and distribution of illness, its effects in terms of disability and chronic impairments, and the kinds of health services people receive. Person variables include sex, age, race, marital status, veteran status, education, income, industry and occupation codes, and limits on activity. This Smoking Supplement contains information on smoking status of respondents including whether they never smoked, occasionally smoked, were former smokers, or were present smokers. Data are also supplied on number of cigarettes smoked, age when started smoking, brands smoked, number of attempts to quit smoking, and tar and nicotine levels of brands smoked. (Source: downloaded from ICPSR 7/13/10)

Please Note: This dataset is part of the historical CISER Data Archive Collection and is also available at ICPSR -- https://doi.org/10.3886/ICPSR09220.v2. We highly recommend using the ICPSR version as they made this dataset available in multiple data formats.

aCurrent smokers smoked at least 100 cigarettes in their lifetime and smoked “every day” or “some days” now.bDaily smokers smoked “every day” now, or if they smoked “some days,” they smoked on >25 days in the past 30 days.cNondaily smokers smoked “some days” now and smoked on ≤25 days in the past 30 days.dVery light daily smokers are daily smokers who smoked ≤5 cigarettes per day.eVery light nondaily smokers are nondaily smokers who smoked ≤3 cigarettes per day.fInfrequent smokers are nondaily smokers who smoked on ≤8 days in the past 30 days.gLifetime abstainers had fewer than 12 drinks in lifetime; Former drinkers had at least 12 drinks in lifetime, but none in past year; Current light drinkers drank 1–3 drinks per week in past year; Current moderate drinkers drank 4–14 drinks per week for male and 4–7 drinks per week for female; Current heavy drinkers drank >14 drinks per week for male and >7 drinks per week for female.hPoverty status is a ratio of family income to the appropriate poverty threshold (given family size and number of children) defined by the US Census Bureau. “Poor” adults reported a family income below the poverty threshold. “Near poor” adults had a family income of 100–199% of the poverty threshold. “Not poor” adults reported a family income of 200% of the poverty threshold or greater.*P < .05;**P < .01;***P < .001Note. AOR = adjusted odds ratio; CI = confidence interval.

In 2023, around 28.6 percent of the population aged 15 years and above in Indonesia were smokers. Smoking prevalence in Indonesia peaked in 2018 at 32.2 percent. To address the widespread prevalence of smoking, the government imposed a tax hike in 2020. Cigarette consumption in Indonesia Despite the Indonesian government's increase in excise duties on cigarettes and tobacco products, smoking among adults remains high, particularly among men. Cultural norms, low prices, and aggressive tobacco marketing significantly challenge efforts to reduce smoking rates. In Indonesia, smoking is deeply embedded in social practices and often begins at a young age. Recent data indicates that Indonesians aged 18 to 59 smoke an average of 12 cigarettes daily, equivalent to one regular-sized pack of cigarettes sold in the country. Tobacco industry in Indonesia The tobacco industry in Indonesia is a vital economic sector, ranking among the world’s leading producers and consumers of tobacco. Indonesia produced over 200,000 metric tons of tobacco annually, with exports to countries such as the Philippines and the United States. This extensive production and export network underscores the industry's importance to Indonesia's economy. The total export value of tobacco and its manufactured products from Indonesia is estimated to be nearly two billion U.S. dollars, highlighting its significant contribution to the nation's economic landscape.

aRate per 100,000 standardized to the age-distribution of the CPS-II men/women.bCox proportional hazards model, adjusted for age, race, education, physical activity, alcohol use, marital status, aspirin use, fat consumption, vegetable consumption, and postmenopausal estrogen use (women).Relative risk of death from cardiovascular, cancer, or other causes according to BMI among men and women who are never smokers without prevalent disease, CPS-II 1982–2010.