DHS COMPARATIVE

REPORTS 31

TOBACCO USE BY MEN AND WOMEN 

IN 49 COUNTRIES WITH 

DEMOGRAPHIC AND HEALTH SURVEYS

JULY 2013

This publication was produced for review by the United States Agency for International Development (USAID). The report was prepared by 

Donna L. Ansara of John Hopkins University, Fred Arnold and Sunita Kishor of ICF International, and Jason Hsia and Rachel Kaufmann of the 

Centers for Disease Control and Prevention.
MEASURE DHS assists countries worldwide in the collection and use of data to monitor and evaluate 

population, health, and nutrition programs. Additional information about the MEASURE DHS project can 

be obtained by contacting MEASURE DHS, ICF International, 11785 Beltsville Drive, Suite 300, 

Calverton, MD 20705 (telephone: 301-572-0200; fax: 301-572-0999; e-mail: reports@measuredhs.com; 

internet: www.measuredhs.com). 

The main objectives of the MEASURE DHS project are: 

• to provide decisionmakers in survey countries with information useful for informed policy 

choices; 

• to expand the international population and health database; 

• to advance survey methodology; and 

• to develop in participating countries the skills and resources necessary to conduct high-quality 

demographic and health surveys. 
DHS Comparative Reports No. 31 

Tobacco Use by Men and Women in 49 

Countries with Demographic and Health 

Surveys 

Donna L. Ansara1 

Fred Arnold2 

Sunita Kishor2 

Jason Hsia3 

Rachel Kaufmann3 

 

July 2013 

Corresponding authors: Sunita Kishor and Fred Arnold, Demographic and Health Surveys, ICF International, 

11785 Beltsville Drive, Suite 300, Calverton, MD 20705; Phone: 301-572-0200; Email: sunita.kishor@icfi.com 

1

Johns Hopkins University 

2

ICF International 

3

Centers for Disease Control and Prevention 

ICF International 

Calverton, Maryland, USA

Centers for Disease Control and Prevention 

Atlanta, Georgia, USA
Document Production: Yuan Cheng 

This study was carried out with support provided by the United States Agency for International 

Development (USAID) through the MEASURE DHS project (#GPO-C-00-08-00008-00) and by the U.S. 

Centers for Disease Control and Prevention (CDC) through the contract on Communications and 

Integrated Marketing Strategies, Media Services, and Database Support to the Office on Smoking and 

Health, Health Communications Branch (#200-2008-F-26188). The views expressed are those of the 

authors and do not necessarily reflect the views of USAID or the United States Government. The authors 

gratefully acknowledge input from Samira Asma, Office on Smoking and Health, CDC, on this project. 

Recommended citation: 

Ansara, Donna L., Fred Arnold, Sunita Kishor, Jason Hsia, and Rachel Kaufmann. 2013. Tobacco Use by 

Men and Women in 49 Countries with Demographic and Health Surveys. DHS Comparative Reports No. 

31. Calverton, Maryland, USA: ICF International. 
iii 

Contents 

Tables ...............................................................................................................................................v 

Appendix Tables ..............................................................................................................................v 

Figures............................................................................................................................................ vi 

Preface ........................................................................................................................................... vii 

Executive Summary ....................................................................................................................... ix 

1 Introduction ................................................................................................................................1 

2 Data and Methods ......................................................................................................................4 

2.1 Data .................................................................................................................................. 5 

2.2 Definition of Variables .................................................................................................... 8 

2.3 Analyses ......................................................................................................................... 17 

3 Results: Prevalence of Tobacco Use among Women and Men ...............................................19 

3.1 Prevalence of Any Tobacco Use .................................................................................... 19 

3.2 Prevalence of Manufactured Cigarette Smoking ........................................................... 27 

3.3 Prevalence of the Use of Other Smoked Tobacco ......................................................... 31 

3.4 Prevalence of the Use of Smokeless Tobacco ............................................................... 32 

3.5 Differentials in Manufactured Cigarette Use by Sociodemographic Characteristics .... 32 

4 Conclusions and Study Limitations .........................................................................................47

References ......................................................................................................................................49 

Appendix ........................................................................................................................................53 

v 

Tables 

Table 1. Summary of Demographic and Health Surveys included in this report, 1999-

2010..................................................................................................................................6 

Table 2. DHS questions assessing current cigarette use ................................................................9 

Table 3. DHS questions assessing current use of other types of smoked tobacco 

(excluding cigarettes) .....................................................................................................11 

Table 4. DHS questions assessing current use of smokeless tobacco ..........................................13 

Table 5. DHS questions assessing number of cigarettes smoked in the last 24 hours .................15 

Table 6a. Percentage of men age 15-49 who currently smoke cigarettes or use other 

tobacco products by country and region, 1999-2010 .....................................................20 

Table 6b. Percentage of women age 15-49 who currently smoke cigarettes or use other 

tobacco products by country and region, 1999-2010 .....................................................22 

Appendix Tables 

Appendix Table A1. Correlates of current cigarette smoking among men age 15-49 in 

countries with >10% prevalence of smoking, 2002-10 ..............................53 

Appendix Table A2. Correlates of current cigarette smoking among women age 15-49 

in countries with >5% prevalence of smoking, 1999-2009 ........................59 

Appendix Table A3a. Percent distribution of men age 15-49 who currently smoke 

cigarettes by number of cigarettes smoked in the past 24 hours, 

2002-10.......................................................................................................62 

Appendix Table A3b. Percent distribution of women age 15-49 who currently smoke 

cigarettes by number of cigarettes smoked in the past 24 hours, 

2001-10.......................................................................................................63 

Appendix Table A4. Percentage of men who currently smoke cigarettes or use other 

tobacco products by age group, according to country and region, 

2002-10.......................................................................................................64 
vi 

Figures 

Figure 1. Percentage of men age 15-49 who currently use any type of tobacco .........................24 

Figure 2. Percentage of women age 15-49 who currently use any type of tobacco ....................26 

Figure 3. Percentage of men age 15-49 who currently smoke manufactured cigarettes .............28 

Figure 4. Percentage of women age 15-49 who currently smoke manufactured cigarettes ........30 
vii 

Preface 

One of the most significant contributions of the MEASURE DHS program is the creation of an 

internationally comparable body of data on the demographic and health characteristics of populations in 

developing countries. 

The DHS Comparative Reports series examines these data across countries in a comparative 

framework. The DHS Analytical Studies series focuses on specific topics. The principal objectives of both 

series are to provide information for policy formulation at the international level and to examine 

individual country results in an international context. Whereas Comparative Reports are primarily 

descriptive, Analytical Studies have a more analytical approach. 

The Comparative Reports series covers a variable number of countries, depending on the 

availability of data sets. Where possible, data from previous DHS surveys are used to evaluate trends over 

time. Each report provides detailed tables and graphs organized by region. Survey-related issues such as 

questionnaire comparability, survey procedures, data quality, and methodological approaches are 

addressed as needed. 

It is anticipated that the availability of comparable information for a large number of developing 

countries will enhance the understanding of important issues in the fields of international population and 

health by analysts and policymakers. 

Sunita Kishor 

Project Director 

ix 

Executive Summary

This report examines the prevalence of current cigarette smoking and tobacco use among women 

and men in 49 developing countries. Data for the analysis were obtained from Demographic and Health 

Surveys (DHS) conducted between 1999 and 2010. Data from the most recent DHS conducted in each of 

the countries with information on current tobacco use were used for this analysis. The report describes the 

proportion of women and men age 15-49 within the countries who report currently using manufactured 

cigarettes, other forms of smoked tobacco, and smokeless tobacco. The study also explores differentials in 

cigarette smoking by selected sociodemographic characteristics. While the questions used to assess 

tobacco use and the populations surveyed were generally similar across most of the countries that were 

examined, some differences in these characteristics are noted. Thus, attention should be paid to these 

differences and caution should be used in interpreting the findings. 

The results reveal that the prevalence of any tobacco use varies substantially worldwide for 

women and men. For men, the prevalence of any tobacco use exceeds 40 percent in all the countries 

examined in North Africa/West Asia/Europe, Central Asia, and South and Southeast Asia. Timor-Leste 

has the highest prevalence of tobacco use for men, with 7 out of 10 men currently using at least one form 

of tobacco. Lower prevalence of tobacco use for men is generally found in countries in sub-Saharan 

Africa and Latin America/Caribbean. The countries in this report with the lowest prevalence of tobacco 

use for men are Ghana (7 percent), Ethiopia (11 percent), Nigeria (12 percent), and the Dominican 

Republic (12 percent). 

Women are much less likely than men to report using tobacco in all the countries with available 

data. The highest prevalence of tobacco use for women is found in Madagascar (21 percent), Nepal (20 

percent), and Ukraine (15 percent). In Turkey, where only ever-married women were interviewed, 28 

percent are current cigarette smokers. The countries with the lowest prevalence of tobacco use for women 

are Egypt, Ghana, Nigeria, Senegal, and Zimbabwe, where less than 1 percent of women age 15-49 use 

any form of tobacco. 

Manufactured cigarettes are the most common type of tobacco used worldwide and they are thus 

responsible for a substantial burden of death and disability among tobacco users. For men, the prevalence 

of cigarette smoking in North Africa/West Asia/Europe and South and Southeast Asia is consistently 

high, ranging from nearly one-third to two-thirds of men (median: 49 percent). The highest prevalence of 

cigarette smoking among men is found in Timor-Leste (66 percent) and Armenia (61 percent). Countries 

in sub-Saharan Africa generally have a lower prevalence of cigarette smoking for men than countries in 

other regions. The countries with the lowest prevalence of current cigarette smoking for men are Ghana (6 

percent), Ethiopia (8 percent), Nigeria (9 percent), and the Dominican Republic (10 percent). 

The prevalence of manufactured cigarette use among women is low in the majority of countries 

examined. In all but 3 of the 47 countries with available data, the prevalence of current cigarette smoking 

among women is less than 10 percent. The three countries with the highest prevalence of cigarette 

smoking for women are Turkey (28 percent), Nepal (15 percent), and Ukraine (15 percent). 

The use of smokeless tobacco, which includes snuff and chewing tobacco, is low in the majority 

of the countries examined for both women and men. In general, the use of smokeless tobacco among men 

is more common in South and Southeast Asia than in any other region. The countries with the highest use 

of smokeless tobacco among men are India (37 percent), Nepal (36 percent), Uzbekistan (32 percent), 

Madagascar (23 percent), and Bangladesh (20 percent). Uzbekistan, India, and Nepal are the only 

countries where men are more likely to use smokeless tobacco than to smoke manufactured cigarettes. 

The countries with the highest use of smokeless tobacco among women are in South and Southeast Asia 

and sub-Saharan Africa (20 percent in Madagascar, 9 percent each in Lesotho and India, 8 percent in 
x 

Cambodia, 5 percent each in Sierra Leone and Nepal, and 4 percent in the Maldives). In all these 

countries except Sierra Leone and Nepal, women are more likely to use smokeless tobacco than to smoke 

manufactured cigarettes. 

The prevalence of cigarette smoking is unevenly distributed in the population, with substantial 

variations in urban and rural areas and by the sociodemographic characteristics of the population. 

Understanding the patterns and predictors of cigarette smoking is important in developing effective 

programs and policies aimed at reducing and eliminating tobacco use. The results show significant 

variation in the prevalence of cigarette smoking for women and men by age, marital status, level of 

education, urban-rural area, employment and cash earnings (women only), occupation (men only), 

household wealth, maternity status, exposure to mass media, and migration status (men only). For women 

and men, the nature and the strength of these associations varies across the countries examined. 

Finally, the report examined the number of cigarettes smoked in the last 24 hours by current 

smokers. This information is important in understanding the potential public health impact of tobacco use. 

Research examining the health consequences of smoking suggests a direct association between adverse 

health outcomes and the duration and level of exposure to tobacco smoke. The analysis shows that the 

number of cigarettes smoked by men who smoke varies across the countries examined, with fewer 

cigarettes generally smoked by men in sub-Saharan Africa. In contrast, in North Africa/West 

Asia/Europe, men who smoked reported smoking the greatest number of cigarettes, with over 80 percent 

of men reporting having smoked 10 or more cigarettes in the last 24 hours. 

The results for women are generally consistent with those found for men. The frequency of 

smoking is generally lower for women in sub-Saharan Africa than for women in other regions. In 

contrast, the frequency of smoking for women who smoke is high in all countries in North Africa/West 

Asia/Europe and Central Asia, with at least 40 percent of smokers saying they smoked 10 or more 

cigarettes in the last 24 hours. 
1 

1 Introduction 

Tobacco use is the leading preventable cause of death and disability worldwide (World Health 

Organization 2002, 2011a). Smoking and tobacco use cause 5.4 million deaths annually (Mathers and 

Loncar 2006) and have been linked to numerous cancers including lung cancer, pancreatic cancer, cancer 

of the larynx, and cervical cancer (U.S. Department of Health and Human Services 2010). Smoking is 

also associated with chronic diseases and other adverse health outcomes, including stroke, coronary heart 

disease, chronic obstructive pulmonary disease (COPD), periodontitis, hip fractures, pneumonia, and 

reduced fertility among women (U.S. Department of Health and Human Services 2010). 

The negative health effects of smoking are not limited to smokers (U.S. Department of Health 

and Human Services 2006). Globally, it has been estimated that exposure to secondhand smoke is 

responsible for more than 600,000 deaths per year, including 166,000 deaths among children (Oberg, 

Jaakkola et al. 2011). Oberg, Jaakkola et al. (2011) also state that most deaths from secondhand smoke in 

adults are caused by ischemic heart disease, asthma, and lung cancer and in children most of these deaths 

are caused by lower respiratory infections. Secondhand smoke is also associated with sudden infant death 

syndrome (Fleming and Blair 2007) and lower birthweight (Jaddoe, Troe et al. 2008). As the prevalence 

of smoking among men often exceeds the prevalence among women, women account for a disproportionate number of deaths from secondhand smoke (Oberg, Jaakkola et al. 2011; U.S. Department of 

Health and Human Services 2006). 

While manufactured cigarettes are the most common form of tobacco used worldwide, other 

types of smoked and smokeless tobacco are widely used in different regions of the world (Shafey et al. 

2009). Other types of smoked tobacco include hand-rolled cigarettes (i.e., “roll-your-own” or RYO), 

pipes, cigars, bidis (small cigarettes hand-rolled in leaf wrappers, most common in India and other South 

Asian countries), kreteks (clove-flavored cigarettes most common in Indonesia), and water pipes (also 

known as qalyan, hookah, narghila, and shisha; most common in Northern Africa, the Mediterranean 

region and parts of Asia). Smokeless tobacco includes chewing tobacco, which is most prevalent in South 

and South East Asia, and snuff. Moist snuff is ground tobacco that is taken orally, while dry snuff is 

inhaled in the nose or taken by mouth. 

Most research examining the adverse health effects of tobacco use has focused on manufactured 

cigarettes given their higher prevalence than other forms of tobacco. However, studies have also 

documented serious health consequences associated with the use of other types of smoked tobacco 

(Baker, Ainsworth et al. 2000; Boffetta, Hecht et al. 2008; Prignot, Sasco et al. 2008; Warnakulasuriya, 

Dietrich et al. 2010). Cigar smoking has been linked to an increased risk of oral cancer, esophageal 

cancer, laryngeal cancer, and lung cancer; and the risk of death from cigar smoking approaches that of 

cigarette smoking as the frequency of smoking and the degree of smoke inhalation increases (Baker, 

Ainsworth et al. 2000). Bidi cigarette smoke delivers significant levels of carbon monoxide, nicotine, and 

tar (Watson, Polzin et al. 2003). Numerous adverse health outcomes have been linked with bidi cigarette 

smoking, including oral cancer, pharyngeal cancer, laryngeal cancer, esophageal cancer, and lung cancer, 

as well as an increased risk of mortality (Prignot, Sasco et al. 2008). The use of kreteks is associated with 

lung cancer, tuberculosis, abnormal lung function, and acute lung injury (Prignot, Sasco et al. 2008). Use 

of the water pipe is associated with an increased risk of lung cancer, tuberculosis, and possibly lip cancer, 

oral cancer, pharyngeal cancer, and gastric cancer (Prignot, Sasco et al. 2008). 

The use of smokeless tobacco has also been linked to deleterious health outcomes. The 

documented health effects of smokeless tobacco vary by region, possibly due to differences in the content 

of the tobacco as well as the quality and availability of studies (Boffetta, Hecht et al. 2008). Smokeless 

tobacco use is associated with an increased risk of oral cancer in studies from the United States and Asia 

and to esophageal cancer and pancreatic cancer in studies from Northern Europe (Boffetta, Hecht et al. 
2 

2008). The small number of studies examining the health consequences associated with the use of nasal 

snuff have shown an increased risk of oral cancer, esophageal cancer, and lung cancer among users 

(Boffetta, Hecht et al. 2008). 

While tobacco use has been declining in many developed countries, it continues to rise in many 

developing countries, and the public health toll of tobacco use is expected to rise in these nations in the 

decades to come (Mathers and Loncar 2006). The World Health Organization (WHO) estimates that the 

estimated number of deaths attributable to tobacco in 2000 was more than one million more than it was in 

1990, with the greatest increase occurring in developing countries (World Health Organization 2002). 

According to WHO estimates, the annual number of deaths globally attributable to tobacco is expected to 

rise from 5.4 million in 2005 to roughly 8.3 million in 2030 (Mathers and Loncar 2006). Moreover, while 

high income countries are expected to experience a decline of 9 percent of deaths attributable to tobacco 

over this period, low to middle-income countries are expected to experience a doubling of deaths 

attributable to tobacco from 3.4 million to 6.8 million (Mathers and Loncar 2006). 

The prevalence of tobacco use varies substantially across regions and across countries. Some of 

the highest prevalence of cigarette smoking among men is found in East Asia, Southeast Asia, Eastern 

Europe, and Central Asia (Eriksen, Mackay and Ross 2012). According to data published in the WHO 

Global Status Report on Noncommunicable Diseases (2011b), countries with more than a 50 percent 

prevalence of tobacco smoking among men include Armenia, Belarus, the Democratic People's Republic 

of Korea, Greece, Indonesia, Kiribati, Papua New Guinea, the Republic of Korea, the Russian Federation, 

Samoa, Tunisia, and Ukraine. 

For women, the regions with the highest prevalence of cigarette smoking are Europe and parts of 

the Pacific, Latin America and the Caribbean (Eriksen, Mackay and Ross 2012). In contrast to men, 

cigarette smoking among women in East Asia and South and Southeast Asia is relatively low (Eriksen, 

Mackay and Ross 2012). Countries with at least 30 percent prevalence of cigarette smoking among 

women include Austria, Chile, Greece, Kiribati, Lebanon, and Nauru (World Health Organization 2011b). 

This report was prepared to provide recent, nationally representative estimates of tobacco use for 

women and men across a large number of developing countries in one document. Currently, there is a 

lack of comparable, high-quality data on tobacco use across countries. While the Global Adult Tobacco 

Survey (GATS) provides comprehensive data on tobacco use (Giovino, Mirza et al. 2012), it has thus far 

been conducted only in 14 countries. GATS is a component of the Global Tobacco Surveillance System 

(GTSS), which has been developed by the World Health Organization, CDC, and the Canadian Public 

Health Association (CPHA). The Demographic and Health Surveys (DHS) provide high-quality, 

nationally representative, population-based data, on selected key tobacco-use indicators in a much larger 

number of countries. Data from the DHS have been collected using similar sampling methods, 

populations surveyed, field procedures, quality control measures, and questions assessing tobacco use. 

Specifically, this report provides nationally representative estimates of cigarette smoking and 

tobacco use in 49 countries in sub-Saharan Africa, North Africa/West Asia/Europe, Central Asia, South 

and Southeast Asia, and Latin America and the Caribbean (see Map). Data from the most recent DHS 

conducted in each of the countries with available data on current tobacco use are included in this analysis. 

The surveys included in this report cover a time span between 1999 and 2010; therefore, caution should 

be used when comparing the prevalence of tobacco use across the countries. 

The first section of the report describes the use of manufactured cigarettes, other smoked tobacco 

products, and smokeless tobacco across the countries studied. While gender differences in tobacco use 

vary across regions, the World Health Organization estimates that on average, men are four times more 

likely to use tobacco than women (World Health Organization 2003a). 
3 

Therefore, to explore the role that gender plays in tobacco use, estimates are presented separately 

for women and men. 

Within countries, the prevalence of tobacco use often varies geographically and across sociodemographic characteristics of the population. To develop effective programs and policies aimed at 

reducing and eliminating tobacco use, it is important to understand the profile of tobacco users (World 

Health Organization 2003b; World Health Organization 2011a, 2011b). The second section of the report 

examines the sociodemographic characteristics associated with use of manufactured cigarettes for women 

and men. The analysis focuses on manufactured cigarettes since this is the most prevalent form of tobacco 

used worldwide. The characteristics that were examined include age, marital status, education, urban-rural 

area, employment status in the last 12 months (women only), cash earnings (women only), occupational 

status (men only), household wealth, maternity status (women only), exposure to mass media, and 

migration status (men only). 

The last section of this report describes the number of cigarettes smoked in the last 24 hours for 

men and women who reported currently smoking cigarettes. This information is important in 

understanding the potential public health impact of tobacco use. According to the Surgeon General’s 

Report, although “there is no risk-free level of exposure to tobacco smoke....the risk and severity of many 

adverse health outcomes caused by smoking are directly related to the duration and level of exposure to 

tobacco smoke” (U.S. Department of Health and Human Services 2010). Information on duration of 

smoking was not available for this analysis; however the data presented on the number of cigarettes 

smoked in the last 24 hours before the interview by male and female cigarette smokers provide a measure 

of the level of exposure to tobacco smoke. 
4
5 

2 Data and Methods 

Data for this report were obtained from DHS surveys, which are nationally representative 

household surveys conducted in developing countries. The DHS project, initiated in 1984, has a key 

mandate to collect information on demographic, health, and nutrition indicators. Mainly funded by the 

United States Agency for International Development (USAID), the DHS has been administered in more 

than 90 developing countries around the world. In conducting a survey within a country, DHS staff works 

with an implementing agency (e.g., a National Statistics Office, Ministry of Health, or university) and 

provide technical assistance for the implementation of the survey, analysis, report writing, and 

dissemination. 

The DHS uses a multi-stage, stratified sampling design with households as the sampling unit. 

Within each sample household, all women and men meeting the eligibility criteria are eligible to be 

interviewed. Because the surveys are not self-weighting, survey weights are calculated to account for 

unequal selection probabilities as well as survey non-response. With weights applied, survey findings 

represent the full target populations. 

The DHS surveys include a household questionnaire, a women’s questionnaire, and in most 

countries, a men’s questionnaire. The household questionnaire is used to identify all usual household 

members and visitors in the selected households and to determine the eligibility of all household members 

for the individual women’s and men’s surveys. All three DHS questionnaires are implemented across 

countries with similar interviewer training, supervision, and implementation protocols. While the 

respondent for the household questionnaire can be any responsible adult in the household, the respondents 

for the woman’s and man’s questionnaires are the eligible individuals themselves. 

The DHS questionnaires include a number of different sections that collect information on a wide 

range of population, reproductive, nutrition, and health-related issues. While household socioeconomic 

status information is collected using the household questionnaire, topics covered in the individual 

questionnaires include fertility; family planning; infant and child mortality; maternal health; child health; 

HIV/AIDS knowledge, attitudes, and behavior; malaria; and women’s empowerment. A number of 

countries also include questions in the woman’s and man’s questionnaires assessing tobacco use and 

exposure to secondhand smoke. The current analysis uses DHS data from countries with information on 

self-reported current tobacco use by women and men. 

2.1 Data 

Data from 49 countries that conducted DHS surveys between 1999 and 2010 and that included 

questions on self-reported tobacco use were used for this report. In countries with multiple DHS surveys, 

the most recent data were used to provide the most up-to-date estimates of tobacco use. For the Peru 

2004/08 continuous survey, only data from the last two rounds of the survey (2007/08) were used in order 

to describe the most recent situation in that country. The countries that are included in this report are 

regionally diverse, including 25 countries from sub-Saharan Africa, eight countries from North 

Africa/West Asia/Europe, two countries from Central Asia, eight countries from South and Southeast 

Asia, and six countries from Latin America and the Caribbean. Table 1 describes the countries included in 

this report, the sample sizes for each country survey, the year(s) of fieldwork, and the eligibility criteria 

for the surveys for women and men.1

 

 

1

 For more information about the DHS, including the methods used and questions administered, please visit the 

following website: http://www.measuredhs.com/ 
6 

Table 1. Summary of Demographic and Health Surveys included in this report, 1999-2010 

Region and country 

Year of 

survey 

Number of 

men 

interviewed

Eligibility criteria 

for men 

interviewed 

Number of 

women 

interviewed 

Eligibility criteria 

for women 

interviewed 

Sub-Saharan Africa 

 Benin 2006 na na 17,794 all women 15-49 

 Burkina Faso 2003 na na 12,477 all women 15-49 

 Cameroon 2004 na na 10,656 all women 15-49 

 Congo, Democratic Republic 2007 na na 9,995 all women 15-49 

 Ethiopia 2005 6,033 all men 15-59 14,070 all women 15-49 

 Ghana 2008 4,568 all men 15-59 4,916 all women 15-49 

 Guinea 2005 na na 7,954 all women 15-49 

 Kenya 2008/09 3,465 all men 15-54 8,444 all women 15-49 

 Lesotho 2009 3,317 all men 15-59 7,624 all women 15-49 

 Liberia 2007 6,009 all men 15-49 7,092 all women 15-49 

 Madagascar 2008/09 8,586 all men 15-59 17,375 all women 15-49 

 Malawi 2004 3,261 all men 15-54 11,698 all women 15-49 

 Mali 2006 na na 14,583 all women 15-49 

 Mozambique 2003 2,900 all men 15-64 12,418 all women 15-49 

 Namibia 2006/07 3,915 all men 15-49 9,804 all women 15-49 

 Niger 2006 na na 9,223 all women 15-49 

 Nigeria 2008 15,486 all men 15-59 33,385 all women 15-49 

 Rwanda 2005 4,820 all men 15-59 11,321 all women 15-49 

 Senegal 2005 na na 14,602 all women 15-49 

 Sierra Leone 2008 3,280 all men 15-59 7,374 all women 15-49 

 Swaziland 2006/07 4,156 all men 15-49 4,987 all women 15-49 

 Tanzania 2004/05 2,635 all men 15-49 10,329 all women 15-49 

 Uganda 2006 2,503 all men 15-54 8,531 all women 15-49 

 Zambia 2007 6,500 all men 15-59 7,146 all women 15-49 

 Zimbabwe 2005/06 7,175 all men 15-54 8,907 all women 15-49 

North Africa/West Asia/Europe

 Albania 2008/09 3,013 all men 15-49 7,584 all women 15-49 

 Armenia 2005 1,447 all men 15-49 6,566 all women 15-49 

 Azerbaijan 2006 2,558 all men 15-59 na na 

 Egypt1 2008 5,430 all men 15-59 5,824 all women 15-49 

 Jordan 2009 na na 10,109 ever-married women 

15-49 

 Moldova 2005 2,508 all men 15-59 7,440 all women 15-49 

 Turkey 2003 na na 8,075 ever-married women 

15-49 

 Ukraine 2007 3,178 all men 15-49 6,841 all women 15-49 

Central Asia 

 Kazakhstan 1999 na na 4,800 all women 15-49 

 Uzbekistan 2002 2,333 all men 15-59 5,463 all women 15-49 

Continued... 

 
7 

Table 1—Continued 

Region and country 

Year of 

survey 

Number of 

men 

interviewed

Eligibility criteria 

for men 

interviewed 

Number of 

women 

interviewed 

Eligibility criteria 

for women 

interviewed 

South and Southeast Asia 

 Bangladesh 2007 3,771 ever-married men 

15-54 

na Na 

 Cambodia 2005 na na 16,823 all women 15-49 

 India 2005/06 74,369 all men 15-54 124,385 all women 15-49 

 Indonesia 2007 na na 32,895 ever-married women 

15-49 

 Maldives2

 2009 1,727 ever-married men 

15-64 

7,131 ever-married women 

15-49 

 Nepal 2006 4,397 all men 15-59 10,793 all women 15-49 

 Philippines 2008 na na 13,594 all women 15-49 

 Timor-Leste 2009/10 4,076 all men 15-49 13,137 all women 15-49 

Latin America/Caribbean 

 Bolivia 2008 6,054 all men 15-64 16,939 all women 15-49 

 Dominican Republic 2007 27,975 all men 15-59 27,195 all women 15-49 

 Haiti 2005/06 4,958 all men 15-59 10,757 all women 15-49 

 Honduras 2005/06 na na 19,948 all women 15-49 

 Nicaragua 2001 na na 13,060 all women 15-49 

 Peru 2007/08 na na 22,558 all women 15-49 

na: Not available 

1

While the Egypt DHS includes women age 15-59, this analysis was restricted to those age 15-49. 2

The response rate for the men's survey in the 2009 Maldives DHS was inordinately low (interviews were completed 

with only 54 percent of the men who were eligible for interview). 

With the exception of Jordan, which is an interim survey, all of the surveys that are included in 

this report are standard DHS surveys. Interim surveys are also nationally representative, but usually 

involve shorter questionnaires and smaller sample sizes than standard DHS surveys. For the analysis that 

examined the sociodemographic correlates of smoking, Jordan has missing information because some of 

the covariates were not assessed in its survey. For almost all of the countries, the estimates of tobacco use 

that are presented in this report are based on data collected from the individual women’s and men’s 

questionnaires. In Egypt, however, the estimates are based on data collected from women and men in the 

households selected for the Health Issues sub-sample, which was administered to one-quarter of the 

households selected for the DHS survey. 

In most of the countries, all women age 15-49 in the selected households were eligible for the 

individual women’s interview. Thus, in most of the countries, the tobacco use estimates for women 

describe the prevalence among all women age 15-49. In four countries included in this report, namely 

Jordan, Turkey, Indonesia, and the Maldives, only ever-married women age 15-49 were eligible for the 

interview. Since tobacco use is often higher for ever-married women than for never married women (see 

Appendix Table A.2), caution should be used when comparing estimates for these four countries with 

estimates for countries that did not restrict eligibility based on marital status. The Egypt survey subsample 

on health topics was the only survey for women that used different age eligibility criteria; women age 

15-59 were interviewed. However, since this was the only country that differed on this characteristic, the 
8 

tobacco use estimates for Egyptian women are only presented for those age 15-49 to reflect the age 

criteria used in all other countries. 

The eligibility criteria for the men’s questionnaire varied across the countries. The lower age 

cutoff for men in all of the countries was 15 years of age, while the upper age cutoff varied from 49 to 64 

years. To allow comparisons by sex, estimates of tobacco use for men are given for those age 15-49 to 

reflect the age range of the women’s surveys. Estimates for men are also presented for the full age range 

within each of the countries. While most countries interviewed men of all marital status groups, 

Bangladesh and the Maldives only interviewed ever-married men. Again, caution should be used when 

comparing estimates of tobacco use in countries with different eligibility criteria given that tobacco use 

varies by age and by marital status in most of the countries. 

Two countries that are examined in this report included the tobacco use questions in the men’s 

questionnaire but did not include them in the women’s questionnaire (Azerbaijan, Bangladesh). 

Therefore, no estimates of tobacco use are presented for women in these countries. A larger number of 

countries either did not include the tobacco use questions in the men’s questionnaire (Benin, Burkina 

Faso, Cambodia, Cameroon, Democratic Republic of Congo, Guinea, Kazakhstan, Mali, Niger, Senegal) 

or did not interview men at all (Haiti, Honduras, Jordan, Nicaragua, Peru, Philippines, Turkey). 

Therefore, it was not possible to estimate tobacco use among men in these countries. Although tobacco 

use for men was assessed in the Indonesia DHS, these results were excluded from the report since the 

tobacco questions were only asked of men with young children. 

2.2 Definition of Variables 

Tobacco use 

In a large proportion of the countries, a standard set of tobacco use questions was included in the 

women’s and men’s questionnaires. However, depending on the version of the DHS2

 administered and the 

specific country, some of the questions were asked in slightly different ways. The specific questions that 

were used to assess current cigarette use, current use of other smoked tobacco, and current use of 

smokeless tobacco are described in the sections that follow. 

Currently smokes manufactured cigarettes. The specific DHS questions that were used to assess 

current manufactured (i.e., commercial) cigarette use in each of the countries are presented in Table 2. In 

over half of the countries studied, respondents were explicitly asked “Do you currently smoke 

cigarettes?” Those who responded ‘yes’ to this question were defined as current manufactured cigarette 

smokers, whereas those who responded ‘no’ were defined as current non-smokers. 

In most of the remaining countries, respondents were first asked whether they currently smoked 

cigarettes or tobacco. There are some slight variations in the wording of this question across the countries. 

Those who responded in the affirmative to this question were then asked to report the type(s) of tobacco 

that they smoked or used. The interviewer did not specifically probe about the use of cigarettes. Those 

who spontaneously reported smoking cigarettes were identified as current cigarette smokers, whereas 

those who did not report smoking cigarettes were identified as current non-smokers. 

The Turkey 2003 DHS included one question asking respondents whether they ever smoked or 

currently smoke cigarettes and a follow-up question for smokers on the frequency with which they smoke 

on average. Those who reported currently smoking were identified as current smokers, whereas those who 

 

2

 DHS questionnaires typically undergo a review every five years or so. This review can result in some questions 

being changed or dropped, and others added. 
9 

reported either having never smoked or having smoked in the past but not currently were identified as 

non-smokers. 

For the most part, the questions assessing current cigarette use are comparable across the 

countries. However, in three of the countries, the current cigarette use variable has a slightly different 

meaning. In India and Bangladesh, respondents were asked if they currently used ‘cigarettes or bidis’. It 

was not possible to disaggregate these forms of tobacco in these countries and therefore the estimates that 

are presented reflect the use of either or both of these types of cigarettes. In Uzbekistan, only those who 

smoked at least 100 cigarettes during their entire life were asked whether they currently smoked 

cigarettes. Therefore, it is possible that the prevalence of current cigarette use for Uzbekistan is a slight 

underestimate since it might exclude those who recently initiated cigarette use as well as those who 

smoke infrequently. 

Table 2. DHS questions assessing current cigarette use 

Questions Countries 

Do you currently smoke cigarettes? 

Do you smoke cigarettes? (Jordan) 

Albania 2008/09 

Armenia 2005 

Azerbaijan 2006 

Bolivia 2008 

Cambodia 2005 

Dominican Republic 2007 

Egypt 2008 

Ethiopia 2005 

Ghana 2008 

Haiti 2005/06 

Honduras 2005/06 

Indonesia 2007 

Jordan 2009 

Kenya 2008/09 

Lesotho 2009 

Liberia 2007 

Madagascar 2008/09 

Maldives 2009 

Moldova 2005 

Nepal 2006 

Nigeria 2008 

Peru 2007/08 

Philippines 2008 

Sierra Leone 2008 

Swaziland 2006/07 

Timor-Leste 2009/10 

Uganda 2006 

Ukraine 2007 

Zambia 2007 

Zimbabwe 2005/06 

Continued... 
10 

Table 2—Continued

Questions Countries 

Do you currently smoke cigarettes or tobacco? 

IF YES: What do you smoke? 

IF YES: What type of tobacco do you smoke? (Kazakhstan, Tanzania) 

Burkina Faso 2003 

Democratic Republic of Congo 2007 

Guinea 2005 

Kazakhstan 1999 

Rwanda 2005 

Senegal 2005 

Tanzania 2004/05 

Do you currently smoke cigarettes or consume tobacco? 

IF YES: What type of tobacco do you consume? 

Cameroon 2004 

Do you currently smoke cigarettes or use tobacco? 

IF YES: What type of tobacco do you use? 

Malawi 2004 

Currently do you chew or smoke or consume cigarettes or tobacco? 

IF YES: What do you chew, consume or smoke? 

Benin 2006 

Do you currently smoke cigarettes or chew tobacco? 

IF YES: What do you smoke or chew? 

Mali 2006 

Niger 2006 

Do you currently smoke cigarettes or consume another kind of tobacco? Mozambique 2003 

Do you currently smoke any type of tobacco? Namibia 2006/07 

Do you smoke cigarettes or puro (cigar) or pipe currently? Nicaragua 2001 

Have you ever smoked cigarettes or do you currently smoke? 

(IF YES) How frequent? 

Turkey 2003 

Have you smoked at least 100 cigarettes during your entire life? Do you 

smoke cigarettes now? 

Uzbekistan 2002 

Do you currently smoke cigarettes or bidis? Bangladesh 2007 

India 2005/06 

Currently using other types of smoked tobacco. Other types of smoked tobacco (excluding 

manufactured cigarettes) include pipes, cigars, hand-rolled cigarettes, kreteks, and water pipes (e.g., 

qalyan, shisha, nargila, hookah). The specific DHS questions that were used to assess these other types of 

smoked tobacco are presented in Table 3 and are described below. These other forms of smoked tobacco 

were not assessed in Bolivia, Honduras, Peru, Turkey, and Uzbekistan. 

In about half of the countries studied, respondents were first asked whether they currently smoke 

cigarettes, after which they were asked about their use of other types of tobacco. Specifically, respondents 

were asked “Do you currently smoke or use any other type of tobacco?” Those who reported yes to this 

question were then asked to specify the type(s) of tobacco that they currently smoke or use. In the 

majority of the remaining countries, respondents were first asked whether they currently smoke or use 
11 

cigarettes or tobacco. There are some slight variations in the wording of this question across the countries. 

Those who responded yes were then asked to report the specific type(s) of tobacco that they smoke or use. 

In almost all of the countries, the interviewer did not probe respondents about their use of specific types 

of tobacco. Rather, they noted all types of smoked tobacco that were spontaneously reported by the 

respondent. Those who reported having used at least one type of smoked tobacco other than cigarettes 

(i.e., pipes, cigars, hand-rolled cigarettes, water pipes) were identified as current users of other types of 

smoked tobacco, whereas those who did not report using any type of smoked tobacco (not including 

cigarettes) were identified as current non-users. 

In Jordan, respondents were asked whether they smoked nargila (i.e., water pipe), and therefore 

the prevalence of ‘other smoked tobacco’ for Jordan only reflects this one type of tobacco. 

It should be noted that not all of the DHS datasets for the countries included the same set of 

variables for the various types of smoked tobacco. In most of the countries, a variable indicating the use 

of a pipe was present in the dataset. In countries where certain types of smoked tobacco were common 

(e.g., hand-rolled cigarettes, water pipes), variables for these types of tobacco may have been included in 

the dataset. However, in other countries, these forms of smoked tobacco may have been coded as ‘other’ 

tobacco. Similarly, some of the more recent surveys specifically included a variable indicating cigar use 

in the dataset, while for some of the older surveys, cigar use may have been coded as ‘other’ tobacco and 

therefore would not have been captured specifically as cigar use in this analysis. 

Table 3. DHS questions assessing current use of other types of smoked tobacco (excluding 

cigarettes) 

Questions Countries 

Do you currently smoke or use any other type of tobacco? 

What (other) type of tobacco do you currently smoke or use? 

Do you currently smoke or use tobacco in any other form? (India) 

In what other form do you currently smoke or use tobacco? (India) 

Albania 2008/09 

Armenia 2005 

Azerbaijan 2006 

Bangladesh 2007 

Cambodia 2005 

Dominican Republic 2007 

Egypt 2008 

Ghana 2008 

Haiti 2005/06 

India 2005/06 

Kenya 2008/09 

Lesotho 2009 

Liberia 2007 

Madagascar 2008/09 

Maldives 2009 

Moldova 2005 

Nepal 2006 

Nigeria 2008 

Philippines 2008 

Sierra Leone 2008 

Swaziland 2006/07 

Timor-Leste 2009/10 

Continued... 
12 

Table 3—Continued

Questions Countries 

Uganda 2006 

Ukraine 2007 

Zambia 2007 

Zimbabwe 2005/06 

Do you currently smoke cigarettes or tobacco? 

IF YES: What do you smoke? 

IF YES: What type of tobacco do you smoke? (Kazakhstan, Tanzania) 

Burkina Faso 2003 

Democratic Republic of Congo 2007 

Guinea 2005 

Kazakhstan 1999 

Rwanda 2005 

Senegal 2005 

Tanzania 2004/05 

Do you currently smoke cigarettes or consume tobacco? 

IF YES: What type of tobacco do you consume? 

Cameroon 2004 

Do you currently smoke cigarettes or use tobacco? 

IF YES: What type of tobacco do you use? 

Malawi 2004 

Currently do you chew or smoke or consume cigarettes or tobacco. 

IF YES: What do you chew, consume or smoke? 

Benin 2006 

Do you currently smoke cigarettes or chew tobacco? 

IF YES: What do you smoke or chew? 

Mali 2006 

Niger 2006 

Do you currently smoke cigarettes or consume another kind of tobacco? Mozambique 2003 

Do you currently smoke any type of tobacco? Namibia 2006/07 

Do you smoke cigarettes, or pure, or pipe currently? Nicaragua 2001 

Do you currently smoke cigarettes? 

IF YES: What type of cigarettes do you smoke? 

Indonesia 2007 

Do you currently smoke or use any other type of tobacco like gaya, shisha

or suret? 

What (other) type of tobacco do you currently smoke or use? 

Ethiopia 2005 

Do you smoke nargila? Jordan 2007 

Currently using smokeless tobacco. Smokeless tobacco includes chewing tobacco and snuff. The 

specific DHS questions that were used to assess the use of smokeless tobacco are presented in Table 4. 

This information was either not collected or was not specifically coded in the following countries: 

Albania, Benin, Bolivia, Burkina Faso, Cameroon, Guinea, Honduras, Indonesia, Jordan, Kazakhstan, 

Mali, Mozambique, Nicaragua, Niger, Peru, Rwanda, Senegal, Tanzania, and Turkey. 

In the majority of the countries studied, respondents were first asked whether they currently 

smoke cigarettes, after which they were asked about their use of other types of tobacco. Specifically, 
13 

respondents were asked “Do you currently smoke or use any other type of tobacco?” Those who reported 

yes to this question were then asked to specify the type(s) of tobacco that they currently smoke or use. In 

the majority of the remaining countries, respondents were first asked whether they currently smoke or use 

cigarettes or tobacco. There are some slight variations in the wording of this question across the countries. 

Those who responded yes to this question were then asked to report the specific type(s) of tobacco that 

they smoke or use. In almost all of the countries, the interviewer did not probe about their use of specific 

types of tobacco. Rather, they noted all types of smokeless tobacco that were spontaneously reported by 

the respondent. Those who reported having used snuff, chewing tobacco, or both were identified as 

current users, whereas those who did not report using any type of smokeless tobacco were identified as 

non-users. 

In Uzbekistan, respondents were specifically asked whether they currently used nas (i.e., naswhy, 

a homemade chewing tobacco made of tobacco, butter, and chalk (slaked lime)), and therefore the 

prevalence of smokeless tobacco for Uzbekistan only reflects this one type of tobacco. 

Table 4. DHS questions assessing current use of smokeless tobacco 

Questions Countries 

Do you currently smoke or use any other type of tobacco? 

What (other) type of tobacco do you currently smoke or use? 

Do you currently smoke or use tobacco in any other form? (India) 

In what other form do you currently smoke or use tobacco? (India) 

Armenia 2005 

Azerbaijan 2006 

Bangladesh 2007 

Cambodia 2005 

Dominican Republic 2007 

Egypt 2008 

Ghana 2008 

Haiti 2005/06 

India 2005/06 

Kenya 2008/09 

Lesotho 2009 

Liberia 2007 

Madagascar 2008/09 

Maldives 2009 

Moldova 2005 

Nepal 2006 

Nigeria 2008 

Philippines 2008 

Sierra Leone 2008 

Swaziland 2006/07 

Timor-Leste 2009/10 

Uganda 2006 

Ukraine 2007 

Zambia 2007 

Zimbabwe 2005/06 

Do you currently smoke cigarettes or tobacco? 

IF YES: What do you smoke? 

Democratic Republic of Congo 2007 

Continued... 
14 

Table 4—Continued

Questions Countries 

Do you currently smoke cigarettes or use tobacco? 

IF YES: What type of tobacco do you use? 

Malawi 2004 

Do you currently smoke any type of tobacco? Namibia 2006/07 

Do you currently smoke or use any other type of tobacco like gaya, shisha

or suret? 

What (other) type of tobacco do you currently smoke or use? 

Ethiopia 2005 

Do you use nas now? Uzbekistan 2002 

Currently using any tobacco. Respondents who reported currently using cigarettes, other types of 

smoked tobacco, smokeless tobacco, or any other type of tobacco were identified as current tobacco users. 

Those who did not report any type of tobacco use were identified as non-users. Countries that only 

assessed the use of cigarettes were not included in the analysis of any tobacco use. 

Number of cigarettes smoked in the last 24 hours. The questions assessing the number of 

cigarettes smoked in the last 24 hours are presented in Table 5. This question was excluded in Malawi and 

Jordan. In the vast majority of the countries, the same question was included in the survey. Respondents 

who reported currently smoking cigarettes were asked “In the last 24 hours, how many cigarettes did you 

smoke?” 

In five of the countries, there were slight variations in the wording of this question. In Namibia, 

respondents were asked to report the number of cigarettes, including rolled cigarettes, that they smoked in 

the last 24 hours. It was not possible to disaggregate cigarettes and rolled cigarettes; therefore, the 

estimates that are presented include both types of cigarettes. Similarly, in India, respondents were asked 

about the number of cigarettes or bidis (i.e., hand-rolled cigarettes) that they smoked in the last 24 hours. 

Again, it was not possible to disaggregate these types of cigarettes in the analysis. Although Bangladesh 

also asked about the number of cigarettes and bidis smoked in the last 24 hours, they were coded 

separately in the dataset and therefore only data assessing the number of cigarettes smoked are presented. 

In Turkey and Uzbekistan, respondents were asked about the average number of cigarettes smoked per 

day, rather than the number smoked in the last 24 hours. Finally, data for Kazakhstan were excluded from 

this analysis since respondents were asked about the number of times they smoked in the last 24 hours, 

rather than the number of cigarettes they smoked. 

For ease of presentation, the number of cigarettes smoked in the last 24 hours was recoded into a 

categorical variable with the following categories: 0, 1-2, 3-5, 6-9, 10 or more, and don’t know/missing. 

For all countries, non-smokers are excluded from this analysis. 
15 

Table 5. DHS questions assessing number of cigarettes smoked in the last 24 hours 

Questions Countries 

In the last 24 hours, how many cigarettes did you smoke? 

In the last 24 hours, how many sticks of cigarettes did you smoke? (Ghana) 

Albania 2008/09 

Armenia 2005 

Azerbaijan 2006 

Bangladesh 2007 

Benin 2006 

Bolivia 2008 

Burkina Faso 2003 

Cambodia 2005 

Cameroon 2004 

Democratic Republic of Congo 2007 

Dominican Republic 2007 

Egypt 2008 

Ethiopia 2005 

Ghana 2008 

Guinea 2005 

Haiti 2005/06 

Honduras 2005/06 

Indonesia 2007 

Kenya 2008/09 

Lesotho 2009 

Liberia 2007 

Madagascar 2008/09 

Maldives 2009 

Mali 2006 

Moldova 2005 

Mozambique 2003 

Nepal 2006 

Nicaragua 2001 

Niger 2006 

Nigeria 2008 

Peru 2007/08 

Philippines 2008 

Rwanda 2005 

Senegal 2005 

Sierra Leone 2008 

Swaziland 2006/07 

Tanzania 2004/05 

Timor-Leste 2009/10 

Uganda 2006 

Ukraine 2007 

Zambia 2007 

Zimbabwe 2005/06 

Continued... 
16 

Table 5—Continued

Questions Countries 

In the last 24 hours, how many cigarettes, including rolled cigarettes, did 

you smoke? 

Namibia 2006/07 

In the last 24 hours, how many cigarettes or bidis did you smoke? India 2005/06 

How many cigarettes do you smoke per day on the average? Turkey 2003 

About how many cigarettes do you smoke per day? Uzbekistan 2002 

In the last 24 hours, how many times did you smoke? Kazakhstan 1999 

Sociodemographic characteristics 

The sociodemographic characteristics that were examined in this analysis were selected based on 

previous research showing differences in cigarette use across these factors. These characteristics include 

age group of the respondent (15-24, 25-34, 35-49, 50 years and over), marital status (never married, 

currently married, formerly married), highest level of education (no education, primary, secondary, 

higher), urban-rural area, employment status in the last 12 months for women (yes vs. no), cash earnings 

for women (yes vs. no), occupational status for men (not working, professional/technical/managerial, 

clerical, sales and services, skilled manual, unskilled manual, agriculture), household wealth quintile 

(described below), maternity status for women (pregnant, breastfeeding, neither), exposure to mass media 

(described below), and migration status for men (described below). 

The wealth status of the household was determined using a wealth index constructed separately 

for each country. Specifically, the wealth index was constructed using household asset data, including 

ownership of a number of consumer items such as a television, a bicycle or a car, as well as dwelling 

characteristics such as source of drinking water, sanitation facilities, and type of flooring material. Each 

asset was assigned a weight generated through principal components analysis. The resulting asset scores 

were standardized in relation to a normal distribution with a mean of zero and a standard deviation of one 

(Gwatkin, Rutstein et al. 2000). Each household was then assigned a score for each asset, and the scores 

were summed for each household. Individuals were ranked according to the score of the household in 

which they were interviewed. Within each country, the sample was then divided into quintiles from one 

(lowest) to five (highest). This wealth index is consistent with expenditure and income measures and has 

been used in a large number of countries (Rutstein and Johnson 2004). 

A number of variables assessing exposure to mass media were examined, including whether or 

not the respondents read newspapers, watched television, and listened to the radio at least once a week. 

Two binary variables were also created to describe the amount or diversity of exposure to different types 

of media. The first binary variable differentiated those who used all three forms of media at least once a 

week from those who did not use all three forms of media at least once a week. The second binary 

variable differentiated those who used any form of media at least once a week from those who did not use 

any form of media at least once a week. Finally, migration status for men was assessed based on the 

number of times men reported that they slept away from home in the last 12 months (none, 1-4, 5 or 

more). 
17 

2.3 Analyses 

The first analysis describes the proportion of the population within each of the countries that 

reported currently using manufactured cigarettes, other types of smoked tobacco, smokeless tobacco, and 

any type of tobacco. Analyses were conducted separately for women and men. To examine the 

association between the sociodemographic characteristics and current cigarette use, chi-square tests were 

conducted. Finally, the number of cigarettes smoked in the last 24 hours was examined for current 

cigarette smokers within each of the countries. All analyses were weighted to ensure that nationally 

representative estimates were obtained. The analyses also estimate the standard errors taking into account 

the clustered and stratified sampling design using Stata’s svy commands. All analyses were conducted 

using Stata 11.2 (StataCorp 2009).3

 

3

 The use of trade names is for identification only and does not imply endorsement by the Public Health Service, 

U.S. Department of Health and Human Services. 

19 

3 Results: Prevalence of Tobacco Use among Women and Men

This section describes the proportion of women and men age 15-49 who report currently using 

manufactured cigarettes, other smoked tobacco products, and smokeless tobacco across the countries 

(Tables 6a for men and Table 6b for women). The results for the entire age range of men interviewed in 

each of the countries are shown in Appendix Table A4. These estimates are weighted and are nationally 

representative of the population within each country. 

3.1 Prevalence of Any Tobacco Use 

Any type of tobacco includes manufactured cigarettes, other types of smoked tobacco (handrolled cigarettes or “roll-your-own” (RYO), pipe, cigars, bidis, kreteks, water pipe), smokeless tobacco 

(chewing tobacco or snuff), and any other type of tobacco reported by respondents. Countries that only 

assessed the use of cigarettes are not included in this section, but are included in the section on cigarette 

use. 

Prevalence of any tobacco use among men 

The prevalence of any tobacco use among men age 15-49 varies widely worldwide, from a low of 

7 percent in Ghana to a high of 69 percent in Bangladesh and Timor-Leste (Table 6a). These results are 

also illustrated in Figure 1. In sub-Saharan Africa, tobacco use was lowest in Ghana (7 percent), Ethiopia 

(11 percent), and Nigeria (12 percent) and was highest in Madagascar (47 percent), Sierra Leone (37 

percent), and Lesotho (34 percent). In fact, of all of the countries examined in this report, the countries 

with the lowest prevalence of tobacco use for men are found in sub-Saharan Africa. In no country in subSaharan Africa did the prevalence of tobacco use among men exceed 50 percent. Madagascar is the only 

country in sub-Saharan Africa where the prevalence exceeded 40 percent. 

In contrast to countries in sub-Saharan Africa, which had more variable prevalence estimates of 

tobacco use for men, the countries examined in North Africa/West Asia/Europe had a consistently high 

prevalence of tobacco use. At least 40 percent of men in these countries reported using one or more forms 

of tobacco. The prevalence of tobacco use among men age 15-49 in these countries ranged from a low of 

43 percent in Albania and Egypt to a high of 61 percent in Armenia. 

Tobacco use for men was also high, exceeding 50 percent, in the one country examined in Central 

Asia (Uzbekistan, 51 percent), as well as in all countries examined in South and Southeast Asia, (ranging 

from 53 percent in the Maldives and Nepal to 69 percent in Bangladesh and Timor-Leste). Of all of the 

countries examined in this report, the highest prevalence of current tobacco use for men was found in 

Bangladesh and Timor-Leste, with about 7 out of 10 men age 15-49 reporting currently using at least one 

form of tobacco. Note that for Bangladesh and the Maldives, only ever-married men were interviewed. 

Given that the prevalence of smoking is usually higher for ever-married men than for never-married men 

(see Appendix Table A1), the estimates for these two countries are likely to be higher than would be the 

case if never-married men had also been included in the sample. 

Finally, in Latin America and the Caribbean, the Dominican Republic was the only country in 

which ‘any tobacco’ use was estimated for men. Relatively few men in the Dominican Republic reported 

using any type of tobacco (12 percent). As will be discussed in the section on manufactured cigarette use, 

a larger proportion of men in Bolivia reported smoking manufactured cigarettes (41 percent). 
Table 6a. Percentage of men age 15-49 who currently smoke cigarettes or use other tobacco products by country and region, 1999-

2010 Region and Country 

Year of survey

Percent 

using 

any 

tobacco (95% CI)

Percent using manufactured 

cigarettes (95% CI) 

Percent 

using 

other 

smoked 

tobacco (95% CI)

Percent 

using 

smokeless 

tobacco (95% CI)

Sub-Saharan Africa  Ethiopia 2005 10.6 (9.3-11.9) 8.1 (7.0-9.3) 1.0 (0.5-1.5) 3.0 (2.3-3.7)

 Ghana 2008 6.8 (5.9-7.6) 6.2 (5.4-7.0) 0.6 (0.3-0.8) 0.9 (0.6-1.3)

 Kenya 2008/09 18.9 (16.5-21.2) 17.5 (15.2-19.8) 1.1 (0.4-1.8) 1.8 (1.2-2.4)

 Lesotho 2009 34.5 (32.4-36.6) 34.5 (32.4-36.6) 5.7 (4.8-6.6) 1.3 (0.8-1.7)

 Liberia 2007 16.2 (14.6-17.8) 15.2 (13.6-16.7) 0.8 (0.4-1.2) 2.3 (1.6-3.1) Madagascar 2008/09 47.3 (45.6-49.0) 28.2 (26.7-29.7) 1.7 (1.3-2.1) 22.6 (20.9-24.3)

 Malawi 2004 20.7 (18.6-22.7) 16.3 (14.5-18.1) 0.1 (0.0-0.2) 0.3 (0.2-0.5) Mozambique 2003 24.3 (21.9-26.6) 14.2 (12.4-16.0) 0.2 (0.0-0.6) na na Namibia 2006/07 23.7 (21.8-25.5) 20.9 (19.2-22.7) 0.9 (0.6-1.2) 1.8 (1.3-2.4)

 Nigeria 2008 11.5 (10.7-12.3) 8.9 (8.2-9.6) 0.7 (0.5-0.9) 3.2 (2.7-3.6) Rwanda 2005 19.4 (18.0-20.8) 13.9 (12.6-15.1) 3.4 (2.8-4.1) na na

 Sierra Leone 2008 37.4 (35.1-39.7) 36.7 (34.5-38.9) 0.4 (0.1-0.7) 1.3 (0.8-1.9)

 Swaziland 2006/07 16.7 (15.2-18.1) 13.8 (12.5-15.2) 1.4 (0.9-1.9) 2.8 (2.3-3.4) Tanzania 2004/05 22.0 (19.8-24.3) 21.0 (18.8-23.3) 0.4 (0.1-0.6) na na Uganda 2006 21.7 (19.4-24.0) 18.1 (15.9-20.2) 1.8 (1.1-2.6) 3.9 (3.1-4.8) Zambia 2007 23.6 (22.0-25.1) 23.2 (21.7-24.7) 1.2 (0.8-1.6) 0.2 (0.1-0.4) Zimbabwe 2005/06 22.8 (21.5-24.1) 21.3 (20.0-22.6) 3.0 (2.5-3.5) 1.9 (1.6-2.3)

North Africa/West Asia/Europe  Albania 2008/09 42.5 (40.4-44.6) 42.5 (40.4-44.6) 2.1 (1.2-2.9) na na

Armenia 2005 60.6 (56.9-64.4) 60.6 (56.8-64.4) 0.9 (0.0-2.1) 1.8 (0.9-2.8)

 Azerbaijan 2006 49.1 (46.5-51.7) 49.0 (46.4-51.6) 0.5 (0.1-0.9) 0.3 (0.1-0.5)

 Egypt 2008 42.6 (40.7-44.5) 37.6 (35.7-39.4) 8.4 (7.4-9.4) 0.2 (0.1-0.4) Moldova 2005 52.3 (49.7-55.0) 52.3 (49.7-55.0) 0.1 (0.0-0.2) 0.1 (0.0-0.3) Ukraine 2007 52.2 (49.3-55.2) 51.6 (48.6-54.6) 3.6 (2.8-4.4) 0.3 (0.1-0.4)

Continued...

Table 6a—Continued

20 
Region and Country Year of 

survey

Percent 

using 

any 

tobacco (95% CI)

Percent using manufactured 

cigarettes (95% CI) 

Percent 

using 

other 

smoked 

tobacco (95% CI)

Percent 

using 

smokeless 

tobacco (95% CI)

Central Asia  Uzbekistan1 2002 51.2 (48.0-54.4) 23.8 (21.4-26.2) na na 31.8 (28.5-35.0)

South and Southeast Asia  Bangladesh† 2007 69.3 (67.2-71.5) 60.1 (57.8-62.4) 0.0 (--) 19.8 (17.6-21.9)

 India2 2005/06 57.0 (56.3-57.7) 32.7 (32.0-33.4) 0.6 (0.5-0.8) 36.9 (36.1-37.7)

 Maldives3 2009 53.0 (49.2-56.9) 49.1 (45.5-52.8) 0.3 (0.0-0.6) 6.0 (4.6-7.4)

 Nepal 2006 53.4 (51.2-55.6) 30.2 (27.4-33.0) 1.4 (0.8-2.0) 36.2 (34.3-38.2)

 Timor-Leste 2009/10 69.5 (67.7-71.3) 65.7 (63.9-67.6) 23.2 (21.5-24.9) 2.5 (1.8-3.1)

Latin America/Caribbean  Bolivia 2008 na na 40.9 (39.0-42.8) na na na na Dominican Republic 2007 11.7 (10.9-12.4) 10.2 (9.5-10.8) 0.1 (0.0-0.1) 1.9 (1.6-2.2)

(--) indicates that no respondents used that form of tobacco and therefore confidence intervals are not estimated.na: Not available 1 The Uzbekistan survey only assessed current smoking status if respondents ever smoked at least 100 cigarettes in their entire life.2 The Bangladesh and India surveys asked about smoking cigarettes or bidis.3 The response rate for the men's survey in the 2009 Maldives DHS was inordinately low (interviews were completed with only 54 percent of the men who were 

eligible for interview). 

21 
Table 6b. Percentage of women age 15-49 who currently smoke cigarettes or use other tobacco products by country and region, 

1999-2010 Region and Country 

Year of survey 

Percent 

using 

any 

tobacco (95% CI) 

Percent using manufactured 

cigarettes (95% CI) 

Percent 

using 

other 

smoked 

tobacco (95% CI) 

Percent 

using 

smokeless 

tobacco (95% CI) 

Sub-Saharan Africa  Benin 2006 2.3 (1.9-2.7) 0.1 (0.0-0.1) 0.1 (0.1-0.2) na na

 Burkina Faso 2003 5.7 (5.0-6.4) 0.1 (0.0-0.1) 0.0 (0.0-0.0) na na 

 Cameroon 2004 1.9 (1.6-2.2) 0.7 (0.6-0.9) 0.1 (0.0-0.1) na na

 Congo Democratic Republic 2007 3.0 (1.9-4.0) 0.6 (0.3-0.9) 0.2 (0.1-0.3) 2.2 (1.3-3.2)  Ethiopia 2005 1.4 (0.9-1.9) 0.2 (0.1-0.3) 0.7 (0.4-1.1) 0.6 (0.3-1.0) Ghana 2008 0.3 (0.2-0.5) 0.2 (0.0-0.3) 0.0 (--) 0.2 (0.1-0.3) Guinea 2005 1.4 (1.0-1.8) 0.8 (0.4-1.1) 0.0 (--) na na 

 Kenya 2008/09 1.6 (0.9-2.3) 0.3 (0.2-0.4) 0.0 (0.0-0.1) 1.3 (0.6-2.0)

 Lesotho 2009 9.4 (8.7-10.2) 0.2 (0.1-0.3) 0.0 (0.0-0.0) 9.1 (8.4-9.9)  Liberia 2007 3.1 (2.5-3.8) 1.0 (0.7-1.3) 0.0 (0.0-0.0) 2.4 (1.8-3.0)

 Madagascar 2008/09 21.0 (19.6-22.4) 1.5 (1.2-1.9) 0.1 (0.0-0.2) 19.6 (18.2-21.1)

 Malawi 2004 1.8 (1.5-2.1) 0.3 (0.2-0.4) 0.0 (0.0-0.0) 1.3 (1.0-1.5)

 Mali 2006 2.3 (1.5-3.1) 0.1 (0.0-0.2) 0.1 (0.0-0.1) na na 

 Mozambique 2003 7.1 (6.3-8.0) 1.6 (1.1-2.1) 0.0 (--) na na

 Namibia 2006/07 8.2 (7.3-9.1) 5.3 (4.5-6.1) 0.5 (0.4-0.7) 2.3 (2.0-2.7) 

 Niger 2006 2.5 (1.7-3.2) 0.1 (0.0-0.2) 0.0 (0.0-0.1) na na

 Nigeria 2008 0.7 (0.5-0.8) 0.2 (0.1-0.2) 0.1 (0.0-0.1) 0.5 (0.3-0.6)

 Rwanda 2005 4.6 (4.1-5.1) 0.3 (0.2-0.4) 2.5 (2.2-2.8) na na 

 Senegal 2005 0.5 (0.3-0.7) 0.4 (0.2-0.6) 0.0 (0.0-0.1) na na

 Sierra Leone 2008 10.4 (9.4-11.3) 6.0 (5.4-6.7) 0.2 (0.1-0.4) 4.7 (4.0-5.5) 

 Swaziland 2006/07 2.1 (1.7-2.6) 1.1 (0.8-1.4) 0.1 (0.0-0.1) 1.0 (0.7-1.3)

 Tanzania 2004/05 1.5 (1.1-1.8) 0.5 (0.3-0.7) 0.1 (0.0-0.1) na na 

 Uganda 2006 3.8 (3.2-4.4) 0.9 (0.6-1.2) 0.6 (0.4-0.7) 2.6 (2.1-3.2)

 Zambia 2007 1.7 (1.3-2.2) 0.7 (0.5-1.0) 0.1 (0.0-0.2) 1.2 (0.8-1.6) 

 Zimbabwe 2005/06 0.9 (0.7-1.2) 0.4 (0.2-0.6) 0.2 (0.0-0.3) 0.5 (0.4-0.7)

Continued... 

Table 6b—Continued

22 
Region and Country 

Year of survey

Percent 

using 

any 

tobacco (95% CI)

Percent using manufactured 

cigarettes (95% CI) 

Percent 

using 

other 

smoked 

tobacco (95% CI)

Percent 

using 

smokeless 

tobacco (95% CI)

North Africa/West Asia/Europe  Albania 2008/09 4.2 (3.0-5.3) 4.2 (3.0-5.3) 0.0 (0.0-0.0) na na

Armenia 2005 1.7 (1.2-2.1) 1.7 (1.2-2.1) 0.0 (--) 0.0 (0.0-0.0)

 Egypt 2008 0.7 (0.5-0.9) 0.6 (0.3-0.8) 0.2 (0.1-0.3) 0.0 (0.0-0.0)

 Jordan 2009 12.0 (10.7-13.2) 8.7 (7.7-9.7) 5.5 (4.6-6.3) na na

 Moldova 2005 7.2 (6.4-7.9) 7.1 (6.4-7.9) 0.0 (0.0-0.0) 0.0 (0.0-0.1)

 Turkey 2003 na na 27.7 (26.2-29.2) na na na na

 Ukraine 2007 15.3 (13.9-16.7) 15.0 (13.7-16.4) 2.9 (2.1-3.6) 0.0 (--)Central Asia  Kazakhstan 1999 8.6 (7.7-9.5) 8.5 (7.6-9.4) 0.0 (0.0-0.0) na na

 Uzbekistan1 2002 1.1 (0.8-1.4) 0.9 (0.6-1.2) na na 0.2 (0.1-0.4)

South and Southeast Asia  Cambodia 2005 10.8 (9.7-11.9) 3.6 (3.0-4.3) 0.1 (0.1-0.2) 7.5 (6.8-8.3) India2 2005/06 10.8 (10.4-11.3) 1.4 (1.2-1.5) 0.2 (0.1-0.2) 9.0 (8.6-9.4) Indonesia 2007 3.0 (2.5-3.4) 2.6 (2.2-3.1) 0.0 (0.0-0.0) na na

 Maldives 2009 8.8 (7.8-9.8) 2.3 (1.7-2.8) 2.6 (2.1-3.0) 4.2 (3.5-5.0)

 Nepal 2006 19.6 (18.0-21.2) 15.2 (13.9-16.6) 2.0 (0.9-3.1) 5.0 (4.1-5.8) Philippines 2008 5.5 (4.9-6.0) 5.1 (4.5-5.6) 1.9 (1.5-2.2) 0.3 (0.2-0.4)

 Timor-Leste 2009/10 4.7 (4.2-5.2) 2.9 (2.5-3.3) 1.4 (1.2-1.7) 1.9 (1.7-2.2)

Latin America/Caribbean  Bolivia 2008 na na 8.7 (8.0-9.3) na na na na

 Dominican Republic 2007 6.7 (6.2-7.1) 6.3 (5.9-6.8) 0.1 (0.0-0.1) 0.3 (0.2-0.4)

 Haiti 2005/06 5.6 (4.8-6.4) 3.2 (2.8-3.7) 0.8 (0.6-1.1) 2.5 (2.0-3.1)

 Honduras 2005/06 na na 2.3 (2.0-2.6) na na na na

 Nicaragua 2001 5.3 (4.7-5.8) 5.2 (4.7-5.8) 0.0 (0.0-0.0) na na

 Peru 2007/08 na na 6.9 (6.1-7.6) na na na na

(--) indicates that no respondents used that form of tobacco and therefore confidence intervals are not estimated.

na: Not available 1 The Uzbekistan survey only assessed current smoking status if respondents ever smoked at least 100 cigarettes in their entire life.2 The India survey asked about smoking cigarettes or bidis.

23
24 

Figure 1. Percentage of men age 15-49 who currently use any type of tobacco 

7

11

12

12

16

17

19

19

21

22

22

23

24

24

24

34

37

43

43

47

49

51

52

52

53

53

57

61

69

69

0 10 20 30 40 50 60 70 80

 Ghana 2008

 Ethiopia 2005

 Nigeria 2008

 Dominican Republic 2007

 Liberia 2007

 Swaziland 2006/07

 Kenya 2008/09

 Rwanda 2005

 Malawi 2004

 Uganda 2006

 Tanzania 2004/05

 Zimbabwe 2005/06

 Zambia 2007

 Namibia 2006/07

 Mozambique 2003

 Lesotho 2009

 Sierra Leone 2008

 Albania 2008/09

 Egypt 2008

 Madagascar 2008/09

 Azerbaijan 2006

 Uzbekistan 2002

 Ukraine 2007

 Moldova 2005

 Maldives 2009

 Nepal 2006

 India 2005/06

 Armenia 2005

 Bangladesh 2007

 Timor-Leste 2009/10

Percentage of men
25 

Type of tobacco used by men 

In all countries except Uzbekistan, India, and Nepal, manufactured cigarettes were the most 

common type of tobacco used by men. In sub-Saharan Africa, Madagascar stands out with very high 

prevalence of smokeless tobacco use among men; 23 percent reported using smokeless tobacco, while 28 

percent reported using manufactured cigarettes. In Central Asia, men in Uzbekistan were more likely to 

report using smokeless tobacco (i.e., nas) than manufactured cigarettes (32 percent vs. 24 percent). In 

South and Southeast Asia, the prevalence of smokeless tobacco use among men was higher than the 

prevalence of manufactured cigarette use in India (37 percent vs. 33 percent) and in Nepal (36 percent vs. 

30 percent). Timor-Leste not only has the highest prevalence of manufactured cigarette use for men (66 

percent), but it also has a substantial prevalence of smoking other types of tobacco (23 percent). A large 

majority of men who smoke other types of tobacco in Timor-Leste also smoke manufactured cigarettes 

Prevalence of any tobacco use among women 

As was the case for men, tobacco use among women age 15-49 was quite variable across the 

countries examined (Table 6b). These results are also displayed in Figure 2. In sub-Saharan Africa, less 

than 1 percent of women reported using any form of tobacco in Ghana, Nigeria, Senegal, and Zimbabwe. 

The countries in sub-Saharan Africa with the highest prevalence of tobacco use for women were also 

those with the highest prevalence of tobacco use for men. The prevalence of tobacco use for women in 

these countries was 21 percent in Madagascar, 10 percent in Sierra Leone, and 9 percent in Lesotho. 

In contrast to the results for men in North Africa/West Asia/Europe, where a consistently high 

proportion of men reported using tobacco, the prevalence of tobacco use among women in the region is 

highly variable. The countries where women were least likely to report using tobacco are Egypt (less than 

1 percent) and Armenia (2 percent). Women were most likely to use tobacco in Ukraine (15 percent) and 

Jordan (12 percent). Since the Turkey DHS only assessed the use of manufactured cigarettes, we did not 

estimate the use of ‘any tobacco’ for women in this country. However, the highest prevalence of tobacco 

use for women in this report was found in Turkey, where slightly over one in four (28 percent) evermarried women reported using manufactured cigarettes. 

The prevalence of tobacco use among women also varied across the countries in Central Asia and 

in South and Southeast Asia. In Central Asia, 1 percent of women used some form of tobacco in 

Uzbekistan, while 9 percent of women used tobacco in Kazakhstan. In South and Southeast Asia, tobacco 

use among women varied from a low of 3 percent in Indonesia to a high of 20 percent in Nepal. 

Finally, the prevalence of tobacco use was relatively low among women in the countries of Latin 

America and the Caribbean, with less than 9 percent of women in all countries in the region reporting any 

type of tobacco use. 

Type of tobacco used by women 

In contrast to the results for men, where the most common type of tobacco used in almost all 

countries was manufactured cigarettes, the pattern of tobacco use for women varies by country and by 

region. In sub-Saharan Africa, where the use of manufactured cigarettes was low for women in most of 

the countries, the prevalence of smokeless tobacco use was often either comparable to or higher than the 

prevalence of manufactured cigarette use. In Lesotho and Madagascar, more than 90 percent of women 

who used any form of tobacco used smokeless tobacco. 
26 

Figure 2. Percentage of women age 15-49 who currently use any type of tobacco

4

4

5

5

5

5

6

6

7

7

7

8

9

9

9

10

11

11

12

15

20

21

0 5 10 15 20 25

 Uganda 2006

 Albania 2008/09

 Rwanda 2005

 Timor-Leste 2009/10

 Nicaragua 2001

 Philippines 2008

 Haiti 2005/06

 Burkina Faso 2003

 Dominican Republic 2007

 Mozambique 2003

 Moldova 2005

 Namibia 2006/07

 Kazakhstan 1999

 Maldives 2009

 Lesotho 2009

 Sierra Leone 2008

 Cambodia 2005

 India 2005/06

 Jordan 2009

 Ukraine 2007

 Nepal 2006

 Madagascar 2008/09

Percentage of women

Less than 4 percent of women in the 

remaining 21 countries currently use any 

type of tobacco
27 

In North Africa/West Asia/Europe and in Central Asia, women were generally more likely to 

report using manufactured cigarettes than any other type of tobacco. The pattern of tobacco use among 

women in South and Southeast Asia varies by country. Whereas women in Cambodia, India, and the 

Maldives were most likely to report using smokeless tobacco, women in Nepal and the Philippines were 

most likely to report using manufactured cigarettes. Women in Timor-Leste were only slightly more 

likely to report using manufactured cigarettes than any other form of tobacco. No data were available to 

assess smokeless tobacco use in Indonesia. 

Finally, only two countries examined in Latin America and the Caribbean for women had data on 

all forms of tobacco use (the Dominican Republic and Haiti). In the Dominican Republic, tobacco use 

almost exclusively reflected the use of manufactured cigarettes. In Haiti, however, the prevalence of 

manufactured cigarette use was about the same as the prevalence of smokeless tobacco use (3 percent). 

Gender differences in the prevalence of any tobacco use 

In all countries in which tobacco use was assessed for both men and women, men were more 

likely than women to report currently using at least one form of tobacco. The magnitude of the gender 

differences in tobacco use was highly variable across regions and across countries within regions. The 

smallest gender differences in tobacco use are found in the Dominican Republic and Madagascar, where 

men age 15-49 were roughly twice as likely as women age 15-49 to report currently using at least one 

form of tobacco. The largest gender differences in tobacco use are found in Armenia, Uzbekistan, and 

Egypt. The largest gender difference in tobacco use was found in Egypt, where men were 61 times more 

likely than women to report currently using tobacco (42.6 percent vs. 0.7 percent). In Uzbekistan, men 

were 47 times more likely than women to report currently using tobacco (51.2 percent vs. 1.1 percent). In 

Armenia, men age 15-49 were 36 times more likely than women age 15-49 to report currently using at 

least one form of tobacco (60.6 percent vs. 1.7 percent). 

3.2 Prevalence of Manufactured Cigarette Smoking 

Manufactured cigarettes are the most prevalent type of tobacco used worldwide. Cigarettes 

represent roughly 80 percent of total global tobacco consumption (Food and Agriculture Organization of 

the United Nations 2003) and account for 92 percent of total tobacco sales (Eriksen, Mackay and Ross 

2012). As such, cigarette smoking is responsible for a substantial burden of death and disability among 

tobacco users. 

Prevalence of manufactured cigarette smoking among men 

The results of this analysis show wide variation in the use of manufactured cigarettes among men 

age 15-49 in the countries examined. These results are presented in Table 6a and Figure 3. With a few 

exceptions, the countries in sub-Saharan Africa generally had lower prevalence of cigarette smoking for 

men than the countries located in other regions. In fact, the countries in this report with the lowest 

prevalence of cigarette smoking for men are found in sub-Saharan Africa—Ghana (6 percent), Ethiopia (8 

percent), and Nigeria (9 percent). Out of 17 countries in sub-Saharan Africa with data on current cigarette 

use for men, 10 had a prevalence of less 20 percent. The countries in sub-Saharan Africa with the highest 

prevalence of manufactured cigarette use for men are Sierra Leone (37 percent), Lesotho (34 percent), 

and Madagascar (28 percent). 

The prevalence of manufactured cigarette smoking among men in North Africa/West 

Asia/Europe was generally high across all of the countries examined, exceeding one-third of the 

population in these countries. In Armenia, Azerbaijan, Moldova, and Ukraine, 49-61 percent of men age 

15-49 reported currently smoking cigarettes. 
28 

Figure 3. Percentage of men age 15-49 who currently smoke manufactured cigarettes 

6

8

9

10

14

14

14

15

16

18

18

21

21

21

23

24

28

30

33

34

37

38

41

43

49

49

52

52

60

61

66

0 10 20 30 40 50 60 70 80

 Ghana 2008

 Ethiopia 2005

 Nigeria 2008

 Dominican Republic 2007

 Swaziland 2006/07

 Rwanda 2005

 Mozambique 2003

 Liberia 2007

 Malawi 2004

 Kenya 2008/09

 Uganda 2006

 Namibia 2006/07

 Tanzania 2004/05

 Zimbabwe 2005/06

 Zambia 2007

 Uzbekistan 2002

 Madagascar 2008/09

 Nepal 2006

 India 2005/06

 Lesotho 2009

 Sierra Leone 2008

 Egypt 2008

 Bolivia 2008

 Albania 2008/09

 Azerbaijan 2006

 Maldives 2009

 Ukraine 2007

 Moldova 2005

 Bangladesh 2007

 Armenia 2005

 Timor-Leste 2009/10

Percentage of men
29 

In the one country examined in Central Asia (Uzbekistan), roughly one in four men (24 percent) 

age 15-49 reported currently smoking cigarettes. As was previously noted in the methods section, it is 

possible that this is a slight underestimate as only those respondents in the Uzbekistan DHS who reported 

smoking at least 100 cigarettes in their lifetime were asked whether they currently smoked cigarettes. 

In the five countries examined in South and Southeast Asia, the prevalence of current cigarette 

use among men was high, ranging from nearly one-third of men in India and Nepal to 60 percent of men 

in Bangladesh and 66 percent of men in Timor-Leste. As noted in the methods section, the estimates for 

Bangladesh and India include the use of manufactured cigarettes as well as bidis (hand-rolled tobacco in a 

leaf wrapper). In all other countries, bidis are coded in the ‘other smoked tobacco’ category. Also, the 

surveys conducted in Bangladesh and the Maldives only included ever-married men, which likely 

increased the estimates of cigarette use compared to what it would have been if never-married men had 

been included in the sample. 

Finally, in the two countries examined in Latin America and the Caribbean, the prevalence of 

smoking among men varied widely. In the Dominican Republic, the prevalence of current cigarette use 

among men was at the lower end of the spectrum (10 percent), whereas in Bolivia, current cigarette use 

among men was much higher (41 percent). 

Prevalence of manufactured cigarette smoking among women 

The prevalence of manufactured cigarette smoking among women age 15-49 was low in the 

majority of the countries examined (Table 6b). In fact, in all but 3 of the 47 countries, the prevalence of 

current cigarette smoking among women was less than 9 percent. The three countries with the highest 

prevalence of cigarette smoking for women were Turkey (28 percent), Nepal (15 percent), and Ukraine 

(15 percent). The results are also presented in Figure 4. 

In sub-Saharan Africa, the prevalence of current cigarette smoking among women was 

universally low. In 19 out of the 25 countries examined, less than 1 percent of women in the population 

reported currently smoking manufactured cigarettes. The two outliers in this region are Sierra Leone and 

Namibia, where 6 percent and 5 percent of women, respectively, reported currently smoking 

manufactured cigarettes. 

In contrast to the low prevalence of cigarette smoking among women in sub-Saharan Africa, the 

prevalence of cigarette smoking among women in countries in North Africa/West Asia/Europe was highly 

variable. The countries in this region with very low prevalence of smoking were Egypt (0.6 percent) and 

Armenia (2 percent). The countries with the highest prevalence of smoking among women in this region 

were Turkey (28 percent) and Ukraine (15 percent). As previously noted, of all of the countries examined 

in this report, these two countries were among those with the highest prevalence of smoking for women. 

Moreover, of all of the countries examined in this report, not only did Turkey have the highest prevalence 

of cigarette smoking among women, this estimate also represents the highest prevalence of any tobacco 

use for women in this report. It should be noted that the higher prevalence of cigarette smoking among 

women in Turkey may, to some extent, be due to the fact that only ever-married women were interviewed. 

The prevalence of smoking for women varied in the two countries examined in Central Asia. In 

Kazakhstan, 8 percent of women reported smoking cigarettes, whereas in Uzbekistan, less than 1 percent 

of women reported smoking. Again, it is possible that the estimate for Uzbekistan may be a slight 

underestimate as only those respondents who reported smoking at least 100 cigarettes in their lifetime 

were asked about their current cigarette use. 
30 

Figure 4. Percentage of women age 15-49 who currently smoke manufactured cigarettes

2

2

2

2

2

3

3

3

4

4

5

5

5

6

6

7

7

8

9

9

15

15

28

0 5 10 15 20 25 30

 Madagascar 2008/09

 Mozambique 2003

 Armenia 2005

 Maldives 2009

 Honduras 2005/06

 Indonesia 2007

 Timor-Leste 2009/10

 Haiti 2005/06

 Cambodia 2005

 Albania 2008/09

 Philippines 2008

 Nicaragua 2001

 Namibia 2006/07

 Sierra Leone 2008

 Dominican Republic 2007

 Peru 2007/08

 Moldova 2005

 Kazakhstan 1999

 Bolivia 2008

 Jordan 2009

 Ukraine 2007

 Nepal 2006

 Turkey 2003

Percentage of women

Less than 2 percent of women in the 

remaining 24 countries currently smoke 

manufactured cigarettes
31 

In South and Southeast Asia, cigarette smoking among women was relatively low, at 5 percent or 

less in all but one country. The prevalence of smoking among the low prevalence countries in this region 

ranged from 1 percent in India to 5 percent in the Philippines. The outlier in this region is Nepal, where 

15 percent of women age 15-49 in the population reported smoking cigarettes. 

Finally, there was relatively little variability in the prevalence of smoking among women in Latin 

America and the Caribbean. Prevalence estimates for women in this region were low, ranging from 2 

percent in Honduras to 9 percent in Bolivia. 

Gender differences in the prevalence of manufactured cigarette smoking 

In all countries in which manufactured cigarette use was assessed for both men and women, men 

were more likely than women to report being current cigarette smokers. The size of the gender differences 

in manufactured cigarette use is substantial in the majority of the countries examined. In 21 out of the 29 

countries in which data were collected from both genders, men age 15-49 were at least 10 times as likely 

as women age 15-49 to report being current cigarette smokers. The smallest gender differences in 

smoking status are found in the Dominican Republic and Nepal, where men were 1.6 and 2.0 times as 

likely as women to report being current smokers. Some of the largest gender differences in the prevalence 

of cigarette smoking are found in sub-Saharan Africa (e.g., Kenya, Lesotho, Malawi, and Zimbabwe) and 

North Africa (Egypt), where men were at least 50 times as likely as women to report being current 

smokers. 

3.3 Prevalence of the Use of Other Smoked Tobacco 

Other types of smoked tobacco, other than manufactured cigarettes, can include pipes, cigars, 

hand-rolled cigarettes (i.e., “roll-your-own” or RYO), bidis, kreteks, and water pipes (e.g., qalyan, shisha, 

nargila, hookah). 

Prevalence of the use of other smoked tobacco among men 

The use of other forms of smoked tobacco among men age 15-49 was relatively low (less than 5 

percent) across the majority of the countries examined. The three countries in which more than 5 percent 

of men currently used some other type of smoked tobacco are Lesotho (6 percent), Egypt (8 percent), and 

Timor-Leste (23 percent). In Lesotho, other smoked tobacco exclusively reflected the use of pipes. In 

Egypt, the vast majority of those who smoked some other form of tobacco reported using the water pipe. 

In Timor-Leste, nearly one in four men reported using some other type of smoked tobacco, almost all of 

which was rolled tobacco. 

Prevalence of the use of other smoked tobacco among women 

The use of other forms of smoked tobacco among women age 15-49 was very low across the vast 

majority of the countries examined. In 35 out of the 42 countries with available data, less than 1 percent 

of women reported currently using some other form of smoked tobacco. The country with the highest 

proportion of women reporting the use of other smoked tobacco is Jordan, where 5 percent of women 

reported using nargila (the water pipe/hookah). 

Gender differences in the use of other smoked tobacco 

In the majority of the countries in which the use of other smoked tobacco was assessed for both 

men and women, men were more likely than women to report being a current user. The gender 

differential in Timor-Leste stands out, with nearly one-quarter of men reporting the use of other smoked 

tobacco compared with only 1 percent of women. 
32 

3.4 Prevalence of the Use of Smokeless Tobacco 

Smokeless tobacco includes chewing tobacco and snuff. Information on the use of smokeless 

tobacco was not available in a number of countries for both women and men. 

Prevalence of the use of smokeless tobacco among men 

The use of smokeless tobacco among men was low in the majority of the countries with available 

data. In 20 out of the 26 countries that measured smokeless tobacco use among men, fewer than 5 percent 

of men age 15-49 reported using either snuff or chewing tobacco. In general, the use of smokeless 

tobacco among men was more common in countries in South and Southeast Asia than in countries in any 

other region. In Bangladesh, almost 20 percent of men reported using smokeless tobacco, while in India 

and Nepal, over one-third of men reported using smokeless tobacco. The two other countries with a high 

prevalence of smokeless tobacco use among men are Madagascar in sub-Saharan Africa (23 percent) and 

Uzbekistan in Central Asia (32 percent). The predominant form of smokeless tobacco used in all of these 

high prevalence countries is chewing tobacco. In Bangladesh, no respondent reported the use of snuff, 

whereas in India and Nepal, less than 1 percent of men reported using snuff. In Madagascar, 4 percent of 

men reported using snuff whereas, 19 percent reported using chewing tobacco. 

Prevalence of the use of smokeless tobacco among women 

As was the case for men, the use of smokeless tobacco among women was low in the majority of 

the countries examined. In 11 out of the 28 countries with available data, less than 1 percent of women 

age 15-49 reported using smokeless tobacco. The countries with the highest prevalence of smokeless 

tobacco use among women are in South and Southeast Asia and sub-Saharan Africa, including 

Madagascar (20 percent), Lesotho (9 percent), India (9 percent), Cambodia (8 percent), Sierra Leone (5 

percent), Nepal (5 percent), and the Maldives (4 percent). As suggested by these numbers, Madagascar 

has the highest proportion of women who reported using smokeless tobacco. Among these higher 

prevalence countries, chewing tobacco is the main type of smokeless tobacco used by women in the 

Maldives, Nepal, Cambodia, India, and Madagascar. Snuff is the main type of smokeless tobacco used by 

women in Lesotho and Sierra Leone. 

Gender differences in the use of smokeless tobacco 

For countries with data available for women and men, while men are more likely than women to 

report currently using at least one form of smokeless tobacco in a large number of these countries, there 

are several countries in which women were either more likely than men to report using smokeless tobacco 

or were as likely as men to report using this form of tobacco. For example, two countries with a higher 

prevalence of smokeless tobacco use among women than among men are Lesotho (9 percent vs. 1 

percent) and Sierra Leone (5 percent vs. 1 percent). Madagascar stands out as a country with about 

equally high prevalence of smokeless tobacco use among women and men (20 percent vs. 23 percent). 

3.5 Differentials in Manufactured Cigarette Use by Sociodemographic 

Characteristics 

Within countries, smoking and tobacco use is not equally distributed in the population, but varies 

by demographic and socioeconomic characteristics (Hosseinpoor, Parker et al. 2011). For policy 

purposes, it is important to examine the profile of tobacco users to identify groups with higher prevalence 

of tobacco use. This section describes the sociodemographic patterns of cigarette smoking across the 

countries for women and men. Specifically, it examines differentials in the proportion of women and men 

age 15-49 who report currently using manufactured cigarettes by selected sociodemographic 

characteristics. The analysis focuses on cigarette smoking specifically since it is the predominant type of 
33 

tobacco used worldwide and is thus responsible for a significant burden of death and disability among 

tobacco users. To ensure adequate sample sizes when estimating the prevalence of cigarette smoking 

within sociodemographic groups, the analysis was restricted to those countries with at least a 10 percent 

prevalence of current cigarette smoking for men (Appendix Table A1). For women, since relatively few 

countries had a prevalence of cigarette smoking of more than 10 percent, the analysis was restricted to 

those countries with at least a 5 percent prevalence of current cigarette smoking (Appendix Table A2). 

Pearson chi-square tests were conducted to test the associations between smoking status and the 

characteristics examined; the resulting p-values from the chi-square tests are presented in the tables. All 

analyses were weighted and the standard errors were adjusted for the clustered and stratified sampling 

design. 

Age 

Understanding the pattern of tobacco use across age groups or cohorts within countries is 

important in developing effective policies and programs aimed at reducing and eliminating such use. The 

age at which tobacco use starts is of particular significance. Research using data from the World Health 

Organization’s (WHO) World Health Survey found that the distribution of smoking across age groups 

varies across countries (Hosseinpoor, Parker et al. 2011). In middle-income countries, the prevalence of 

smoking any type of tobacco generally increases with age between the ages of 18 and 50, after which it 

decreases. This pattern was found for both women and men in middle-income countries. However, in 

low-income countries, while the same general pattern was found for men, the prevalence of smoking for 

women continued to increase with each age group. 

Higher prevalence of tobacco use among certain age groups may reflect differences in cultural 

norms or practices related to tobacco within a country. It may also reflect differences in knowledge about 

the health effects of smoking or differences in the marketing and availability of tobacco within countries. 

Age differences in tobacco use may also reflect the influence of other factors such as socioeconomic 

status, education, occupational status, or area of residence. This analysis explores the prevalence of 

cigarette smoking across age groups for women and men within the countries. 

Men

For men, there is a statistically significant relationship between age group and the likelihood of 

being a current cigarette smoker in all 28 countries that were examined (see Appendix Table A2). The 

nature and the strength of these associations vary by country. In most countries, the likelihood of men 

being current smokers increases with age between the ages of 15 and 49. In some countries, there is a 

threshold increase between the youngest (15-24) and the second youngest (25-34) age groups. 

In every country except Bangladesh, there is an increase in the likelihood of smoking between the 

youngest (15-24) and the second youngest (25-34) age groups. In 16 out of the 28 countries, men age 

25-34 are at least twice as likely to smoke cigarettes as men age 15-24. 

For countries with available data, the prevalence of cigarette smoking is presented for those 50 

years of age and over. The age range of this group varies considerably across the countries and therefore 

caution should be used when interpreting the estimates for this age group (see Table 1 for the 

characteristics of the country samples). For example, in some countries, this age group only includes men 

50-54, whereas in other countries, this age group captures men age 50-64. In seven countries, men in the 

50+ age group are more likely to smoke cigarettes than men age 35-59. The prevalence of cigarette 

smoking is lower among men in the 50+ age group than among men age 35-49 in Lesotho, Madagascar, 

Sierra Leone, Uzbekistan, Zambia, Azerbaijan, Moldova, Uzbekistan, and the Maldives. 
34 

There are two countries in South and Southeast Asia where the relationship between age and 

smoking status differs from the trends described above. In Bangladesh, there is no clear trend in smoking 

prevalence by age group for men, with a high percentage of men smoking in all age groups (56-63 

percent). Bangladeshi men are most likely to smoke in the youngest (15-24) and second oldest (35-49) 

age groups. In the Maldives, the prevalence of smoking is high in the first three age groups, then 

decreases substantially among men age 50+. What these two countries have in common, which is 

different from the other countries in the table, is that the prevalence of smoking among the youngest age 

group of men (15-24) is relatively high. 

Cigarette smoking at young ages (15-24) is less prevalent in sub-Saharan Africa than in other 

regions. In 9 of the 14 countries in sub-Saharan Africa included in Appendix Table A1, less than 10 

percent of men age 15-24 are current smokers. In 11 of those 14 countries, the prevalence of cigarette 

smoking at age 15-24 is far less than half of the prevalence of cigarette smoking in the peak age group for 

smokers. On the contrary, half of the countries outside of sub-Saharan Africa have a prevalence of 

cigarette smoking at age 15-24 that is at least 50 percent as high as the prevalence in the peak smoking 

age group. In Bangladesh, prevalence is highest in the age 15-24 age group. Other countries with 

particularly high ratios of cigarette smoking at age 15-24 to cigarette smoking in the peak age group are 

the Maldives (with a ratio of 0.92), Madagascar (0.74), Bolivia and Moldova (0.67 each), Timor-Leste 

(0.61), and Ukraine (0.60). 

Women 

For women, there is a statistically significant relationship between age group and the likelihood 

of being a current cigarette smoker in 12 out of the 13 countries examined. Peru is the only country in 

which women were equally likely to smoke across the age groups. The nature of the relationship between 

age and smoking status varies by country. Consistent with the results for men, in the majority of the 

countries, the likelihood of being a current smoker for women increases with age. The magnitude of this 

relationship is particularly pronounced in Nepal, where women age 35-49 were more than 10 times as 

likely to smoke as women age 15-24 (34 percent vs. 3 percent). 

The countries that deviate from this trend are Moldova, Turkey, Ukraine, and Kazakhstan. First, 

the differentials in smoking status are relatively small across the age groups in all of these countries 

except Turkey. Second, while the exact age pattern of smoking varies across these four countries, the 

prevalence of smoking among the oldest age group of women 35-49 is at the lower end of the continuum 

(compared with the prevalence of smoking in the other age groups). In Moldova and Kazakhstan, women 

in the oldest age group (35-49) were least likely to smoke, while women in the middle age group (25-34) 

were most likely to smoke. In Turkey, women in the middle age group (25-34) were also most likely to 

smoke, whereas there was no difference in the likelihood of smoking between women in the oldest and 

youngest age groups. Finally, in Ukraine, women in the oldest age group were less likely to smoke than 

women in the two younger age groups. 

There are only two countries examined in which more than 10 percent of women age 15-24 

smoke cigarettes—Turkey (24 percent) and Ukraine (17 percent). Half of the 13 countries examined in 

Appendix Table A2 have a prevalence of cigarette smoking at age 15-24 that is more than half of the peak 

prevalence in any age group. In Peru, the highest prevalence of smoking is at age 15-24, although less 

than 8 percent of women smoke in every age group. There are only two countries in which more than 15 

percent of women smoke cigarettes in the peak smoking age group and in which the ratio of smokers at 

age 15-24 to smokers in the peak smoking age group exceeds 0.70—Ukraine (with a ratio of 0.97) and 

Turkey (with a ratio of 0.74). 
35 

Marital status 

Marital status is associated with a range of demographic, social, cultural, and economic factors 

that may influence patterns of tobacco use. For example, marriage may be associated with the assumption 

of different roles and responsibilities that might influence levels of stress, levels of social support and 

exposure to different social networks, norms related to acceptable behavior including the acceptability of 

tobacco use, or socioeconomic circumstances. Those who were formerly married (i.e., widowed, 

divorced, or separated), particularly women, may experience a downturn in their socioeconomic wellbeing or may experience other social stressors associated with their marital status that might influence the 

likelihood of using tobacco. It should also be pointed out that the age distribution of persons in different 

marital status groups is quite different. Persons who have never been married tend to be in the younger 

age groups and persons who are formerly married tend to be in the older age groups. Since cigarette 

smoking tends to increase with age in most countries, the age distribution needs to be taken into account 

when assessing the relationship between marital status and smoking. 

Research using data from the World Health Survey reported the highest prevalence of smoking 

among women and men who were formerly married (Hosseinpoor, Parker et al. 2011). In low-income 

countries, however, no significant association was found between marital status and smoking prevalence 

for women, after controlling for a range of sociodemographic characteristics. The pattern of smoking 

across the other marital status groups (i.e., never married and currently married/cohabiting) varied by 

region. 

This analysis explores the prevalence of cigarette smoking for women and men by their marital 

status (never married, currently married/cohabiting, and formerly married) across the countries. 

Men 

With the exception of Bangladesh, there is a statistically significant relationship between marital 

status and the likelihood of being a current cigarette smoker for men in all 28 countries examined. It 

should be noted that for Bangladesh, only ever-married men were interviewed and therefore a significant 

association between marital status and smoking status may have been found if never married men had 

been included in the sample. In almost every country, cigarette smoking was least prevalent among men 

who had never married, intermediate among those who were currently married, and most prevalent among 

those who were formerly married (widowed, divorced, or separated). For every country except 

Bangladesh, the prevalence of smoking is highest among men who were formerly married. In TimorLeste, the prevalence is similar for men who are currently married and men who are formerly married. 

Men who have never been married have the lowest prevalence of cigarette smoking in every country. 

The magnitude of the association between marital status and smoking status among men varies 

across the countries. The largest group relative differences in the prevalence of smoking for men are 

found in Mozambique, Tanzania, and Uganda, where formerly married men have over six times the 

likelihood of being current cigarette smokers as never married men. In addition to these countries, the 

largest relative differences in the prevalence of smoking between these two groups of men are evident in 

Liberia, Dominican Republic, Zambia, and Zimbabwe. 

Women 

For women, there is a statistically significant relationship between current marital status and the 

likelihood of being current cigarette smokers in all 13 countries examined. In all of the countries, the 

prevalence of smoking is highest among women who were formerly married. 
36 

The marital status group with the lowest prevalence of cigarette smoking for women varies by 

country. Women who have never been married were least likely to smoke in a number of countries 

(Namibia, Sierra Leone, Moldova, Nepal, the Philippines, the Dominican Republic, and Nicaragua). In 

contrast, currently married women were least likely to smoke in Ukraine, Kazakhstan, Bolivia, and Peru. 

In Jordan and Turkey, where only ever-married women were interviewed, currently married women were 

less likely to smoke than formerly married women. 

The difference in the prevalence of cigarette smoking across marital status groups for women 

varies substantially across the countries. The largest group differences are found in Sierra Leone, Nepal, 

and the Dominican Republic. The largest difference is found in Nepal, where formerly married women 

are 35 times as likely as never married women to smoke. 

Education 

Research conducted in both low and middle-income countries finds higher prevalence of smoking 

among women and men with lower levels of education (Hosseinpoor, Parker et al. 2011). Education may 

be associated with tobacco use through a number of mechanisms. Those with higher levels of education 

may have better access to information about health promoting behaviors and the negative health effects of 

tobacco use. They may also have better access to information about tobacco cessation programs and have 

more resources to use them. Education may also be a proxy for a number of other factors that may affect 

tobacco use, including socioeconomic status, occupational status, area of residence, or social networks. In 

addition, age is a confounding factor since as educational attainment increases in a society, those with 

higher levels of education tend to be younger. This analysis examines the association between level of 

education (no education, primary, secondary, higher) and the prevalence of cigarette smoking for women 

and men across the countries. 

Men 

In 23 out of the 28 countries examined, there is a statistically significant bivariate association 

between level of education and the likelihood of being a current cigarette smoker for men. The five 

countries in which education was not associated with smoking status are Kenya, Madagascar, Tanzania, 

Armenia, and Uzbekistan. 

In virtually all of the countries in which a significant association was found for men, there is a 

negative relationship between level of education and the likelihood of being a current cigarette smoker. 

That is, men with more education are less likely to smoke. There is no country in which a statistically 

significant positive association was found for men (i.e., where more educated men are more likely to 

smoke). 

In Mozambique and Namibia, the relationship between education and smoking status for men is 

difficult to interpret as there is no clear trend in one direction or another. 

The strength and the nature of the association between education and smoking status for men vary 

across the countries. Some countries show relatively small differences in the prevalence of cigarette 

smoking across education groups for men. For example, smaller differences are found in Timor-Leste, 

where men with no education are 1.2 times more likely to smoke than are men who have a ‘higher’ level 

of education (70.9 percent vs. 60.6 percent). A number of countries show large differences in smoking 

behavior across education groups. For example, in Malawi, men with no education are almost five times 

as likely to smoke cigarettes as men who have a ‘higher’ level of education (25.4 percent vs. 5.3 percent). 

Many countries also show a gradient relationship between level of education and smoking status 

for men (i.e., smoking prevalence decreases with each level of education), whereas other countries show 
37 

more of a threshold effect where a large decrease in the prevalence of smoking is observed at certain 

levels of education. An example of a country where a threshold association is found is Swaziland. In this 

country, men with no education have the highest prevalence of cigarette smoking (24 percent), whereas 

men in all other education categories have lower but similar prevalence of cigarette smoking (13-15 

percent). Some examples of countries that show a clear gradient in smoking prevalence across all 

education groups are Lesotho, Malawi, Zimbabwe, Bangladesh, India, and Nepal. In these countries, the 

prevalence of smoking among men decreases substantially with each additional level of education. 

Women 

In 11 out of the 13 countries examined, there is a statistically significant bivariate association 

between level of education and the likelihood of being a current cigarette smoker for women. In the two 

countries that were not significant (Ukraine and Kazakhstan) very few women in the population had less 

than secondary schooling and there was no difference of being a current cigarette smoker between those 

with secondary schooling and those with higher levels of education. 

The results for the remaining 11 countries show two distinct patterns of smoking behavior across 

education groups for women. In several of the countries (Sierra Leone, Nepal, the Philippines, and the 

Dominican Republic), there is a negative association between women’s educational attainment and the 

likelihood of being a current cigarette smoker. In contrast, there is a positive association between 

education and the likelihood of being a smoker for women in Turkey, Bolivia, Nicaragua, and Peru. 

Among the countries where a significant association was found between education and smoking 

status for women, the magnitude of the association varies substantially across the countries. Relatively 

large differences in smoking status across education groups are found in countries such as the Dominican 

Republic, Peru, and particularly Nepal. In Nepal, less than 1 percent of women age 15-49 with secondary 

schooling or higher currently smoke compared with 26 percent of women with no schooling. 

The bivariate results for women also show that the specific nature of the relationship between 

level of education and smoking prevalence varies across the countries. In some of the countries, this 

association is best described as a gradient. In other countries the relationship between education and 

smoking status is better described as a threshold effect. The countries that show more of a gradient for 

women include Sierra Leone, Turkey, the Philippines, the Dominican Republic, and Peru. Countries that 

show more of a threshold association include Namibia, Jordan, Nepal, and Bolivia. 

Urban versus rural areas 

The prevalence of smoking has been shown to vary across urban and rural areas within countries 

(Hosseinpoor, Parker et al. 2011). Results from the World Health Survey suggest that the particular 

pattern of these differences varies across countries (Hosseinpoor, Parker et al. 2011). The characteristics 

of urban areas that may influence tobacco use include factors such as better access to tobacco, targeted 

marketing, and greater social inequalities within cities and poor living conditions (World Health 

Organization 2012). On the other hand, the socioeconomic characteristics and cultural norms of rural 

areas may influence the prevalence of tobacco use. This analysis examines the prevalence of tobacco use 

among women and men in urban and rural areas within the countries. 

Men 

In 13 out of the 28 countries examined, there are significant differences in the prevalence of 

cigarette smoking between men in urban areas and rural areas. The countries in which a significant 

association was found are regionally diverse. In four of the countries in which a significant association 

was found for men, smoking was more prevalent in urban areas than rural areas (Madagascar, Namibia, 
38 

Rwanda, and Uzbekistan). In nine of the countries, smoking was more prevalent among men in rural areas 

than urban areas (Liberia, Sierra Leone, Zambia, Zimbabwe, Bangladesh, India, Timor-Leste, Bolivia, 

and the Dominican Republic). 

The magnitude of the difference in smoking prevalence among men in urban versus rural areas is 

also variable across the countries. The largest difference in smoking prevalence for men is found in Sierra 

Leone, where men in rural areas were twice as likely to smoke as men in urban areas (45.4 percent in 

rural areas vs. 22.6 percent in urban areas). 

Women 

In contrast to the results for men where only half of the countries showed significant urban-rural 

differences, in 12 out of the 13 countries examined, there are significant differences in the prevalence of 

cigarette smoking between women in urban areas and those in rural areas. In the Dominican Republic, 

there was only a marginally significant association between area of residence and smoking prevalence 

(p=0.05). In 10 of the countries in which a significant association was found, smoking was more prevalent 

among women in urban areas than among those in rural areas (Namibia, Jordan, Moldova, Turkey, 

Ukraine, Kazakhstan, the Philippines, Bolivia, Nicaragua, and Peru). The countries in which smoking was 

more prevalent among women in rural areas than among those in urban areas are Sierra Leone, Nepal, and 

the Dominican Republic (marginally). 

The magnitude of the difference in smoking prevalence among women in urban versus rural areas 

varies widely across the countries, although the differences are generally larger than those found for men. 

Relatively small differences in smoking prevalence are found in Sierra Leone (urban: 5.0 percent vs. 

rural: 6.6 percent), the Dominican Republic (urban: 6.1 percent vs. rural: 7.0 percent), and the Philippines 

(urban: 5.5 percent vs. rural: 4.5 percent). Large geographic differences in smoking prevalence are found 

in Turkey (urban: 32.8 percent vs. rural 15.0 percent) and Nepal (urban: 8.6 percent vs. rural: 16.5 

percent). 

Interestingly, in Bolivia, men were significantly more likely to smoke in rural areas than in urban 

areas, whereas women were more likely to smoke in urban areas than in rural areas. 

Employment and cash earnings (women only) 

Employment status may affect the prevalence of smoking among women by directly increasing 

the affordability of tobacco, or indirectly through women’s social networks and the norms and practices 

of women’s co-workers with respect to tobacco use. Other research finds higher prevalence of smoking 

among women who work for pay in middle-income countries, but no difference in smoking prevalence by 

employment status among women in low-income countries (Hosseinpoor, Parker et al. 2011). This 

analysis examines differences in the prevalence of cigarette smoking by women’s employment status in 

the last 12 months and by whether or not women earned cash for their work. 

In 10 of the 12 countries for which data were available on women’s employment status, there was 

a significant association between employment in the last 12 months and the likelihood that women 

smoked cigarettes. There was no significant association between employment status and smoking 

prevalence in Turkey. In Peru, this association was only marginally significant (p=0.06). In all 10 

countries in which a significant association was found, women who worked in the last 12 months were 

more likely to smoke cigarettes than those who did not work in the last 12 months. 

The largest difference in smoking prevalence between women who worked and those who did not 

work are found in Nepal, where women who worked in the last 12 months were five times as likely to 
39 

smoke cigarettes as women who did not work. In most other countries, there was less than a two-fold 

difference between women who worked in the last 12 months and those who did not. 

In over half of the countries, there was a significant association between cash earnings and the 

likelihood that women smoked. Among women who worked in the last 12 months, those who earned cash 

for their work were more likely to smoke than those who did not earn cash in Namibia, Sierra Leone, 

Moldova, Turkey, Kazakhstan, Bolivia, and Peru. There was no significant association between cash 

earnings and smoking prevalence among women in Ukraine, Nepal, the Philippines, and the Dominican 

Republic. In Nicaragua, there was only a marginally significant association (p=0.05). 

The magnitude of the differences in smoking prevalence between women who earned cash and 

those who did not is highly variable across the countries. A small, albeit significant, difference is found in 

Sierra Leone (No: 6.1 percent vs. Yes: 8.5 percent). Quite substantial differentials are found in Turkey, 

Peru, and Namibia. In Turkey, 38 percent of women who earned cash smoked cigarettes, compared with 

14 percent of those who worked but did not earn cash. In Peru, women who earned cash were more than 

four times as likely to smoke cigarettes as those who worked but did not earn cash (No: 1.9 percent vs. 

Yes: 8.7 percent). In Namibia, women who earned cash were seven times as likely to smoke cigarettes as 

those who did not (No: 1.2 percent vs. Yes: 8.5 percent). 

Occupation (men only) 

Research also has also found that in both low and middle-income countries, men who work for 

pay are more likely to smoke than men who do not (Hosseinpoor, Parker et al. 2011). The current analysis 

examines differentials in the prevalence of cigarette smoking by employment status and type of 

occupation for men age 15-49 across the countries. 

In all 25 countries in which data were available on men’s occupation, a significant bivariate 

association was found between smoking prevalence and type of occupation. In almost all of the countries, 

the prevalence of cigarette smoking was lowest among men who did not work at all in the past 12 months. 

Moreover, the differential in the prevalence of smoking between men who did not work and those who 

did is large in most of the countries. 

In most of the countries, men who work in professional/technical/managerial occupations have a 

lower prevalence of smoking than men who work in other types of occupations. Some countries in which 

this differential is particularly large are Malawi, Sierra Leone, and Nepal. In Nepal, for example, men 

who work in professional/technical/managerial occupations have roughly half the prevalence of smoking 

as men in any other occupation. A possible explanation for this association is that men who work in 

professional/technical/managerial occupations tend to be more highly educated and to have higher levels 

of household wealth, both factors associated with lower prevalence of smoking for men. 

The occupations with higher prevalence of cigarette smoking for men vary across the countries. It 

should be noted that the confidence intervals for some of the occupational sub-groups are large due to 

small sample sizes. Thus, caution should be used when singling out particular occupations as having the 

highest prevalence of smoking within the countries. 

Household wealth 

The results of a meta-analysis examining the association between smoking prevalence and 

income suggest an inverse relationship for both women and men across most regions of the world 

(Ciapponi, Bardach et al. 2011). The only region in which no significant relationship was found was the 

Eastern Mediterranean region, although the authors noted that insufficient data may have influenced these 

results. The study also found evidence of a gradient, whereby smoking prevalence decreased among 
40 

higher income groups. It also found that the association between income and smoking prevalence was 

stronger in higher income countries than in lower income countries. 

Another study focusing on an asset-based wealth index as a determinant of smoking also found 

that for adults, lower wealth was associated with a higher prevalence of smoking in most of the 13 low 

and middle-income countries included in their analysis (Palipudi, Gupta et al. 2012). For women 

however, this pattern was only observed for those in low income countries. In middle income countries, 

there was less evidence of an association between wealth and smoking, with some evidence possibly 

suggesting lower prevalence of smoking among lower wealth groups. 

The current analysis examines differences in the prevalence of cigarette smoking across 

household wealth quintiles for women and men across the countries. 

Men 

In 19 out of the 27 countries with data on household wealth, a significant bivariate association 

was found between household wealth and smoking prevalence for men. No significant association was 

found for men in Kenya, Mozambique, Rwanda, Swaziland, Albania, Armenia, and the Maldives. In 

Timor-Leste, the association was only marginally significant (p=0.08). 

In almost all of the 19 countries in which a significant association was found between men’s 

smoking status and household wealth, the association was generally negative in direction. That is, the 

prevalence of smoking is lower among men in households with higher levels of household wealth. 

Namibia is the only country in which a positive association was found. In Madagascar, while a significant 

association was found, there is no clear pattern of smoking prevalence across household wealth quintiles. 

The prevalence of smoking among men in Madagascar is highest in the wealthiest and poorest wealth 

quintiles, and is lowest in the middle wealth quintile. 

The disparities in smoking prevalence across wealth quintiles vary across the countries for men. 

Some of the largest disparities in smoking prevalence for men are found in Sierra Leone and Uganda, 

where men in the lowest wealth quintile are almost three times as likely to smoke as men in the highest 

wealth quintile. In addition, the prevalence of smoking is approximately twice as high in the lowest 

wealth quintile than in the highest wealth quintile in Liberia, India, the Dominican Republic, and Zambia. 

Women 

In 12 out of the 13 countries examined, there is a significant bivariate association between the 

prevalence of cigarette smoking and household wealth for women. In the Philippines, this association was 

only marginally significant (p=0.06). The results show two distinct patterns of smoking prevalence across 

wealth quintiles for women. In the majority of the countries, there is a positive association between the 

prevalence of cigarette smoking and household wealth. In Namibia, Jordan, Moldova, Turkey, Ukraine, 

Kazakhstan, Bolivia, Nicaragua, and Peru, the prevalence of smoking among women increases with 

higher levels of household wealth. In contrast, in Sierra Leone, Nepal, the Philippines, and the Dominican 

Republic, there is a negative association between smoking prevalence and household wealth. 

While the disparities in the prevalence of cigarette smoking for women across wealth quintiles 

vary across the countries, they are quite large in several of the countries. They are also larger in size than 

those found for men. Of the countries in which a significant association was found, the smallest 

disparities are found in Sierra Leone. The prevalence of cigarette smoking in Sierra Leone is comparable 

for women in the first four wealth quintiles, and only decreases slightly among women in the highest 

wealth quintile. Sierra Leone is also the one country where a much larger gradient in smoking prevalence 

across wealth quintiles is found for men than for women. As previously noted, while statistically 
41 

significant for both women and men, Sierra Leone is the country with the smallest disparities for women 

but the largest disparities for men. 

In the remaining countries in which a significant association was found, there is at least a twofold difference in smoking prevalence between women in the lowest and highest wealth quintiles. 

Moreover, in six of these countries, there is at least a four-fold difference (Namibia, Moldova, 

Kazakhstan, Nepal, Nicaragua, and Peru).

The results of this analysis also reveal some interesting gender differences in the nature of the 

associations between smoking status and household wealth. Among the seven countries in which data 

were examined for both women and men, four of the countries show the same pattern of smoking across 

wealth quintiles by gender (Namibia, Sierra Leone, Nepal, and the Dominican Republic) whereas three 

countries show divergent results by gender (Moldova, Ukraine, and Bolivia). In the latter three countries, 

the prevalence of smoking increases for women in wealthier households, whereas the prevalence of 

smoking decreases for men in wealthier households. 

Maternity status (women only) 

Smoking during pregnancy is associated with a range of adverse maternal and fetal outcomes, 

including placenta previa, preterm delivery, low birth weight, fetal loss, and developmental outcomes 

such as cleft lip (U.S. Department of Health and Human Services 2010). Secondhand smoke exposure 

among infants and children has also been linked to middle ear disease, respiratory symptoms, impaired 

lung function, and sudden infant death syndrome (U.S. Department of Health and Human Services 2010). 

This analysis examines the prevalence of cigarette smoking among women according to their maternity 

status (i.e., their pregnancy and breastfeeding status) across the countries. 

The results show that in 12 out of the 13 countries examined, a significant bivariate relationship is 

found between women’s maternity status and their likelihood of smoking. The only country in which no 

significant association was found is Sierra Leone. In Sierra Leone, women who were pregnant or 

breastfeeding were as likely to smoke as women who were neither pregnant nor breastfeeding. In the 

remaining countries, smoking was less prevalent among women who were breastfeeding than among 

women who were neither pregnant nor breastfeeding. In 9 countries, the prevalence of smoking was 

lowest among women who were pregnant.

Migration status (men only) 

This analysis examines the relationship between cigarette smoking among men and their 

migration status, operationalized as the number of times they slept away from home in the last 12 months. 

While little research has examined the association between labor migration and health (Benach, Muntaner 

et al. 2010), factors experienced by migrant workers such as social exclusion and decreased social 

support, poor living and working conditions, and reduced access to health care (Benach, Muntaner et al. 

2010) may influence the likelihood of smoking among men. While being away from home is often related 

to labor migration, men may also be away from home to visit relatives or friends, for a hospital stay or for 

vacation purposes. 

In the present analysis, a significant bivariate association was found between the prevalence of 

cigarette smoking and the number of times men slept away from home in only 6 of the 17 countries in 

which data were available on men’s migration status. The six countries in which a significant association 

was found are Lesotho, Liberia, Sierra Leone, Uzbekistan, India, and the Dominican Republic. 

The size and the nature of the association between migration status and smoking prevalence 

among men vary across the countries. In Liberia, Sierra Leone, India and Uzbekistan, there is a gradient 
42 

in smoking prevalence across migration subgroups. The prevalence of cigarette smoking is higher for men 

who stay away from home more frequently. The gradient is particularly large in Uzbekistan, where men 

who stayed away from home five times or more in the last year were twice as likely to smoke as men who 

did not stay away from home at all. Although a slight gradient is seen in Sierra Leone, there is also 

evidence of a threshold effect; smoking is more prevalent among men who stayed away from home any 

amount of time (1-4 or 5+ times) than among men who did not stay away from home. 

In Lesotho, only men who stayed away from home between 1-4 times were more likely to smoke 

than men who did not stay away from home at all. Finally, the results for men in the Dominican Republic 

do not appear to follow any of the patterns described above. Men who stayed away from home 1-4 times 

in the last year were the least likely to smoke, whereas men who stayed away from home 5+ times were 

the most likely to smoke. 

Exposure to mass media 

Exposure to mass media, including newspapers, television, and radio can potentially affect the 

likelihood that a person smokes in a number of ways. Media exposure may be a proxy for socioeconomic 

status or education, and these factors may affect the prevalence of smoking. Media can also be a source of 

information on the negative health consequences of smoking, which may alter attitudes, knowledge, and 

behavior related to tobacco use. On the other hand, marketing strategies and media portrayal of cigarette 

smoking as unproblematic, fashionable, masculine, or independent may encourage smoking among 

individuals (Charlesworth and Glantz 2005; National Cancer Institute 2008; World Health Organization 

2010). This analysis examines the relationship between at least weekly exposure to three forms of media 

(newspapers, television, and radio) and the prevalence of cigarette smoking. It also examines smoking 

prevalence as a function of the amount or diversity of exposure to these various media sources (described 

below). 

Men 

In 22 out of the 27 countries with data on men’s media use, there was a significant bivariate 

association between the prevalence of cigarette smoking and at least one of the media use variables. The 

five countries in which no significant association was found for any of the media use variables are 

Namibia, Rwanda, Tanzania, Armenia, and the Maldives. Eighteen of the countries show a significant 

association between the prevalence of cigarette smoking for men and their weekly use of newspapers. 

Fourteen of the countries show a significant association between the prevalence of cigarette smoking and 

their weekly television use. Finally, only nine of the countries show a significant association between the 

prevalence of cigarette smoking and men’s weekly radio use. 

In all of the countries except Madagascar, in which exposure to newspapers, television, or the 

radio was associated with smoking status for men, smoking was more prevalent among men who did not 

use that form of media at least once a week than among men who did. Madagascar is the only country in 

which smoking was more common among men who used specific forms of media (i.e., newspapers and 

the radio) at least once a week than among men who did not use these forms of media at least once a 

week. 

The last two media use variables reflect the amount or diversity of exposure to different types of 

media. In 16 of the countries there was a significant difference in the prevalence of cigarette smoking 

between men who used all three forms of media at least once a week and those who used at least one form 

of media less than once a week. Again, with the exception of Madagascar, in all of the countries smoking 

was more prevalent among men with less media exposure (i.e., those who used at least one form of media 

less than once a week). For the last media use variable, in 11 of the countries there was a significant 

difference in the prevalence of cigarette smoking between men did not use any form of media at least 
43 

once a week and men who did. With the exception of Madagascar, smoking was more prevalent among 

men who did not use any form of media on a weekly basis than among men who did. 

Women 

In all 12 countries in which data were available on women’s media use, there was a significant 

association between the prevalence of cigarette smoking and at least one of the media use variables. The 

specific nature and the strength of these associations vary across the countries. Almost all of the countries 

show an association between cigarette smoking for women and their weekly use of newspapers (11 out of 

12 countries). Fewer countries show a significant association between cigarette smoking and women’s 

weekly television use (7 out of 11 countries) or radio use (6 out of 11 countries). Thus, consistent with the 

results for men, more of the countries show an association between cigarette smoking among women and 

their weekly use of newspapers, whereas fewer of the countries show an association between cigarette 

smoking and their weekly use of the radio. 

In eight of the countries in which women’s newspaper use was associated with their cigarette 

smoking, those who read a newspaper at least once a week were more likely to smoke than those who did 

not read a newspaper (Namibia, Moldova, Turkey, Ukraine, Kazakhstan, Bolivia, Nicaragua, and Peru). 

In contrast, in Sierra Leone, Nepal, and the Dominican Republic, women who did not read a newspaper at 

least once a week were more likely to smoke than those who did. The magnitude of this association is 

particularly striking for Nepal, where less than 1 percent of women who read a newspaper at least once a 

week smoked cigarettes compared with 16.9 percent of women who did not read a newspaper. 

In five of the countries in which women’s television use was associated with the prevalence of 

cigarette smoking, those who watched television at least once a week were more likely to smoke than 

those who did not (Namibia, Moldova, Bolivia, Nicaragua, and Peru). In contrast, in Nepal and the 

Dominican Republic, women who did not watch television at least once a week were more likely to 

smoke than those who did. 

Finally, among the six countries in which women’s radio use was associated with the prevalence 

of cigarette smoking, the results for three of the countries showed that women who listened to the radio at 

least once a week were more likely to smoke than those who did not (Ukraine, Kazakhstan, and Peru), 

whereas the reverse was true in Nepal, the Philippines, and the Dominican Republic. 

With respect to the amount or diversity of media exposure, with the exception of the Philippines, 

all of the countries with available data show a significant relationship between women’s use of all three 

forms of media and their prevalence of cigarette smoking. However, the nature of this association varies 

across the countries. The results for seven of the countries show that the prevalence of cigarette smoking 

is higher for women who used all three forms of media at least once a week than women who used at least 

one form of media less than once a week (Namibia, Moldova, Ukraine, Kazakhstan, Bolivia, Nicaragua, 

and Peru). The three countries with contrasting findings are Sierra Leone, Nepal, and the Dominican 

Republic. Again, the results for Nepal are striking in that smoking is almost exclusively concentrated 

among women with lower media use. 

Eight of the 11 countries with available data show a significant association between smoking 

prevalence and any weekly media exposure. No significant association was found in Sierra Leone, 

Ukraine, and Kazakhstan. It should be noted that in Ukraine and Kazakhstan, the confidence intervals for 

the subgroup of women who did not report any weekly media use are large because relatively few women 

fell in this category. The results for five of the countries in which a significant association was found 

show that the prevalence of smoking is higher for women with any weekly media exposure than for 

women with no weekly media exposure (Namibia, Moldova, Bolivia, Nicaragua, Peru). However, these 
44 

results are in opposition to those found in Nepal, the Philippines, and the Dominican Republic, where the 

prevalence of smoking is higher for women with no weekly media exposure. 

In summary, with a few exceptions, the results of this analysis paint a different picture of the 

relationship between media exposure and smoking prevalence for women and men. For women, smoking 

was more prevalent among those who reported at least weekly media exposure whereas for men, smoking 

was less prevalent among those who reported at least weekly media exposure. Future research should 

examine the extent to which these associations reflect the direct influence of media exposure on tobacco 

use versus the influence of confounding factors related to both smoking behavior and media exposure. 

Number of cigarettes smoked in the last 24 hours by women and men 

While there is no risk-free level of exposure to tobacco smoke, the risk and severity of many 

adverse health outcomes caused by smoking are directly related to the duration and level of exposure to 

tobacco smoke (Kuper, Boffetta et al. 2002; Thornton, Edwards et al. 2005; Liang, Chen et al. 2009; Shah 

and Cole 2010). To understand the public health toll of tobacco use, it is important to examine the 

quantity of cigarette smoking within countries. This section examines the number of cigarettes smoked in 

the last 24 hours by current smokers age 15-49 across the countries. 

Men 

The number of cigarettes smoked by men who smoke varies across the countries examined, with 

the lowest generally reported by smokers in sub-Saharan Africa and the highest reported by male smokers 

in North Africa/West Asia/Europe (Appendix Table A3a). In sub-Saharan Africa, male smokers were 

most likely to report smoking 3-5 cigarettes in the past 24 hours in almost all of the countries, with 

between one-third and half of male smokers reporting having smoked 3-5 cigarettes. In a small number of 

countries in sub-Saharan Africa, more than a quarter of male smokers reported smoking 10 or more 

cigarettes in the last 24 hours (Ethiopia, Kenya, Namibia, Sierra Leone, Zimbabwe). 

The number of cigarettes smoked is consistently high among men who smoke in all countries in 

North Africa/West Asia/Europe, with 83-93 percent of smokers in these countries reporting having 

smoked 10 or more cigarettes in the last 24 hours. 

In the majority of the remaining countries in Central Asia, South and Southeast Asia, and Latin 

America/Caribbean, while men who smoked were most likely to report smoking 10 or more cigarettes in 

the last 24 hours, the proportion was smaller than the proportion reporting this amount in North 

Africa/West Asia/Europe. In Bangladesh, male smokers were most likely (41 percent) to report smoking 

no cigarettes in the last 24 hours. However, many male Bangladeshi smokers smoked bidis (small handrolled leaf wrappers), which were not captured in this analysis. Of the remaining countries, the Maldives 

stands out with two-thirds of male smokers reporting having smoked 10 or more cigarettes in the last 24 

hours. 

Women 

The results for women also show variation in the frequency of cigarette smoking across the 

countries (Appendix Table A3b). Women in sub-Saharan Africa and Latin America/Caribbean who 

smoke also tended to report a lower number of cigarettes smoked than women in other regions. The 

largest percentage of female smokers in sub-Saharan Africa and Latin America/Caribbean reported 

smoking either 1-2 cigarettes or 3-5 cigarettes in the last 24 hours. In Mozambique and Uganda, more 

than half of female smokers reported smoking only 1-2 cigarettes in the last 24 hours. Countries in subSaharan Africa where a notable proportion of female smokers (more than 20 percent) reported smoking 

10 or more cigarettes include Guinea, Kenya, Namibia, and Swaziland. 
45 

Consistent with the results for men, the number of cigarettes smoked by women who smoke was 

high across all countries in North Africa/West Asia/Europe, with at least 40 percent of smokers in these 

countries reporting having smoked 10 or more cigarettes in the last 24 hours. In Albania, more than 60 

percent of female smokers reported smoking 10 or more cigarettes in the last 24 hours. In the one country 

examined in Central Asia (Uzbekistan), the number of cigarettes smoked was also high for female 

smokers, with 40 percent of smokers reporting having smoked 10 or more cigarettes. 

In South and Southeast Asia, female smokers in most countries were most likely to have reported 

having smoked 3-5 cigarettes. In Timor-Leste and Indonesia, female smokers were most likely to have 

smoked 1-2 cigarettes in the last 24 hours. In a number of countries in this region, more than 20 percent of 

female smokers reported smoking 10 or more cigarettes, including Cambodia, India, Nepal, and the 

Philippines. 

Finally, in Latin America and the Caribbean, the number of cigarettes smoked varies across the 

countries. In Bolivia and Peru, roughly 60 percent of female smokers reported not smoking any cigarettes 

at all in the last 24 hours. In Honduras and Nicaragua, female smokers were most likely to report having 

smoked 1-2 cigarettes in the last 24 hours. In Haiti, roughly the same proportion of female smokers 

reported smoking 1-2 cigarettes and 3-5 cigarettes. Finally, in the Dominican Republic, 29 percent of 

female smokers reported having smoked 3-5 cigarettes in the last 24 hours, and the same percentage 

reported smoking 10 or more cigarettes in the last 24 hours. 

Gender differences in the number of cigarettes smoked in the last 24 hours 

In most countries with available data for both women and men, the number of cigarettes smoked 

by male smokers is greater than the number smoked by female smokers. The size of the gender 

differences varies across the countries. In sub-Saharan Africa, there are some countries where the gender 

differences are small (Kenya, Namibia, and Swaziland). In North Africa/West Asia/Europe, while women 

and men who smoked most commonly reported having smoked 10 or more cigarettes in the last 24 hours, 

men were much more likely to have done so than women. In Uzbekistan, very small gender differences 

are found in the number cigarettes smoked. The magnitude of the gender differences in South and 

Southeast Asia vary, with smaller differences found in Nepal and the largest difference found in the 

Maldives. Finally, among smokers in the one country in Latin America/Caribbean with data available for 

women and men (the Dominican Republic), 38 percent of men and 29 percent of women smoked 10 or 

more cigarettes in the last 24 hours. 

47 

4 Conclusions and Study Limitations 

The examination of tobacco use among men and women in 49 developing countries reveals that 

the prevalence of any tobacco use varies substantially worldwide for both women and men, although 

women are much less likely than men to use tobacco in all countries examined. For men, the prevalence 

of any tobacco use exceeds 40 percent in all the countries examined in North Africa/West Asia/Europe, 

Central Asia, and South and Southeast Asia. For women, no clear regional patterns are visible. Tobacco 

use, at about one in five women using, is highest in Madagascar and Nepal. 

Manufactured cigarettes are the most common type of tobacco used worldwide; thus, a substantial 

burden of death and disability among tobacco users is due to this one form of tobacco alone. For men, the 

prevalence of cigarette smoking in North Africa/West Asia/Europe and South and Southeast Asia is 

consistently high, ranging from nearly one-third to two-thirds of men. Among women by contrast, in all 

but 3 of the 47 countries with available data, the prevalence of current cigarette smoking is less than 10 

percent. The prevalence is less than one percent in 21 of the countries. The use of smokeless tobacco, 

which includes snuff and chewing tobacco, is low in the majority of the countries examined for both 

women and men. 

The number of cigarettes smoked by men who smoke varies across the countries examined, with 

fewer cigarettes generally smoked by men in sub-Saharan Africa. In contrast, in North Africa/West 

Asia/Europe, men who smoked reported smoking the greatest number of cigarettes, with over 80 percent 

of men reporting having smoked 10 or more cigarettes in the last 24 hours. The regional patterns for 

women are generally consistent with those found for men, but in almost every country female smokers 

were much less likely than male smokers to have smoked 10 or more cigarettes in the last 24 hours. 

Cigarette smoking among women and men varies significantly by age, marital status, level of 

education, urban-rural area, employment and cash earnings (women only), occupation (men only), 

household wealth, maternity status, exposure to mass media, and migration status (men only). For both 

women and men, the nature and the strength of these associations varies across the countries examined. 

Based on this analysis, it is clear that tobacco control efforts need to be strengthened in these 

countries. The high levels of tobacco use in most countries, particularly among men, pose a clear and 

significant health hazard for these populations. In addition, men who smoke cigarettes tend to be heavy 

smokers, especially in North Africa/West Asia and Europe. This suggests that the duration and level of 

exposure to tobacco smoke, factors that increase the health risks associated with tobacco use, also remain 

disturbingly high in many of the countries examined. 

Despite the important findings of this analysis, there are several limitations of DHS data that 

should be considered when interpreting these results. The DHS is only conducted in developing countries, 

and the countries that were included in this report are not representative of all countries within a particular 

region. There are also a number of developing countries with DHS surveys that were excluded from this 

report as they did not collect information on current tobacco use. Another limitation is that the data on 

tobacco use are self-reported and may therefore be affected by reporting bias (e.g., underreporting 

tobacco use) or recall bias (e.g., incorrectly reporting the number of cigarettes smoked). The DHS surveys 

are also not intended to be tobacco surveys and therefore do not collect important information related to 

the duration of smoking or addiction. As noted in the methods section, caution should also be taken when 

comparing the prevalence of tobacco use across the countries given that the surveys may have been 

conducted at different points in time, the population surveyed within the countries may have differed with 

respect to the age range or marital status of respondents, and the questions assessing tobacco use may 

have differed. 

49 

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Appendix 

Appendix Table A1. Correlates of current cigarette smoking among men age 15-49 in countries with >10% prevalence of smoking, 2002-10 Characteristics 

Kenya 2008/09 Lesotho 2009 Liberia 2007 Madagascar 2008/09 Malawi 2004 

Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** *** *** *** ***  15-24 years 8.2 (6.2-10.2) 25.8 (23.0-28.5) 2.4 (1.6-3.2) 23.4 (21.1-25.7) 7.0 (5.2-8.7)  25-34 years 22.7 (18.1-27.4) 44.2 (40.3-48.2) 18.3 (15.5-21.1) 31.6 (29.2-34.1) 19.9 (16.9-22.9)  35-49 years 26.4 (22.2-30.7) 41.0 (37.1-44.9) 25.8 (23.1-28.5) 31.0 (28.4-33.7) 26.2 (22.1-30.2)  50 years and over 28.6 (20.7-36.6) 30.8 (25.2-36.5) na na 24.2 (21.0-27.5) 23.9 (16.6-31.3) Marital status *** *** *** *** *** 

 Never married 9.9 (7.9-12.0) 27.3 (24.7-30.0) 5.1 (3.8-6.4) 20.1 (17.6-22.5) 7.5 (5.8-9.3) 

 Currently married 22.6 (19.0-26.3) 42.3 (38.9-45.6) 20.8 (18.7-22.9) 31.2 (29.3-33.0) 20.7 (18.1-23.3) 

 Formerly married 41.7 (30.1-53.2) 54.7 (46.5-62.9) 26.9 (20.0-33.7) 38.1 (32.3-43.8) 26.5 (16.5-36.5) Education *** *** *** 

 No education 19.8 (10.2-29.4) 43.5 (38.2-48.9) 29.4 (25.5-33.4) 30.4 (27.1-33.8) 25.4 (19.8-31.0)  Primary 19.5 (16.4-22.5) 38.0 (34.8-41.2) 13.6 (11.6-15.6) 27.7 (25.5-30.0) 17.1 (14.9-19.3) 

 Secondary 15.0 (11.5-18.5) 28.5 (25.1-31.9) 11.3 (9.6-12.9) 27.5 (25.2-29.8) 11.3 (8.7-14.0)  Higher 15.4 (10.9-19.8) 22.9 (14.9-30.8) 9.6 (5.0-14.2) 30.6 (23.8-37.5) 5.3 (0.0-11.6) 

Residence *** ***  Urban 17.2 (12.5-21.9) 33.0 (28.8-37.2) 11.3 (9.1-13.6) 33.6 (31.2-36.1) 14.5 (10.4-18.7) 

 Rural 17.6 (15.0-20.2) 35.0 (32.6-37.5) 17.8 (15.7-19.8) 27.1 (25.4-28.8) 16.8 (14.8-18.8) 

Occupation *** *** *** *** *** 

 Not working 4.5 (2.1-6.8) 25.0 (21.4-28.6) 4.5 (2.2-6.7) 10.6 (7.9-13.3) 6.1 (4.2-8.1) 

 Professional/technical/managerial 19.1 (13.9-24.2) 23.0 (14.9-31.2) 9.3 (5.5-13.2) 33.0 (25.7-40.3) 6.7 (1.9-11.5) 

 Clerical 23.8 (3.8-43.8) 35.1 (20.8-49.3) 15.0 (4.5-25.5) 26.3 (7.9-44.8) 15.9 (2.5-29.4) 

 Sales and services 18.9 (12.6-25.3) 32.9 (25.2-40.7) 14.9 (11.4-18.3) 34.4 (28.9-39.8) 18.4 (13.6-23.2)  Skilled manual 19.7 (13.3-26.0) 45.8 (39.7-51.9) 23.2 (18.5-28.0) 37.3 (32.8-41.8) 20.4 (14.8-26.0)  Unskilled manual 24.6 (18.8-30.5) 46.7 (39.3-54.0) 9.6 (3.7-15.5) 33.6 (24.5-42.7) 22.4 (14.3-30.4) 

 Agriculture 17.9 (14.2-21.6) 38.1 (34.7-41.5) 20.3 (17.9-22.6) 28.8 (26.9-30.8) 20.8 (17.7-23.9) 

Household wealth quintile ** *** * ***  Lowest 16.7 (11.3-22.1) 35.1 (30.2-40.0) 20.4 (17.4-23.4) 29.5 (25.8-33.2) 23.7 (18.8-28.6)  Second 17.1 (12.1-22.1) 36.6 (31.7-41.4) 20.9 (17.8-24.0) 26.1 (23.2-28.9) 17.5 (14.1-20.9)  Middle 19.3 (14.8-23.7) 36.7 (32.2-41.1) 14.8 (12.1-17.5) 25.4 (22.3-28.6) 17.5 (14.1-20.9) 

 Fourth 19.6 (15.2-24.0) 37.4 (32.5-42.3) 11.6 (9.1-14.0) 28.3 (25.3-31.2) 14.4 (10.8-17.9) 

 Highest 15.4 (11.7-19.2) 27.4 (23.6-31.2) 9.8 (7.0-12.6) 31.1 (28.8-33.4) 12.3 (9.8-14.7) 

Migration status - times slept away from home in last 12 months * *  None na na 32.1 (29.4-34.9) 13.7 (11.9-15.6) na na 16.9 (14.6-19.1)  1-4 na na 37.8 (34.3-41.2) 16.5 (14.2-18.8) na na 15.8 (12.9-18.6) 

 5 or more na na 34.6 (30.4-38.7) 17.9 (14.5-21.3) na na 14.2 (9.9-18.4) Exposure to mass media ** ***    Does not read a newspaper at least once a week 18.2 (15.1-21.3) 36.3 (33.8-38.7) 17.3 (15.5-19.1) 27.5 (25.8-29.1) 17.5 (15.3-19.7)  Reads a newspaper at least once a week 16.7 (13.6-19.8) 26.9 (22.2-31.6) 10.8 (8.6-13.0) 32.8 (29.5-36.2) 13.0 (10.8-15.2)

** * * *** 

 Does not watch television at least once a week 21.1 (18.1-24.1) 36.0 (33.4-38.6) 18.4 (16.6-20.1) 27.6 (25.9-29.4) 16.7 (14.7-18.7)  Watches television at least once a week 13.9 (11.1-16.6) 30.5 (26.7-34.2) 10.2 (7.8-12.5) 30.6 (27.8-33.3) 14.4 (11.4-17.3) 

* 

 Does not listen to the radio at least once a week 16.9 (10.9-22.8) 35.0 (31.5-38.6) 16.4 (14.2-18.6) 26.2 (23.9-28.5) 18.6 (14.3-22.9) 

 Listens to the radio at least once a week 17.6 (15.3-19.9) 34.1 (31.7-36.6) 14.6 (12.9-16.3) 29.6 (27.9-31.3) 15.9 (14.0-17.7) 

* ** *** *** 

 At least one form of media less than once per week 19.2 (16.4-22.0) 35.5 (33.2-37.8) 16.6 (15.0-18.1) 27.6 (26.0-29.2) 16.6 (14.6-18.5) 

 All three media at least once a week 13.8 (10.5-17.1) 26.2 (20.8-31.6) 9.6 (6.7-12.6) 34.5 (30.8-38.2) 13.6 (10.5-16.7) 

** * 

 At least one form of media at least once a week 17.5 (15.2-19.8) 33.9 (31.6-36.3) 14.2 (12.5-15.9) 29.4 (27.8-31.0) 15.8 (14.0-17.6) 

 No media at least once a week 17.4 (10.3-24.5) 35.6 (31.7-39.4) 18.4 (15.8-20.9) 26.1 (23.7-28.6) 19.0 (14.4-23.6) 

Total age 15-49 17.5 (15.2-19.8) 34.5 (32.4-36.6) 15.2 (13.6-16.7) 28.2 (26.7-29.7) 16.3 (14.5-18.1) Age 50 to highest age 28.6 (20.7-36.6) 30.8 (25.2-36.5) na na 24.2 (21.0-27.5) 23.9 (16.6-31.3) 

Total age 15 to highest age 18.2 (16.0-20.4) 34.1 (32.1-36.1) 15.2 (13.6-16.7) 27.7 (26.3-29.2) 16.6 (14.8-18.4) 

Continued... 

53 
Appendix Table A1—Continued

Characteristics 

Mozambique 2003 Namibia 2006/07 Rwanda 2005 Sierra Leone 2008 Swaziland 2006/07 Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** *** *** *** ***  15-24 years 7.0 (5.1-9.0) 14.4 (12.0-16.8) 7.7 (6.5-8.9) 16.2 (13.2-19.1) 6.4 (5.0-7.7) 

 25-34 years 24.1 (19.9-28.3) 25.7 (22.5-29.0) 17.8 (15.3-20.2) 41.0 (36.7-45.4) 19.4 (16.6-22.2)  35-49 years 15.1 (12.2-18.0) 25.8 (22.6-28.9) 20.6 (17.9-23.3) 49.7 (46.6-52.8) 25.9 (22.7-29.1)  50 years and over 13.0 (9.0-17.0) na na 18.3 (14.6-22.1) 41.9 (35.5-48.2) na na 

Marital status *** *** *** *** ***  Never married 6.6 (4.6-8.6) 16.6 (14.6-18.7) 9.0 (7.7-10.4) 17.9 (15.1-20.6) 10.0 (8.6-11.3) 

 Currently married 16.7 (14.3-19.1) 26.8 (23.7-30.0) 18.2 (16.2-20.2) 47.2 (44.4-50.1) 18.2 (15.5-20.8) 

 Formerly married 42.1 (29.7-54.4) 45.0 (35.2-54.9) 27.7 (18.2-37.3) 56.1 (44.6-67.6) 40.1 (32.4-47.7) 

Education *** * *** *** *** 

 No education 12.9 (8.3-17.4) 23.1 (18.2-28.0) 21.2 (17.7-24.7) 50.1 (46.9-53.3) 24.1 (18.7-29.5)  Primary 16.1 (13.9-18.2) 18.7 (16.1-21.3) 12.6 (11.3-14.0) 31.9 (27.5-36.4) 13.1 (10.8-15.5) 

 Secondary 7.3 (4.5-10.0) 22.7 (20.2-25.1) 12.0 (8.9-15.2) 21.3 (18.3-24.2) 12.5 (10.8-14.3) 

 Higher 16.8 (4.2-29.4) 14.6 (8.7-20.6) 6.0 (0.0-12.3) 20.3 (13.4-27.2) 15.1 (11.4-18.8) 

Residence   ** *  Urban 15.1 (12.6-17.6) 23.4 (20.5-26.3) 17.7 (14.5-20.8) 22.6 (19.1-26.1) 15.0 (12.6-17.4)  Rural 13.5 (10.9-16.0) 18.5 (16.5-20.5) 13.0 (11.7-14.4) 45.4 (42.6-48.1) 13.4 (11.7-15.1) Occupation *** *** *** *** *** 

 Not working 5.4 (3.4-7.4) 13.3 (11.1-15.5) 11.5 (9.9-13.1) 6.2 (3.1-9.4) 9.1 (7.6-10.6) 

 Professional/technical/managerial 9.7 (5.2-14.3) 25.5 (20.1-31.0) 8.5 (4.0-13.0) 20.9 (14.3-27.6) 12.3 (8.7-15.8) 

 Clerical 13.0 (3.0-23.0) 30.9 (12.7-49.1) -- -- 49.9 (35.4-64.4) 12.6 (5.4-19.7) 

 Sales and services 19.2 (14.0-24.4) 24.9 (18.9-30.9) 13.7 (8.5-18.9) 33.0 (26.5-39.5) 15.2 (12.0-18.5)  Skilled manual 22.5 (16.3-28.6) 23.5 (19.5-27.5) 19.1 (14.2-24.0) 43.3 (36.1-50.6) 22.8 (19.3-26.3)  Unskilled manual 14.0 (4.0-23.9) 26.4 (18.0-34.8) 17.8 (14.0-21.5) 59.4 (48.9-69.9) 12.7 (6.4-19.0)  Agriculture 16.1 (13.1-19.2) 24.9 (21.2-28.7) 15.5 (13.1-17.9) 47.7 (44.7-50.6) 18.4 (14.2-22.6) Household wealth quintile *** ***  Lowest 11.2 (7.8-14.5) 15.0 (11.5-18.5) 14.4 (11.4-17.4) 50.2 (45.1-55.3) 17.2 (13.9-20.6)  Second 16.2 (11.6-20.9) 14.7 (11.6-17.8) 13.1 (10.2-15.9) 43.4 (38.0-48.8) 13.2 (10.1-16.2)  Middle 14.5 (10.8-18.2) 23.2 (20.2-26.1) 13.6 (11.2-16.0) 44.7 (39.7-49.7) 14.1 (11.1-17.2)  Fourth 17.2 (12.8-21.7) 21.3 (17.8-24.9) 13.9 (11.2-16.6) 35.1 (30.0-40.2) 13.7 (11.0-16.3) 

 Highest 13.2 (9.7-16.7) 26.2 (21.1-31.4) 14.3 (11.8-16.7) 17.2 (12.5-21.9) 12.3 (10.1-14.6) Migration status - times slept away from home in last 12 months ***  None 14.4 (12.1-16.7) 19.9 (17.6-22.3) 13.8 (12.4-15.2) 30.8 (27.9-33.7) 14.5 (12.2-16.7)  1-4 13.7 (10.8-16.6) 21.3 (17.9-24.7) 13.4 (11.1-15.7) 40.1 (36.5-43.7) 12.8 (10.3-15.3)  5 or more 14.9 (9.5-20.3) 23.8 (20.1-27.5) 16.6 (11.5-21.6) 43.1 (38.4-47.7) 13.8 (11.9-15.6) Exposure to mass media *** **  Does not read a newspaper at least once a week 14.6 (12.6-16.6) 21.2 (18.7-23.8) 14.0 (12.7-15.4) 40.4 (37.8-43.1) 16.0 (13.8-18.2)  Reads a newspaper at least once a week 11.6 (7.9-15.3) 20.7 (18.2-23.3) 12.4 (9.2-15.6) 20.5 (15.9-25.0) 12.5 (11.1-14.0) 

*** ** 

 Does not watch television at least once a week 14.4 (12.2-16.6) 19.5 (17.3-21.7) 13.7 (12.4-15.0) 40.1 (37.6-42.7) 15.6 (13.6-17.6) 

 Watches television at least once a week 13.4 (9.7-17.2) 22.4 (19.7-25.0) 15.4 (12.1-18.7) 20.5 (15.9-25.1) 11.7 (10.1-13.3) 

* 

 Does not listen to the radio at least once a week 17.6 (13.8-21.3) 22.6 (17.5-27.8) 12.0 (9.6-14.3) 39.6 (35.4-43.8) 16.2 (13.4-19.1) 

 Listens to the radio at least once a week 13.1 (11.2-15.1) 20.6 (18.5-22.6) 14.4 (13.0-15.7) 35.0 (32.4-37.6) 13.4 (11.9-14.8) 

*** 

 At least one form of media less than once per week 14.6 (12.7-16.5) 20.5 (18.3-22.8) 14.0 (12.7-15.3) 38.9 (36.5-41.4) 14.4 (12.7-16.1)  All three media at least once a week 9.9 (5.5-14.4) 21.6 (18.2-25.1) 11.8 (7.0-16.7) 15.0 (10.0-20.0) 12.7 (10.6-14.9) 

* * *** 

 At least one form of media at least once a week 13.3 (11.3-15.3) 21.1 (19.2-23.0) 14.3 (13.0-15.7) 34.7 (32.1-37.3) 13.3 (11.9-14.6) 

 No media at least once a week 17.7 (13.7-21.7) 19.5 (15.0-24.1) 12.0 (9.5-14.4) 40.7 (36.3-45.1) 22.4 (17.4-27.4) Total age 15-49 14.2 (12.4-16.0) 20.9 (19.2-22.7) 13.9 (12.6-15.1) 36.7 (34.5-38.9) 13.8 (12.5-15.2) Age 50 to highest age 13.0 (9.0-17.0) na na 18.3 (14.6-22.1) 41.9 (35.5-48.2) na na 

Total age 15 to highest age 14.0 (12.3-15.7) 20.9 (19.2-22.7) 14.2 (13.1-15.4) 37.2 (35.1-39.3) 13.8 (12.5-15.2) 

Continued...

54 
Appendix Table A1—Continued

Characteristics Tanzania 2004/05 Uganda 2006 Zambia 2007 Zimbabwe 2005/06 Albania 2008/09 

Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** *** *** *** ***  15-24 years 7.5 (5.7-9.4) 6.5 (4.7-8.4) 9.2 (7.8-10.5) 13.3 (11.8-14.8) 23.5 (19.9-27.1) 

 25-34 years 27.8 (23.1-32.5) 24.7 (20.6-28.8) 29.8 (27.1-32.5) 25.9 (23.4-28.4) 55.2 (50.2-60.2)  35-49 years 34.8 (30.5-39.2) 28.2 (24.2-32.1) 37.2 (34.6-39.7) 32.9 (30.2-35.7) 52.0 (48.9-55.0)  50 years and over na na 31.2 (22.6-39.9) 31.7 (27.0-36.4) 40.0 (34.3-45.6) na na 

Marital status *** *** *** *** *** 

 Never married 7.3 (5.4-9.2) 6.8 (4.8-8.8) 10.8 (9.4-12.2) 12.5 (11.1-13.9) 28.2 (25.3-31.1) 

 Currently married 29.2 (26.0-32.4) 23.5 (20.3-26.7) 31.3 (29.3-33.3) 28.0 (26.1-29.9) 53.1 (50.4-55.9) 

 Formerly married 47.8 (37.8-57.8) 42.9 (32.5-53.3) 45.8 (39.1-52.6) 49.2 (43.6-54.7) -- -- Education *** *** *** ** 

 No education 24.7 (18.4-31.0) 32.8 (23.4-42.1) 41.3 (35.1-47.4) 52.8 (40.4-65.3) -- --  Primary 21.4 (18.9-24.0) 21.1 (18.4-23.9) 27.3 (25.3-29.3) 25.4 (23.0-27.8) 48.6 (44.7-52.5) 

 Secondary 14.0 (8.9-19.2) 9.4 (6.9-12.0) 18.4 (16.5-20.3) 19.9 (18.2-21.5) 38.2 (35.1-41.3)  Higher 15.2 (5.5-24.9) 8.0 (2.8-13.3) 14.1 (9.7-18.6) 12.7 (9.1-16.4) 38.9 (31.9-45.9) 

Residence * *  Urban 18.5 (13.9-23.1) 12.9 (7.9-18.0) 21.2 (18.5-23.9) 19.5 (17.2-21.9) 42.3 (39.6-45.0)  Rural 21.9 (19.4-24.5) 19.1 (16.8-21.5) 24.7 (23.0-26.4) 22.5 (21.0-24.0) 42.7 (39.5-45.9) Occupation *** ** *** *** *** 

 Not working 2.7 (1.0-4.4) 4.4 (0.8-8.0) 6.0 (4.6-7.4) 9.8 (7.9-11.7) 21.2 (17.5-24.9)  Professional/technical/managerial 17.3 (4.8-29.9) 10.5 (4.8-16.2) 15.9 (10.7-21.0) 16.0 (12.0-20.0) 45.9 (40.3-51.5) 

 Clerical -- -- -- -- 12.9 (2.2-23.5) 15.6 (8.7-22.5) 44.6 (28.1-61.1) 

 Sales and services 16.4 (8.7-24.2) 14.7 (9.2-20.2) 28.0 (24.5-31.4) 22.4 (19.0-25.8) 49.6 (42.8-56.4)  Skilled manual 22.3 (15.3-29.3) 15.9 (10.0-21.8) 32.4 (28.8-36.0) 31.6 (28.3-35.0) 53.9 (49.9-58.0)  Unskilled manual 27.5 (19.1-35.9) 25.1 (15.3-34.9) 23.4 (5.2-41.7) 33.7 (27.3-40.0) 57.6 (46.4-68.9)  Agriculture 25.9 (22.9-28.9) 20.0 (17.2-22.8) 28.4 (26.3-30.6) 27.1 (24.3-29.9) 40.6 (34.5-46.7) Household wealth quintile * *** *** *** 

 Lowest 24.3 (19.8-28.8) 25.5 (20.9-30.1) 28.7 (25.8-31.7) 25.3 (22.4-28.3) 45.1 (39.8-50.4)  Second 22.8 (18.1-27.4) 25.0 (20.3-29.6) 28.2 (25.0-31.4) 22.8 (20.2-25.3) 43.4 (36.4-50.5)  Middle 23.7 (18.8-28.7) 20.5 (15.0-26.0) 22.3 (19.6-25.0) 22.6 (20.1-25.1) 41.0 (36.0-46.1)  Fourth 20.1 (15.4-24.8) 14.4 (11.1-17.6) 25.7 (22.7-28.7) 22.4 (19.7-25.0) 44.6 (40.4-48.7) 

 Highest 15.5 (11.2-19.8) 8.9 (5.9-12.0) 14.7 (11.9-17.6) 15.4 (12.7-18.1) 39.3 (35.3-43.4) Migration status - times slept away from home in last 12 months 

 None 19.2 (16.4-21.9) 17.7 (14.8-20.7) 23.1 (21.1-25.0) 20.9 (19.0-22.7) na na  1-4 22.6 (19.3-25.9) 18.9 (15.7-22.1) 23.4 (21.3-25.6) 21.5 (19.6-23.5) na na  5 or more 24.2 (18.5-30.0) 17.8 (14.0-21.5) 23.6 (20.0-27.2) 21.9 (19.3-24.6) na na 

Exposure to mass media *** *** ** 

 Does not read a newspaper at least once a week 22.1 (19.5-24.7) 20.1 (17.7-22.5) 25.4 (23.7-27.0) 22.9 (21.4-24.4) 43.0 (39.6-46.4) 

 Reads a newspaper at least once a week 19.1 (15.6-22.5) 10.9 (7.4-14.4) 18.0 (15.7-20.3) 19.0 (16.9-21.0) 42.1 (39.2-44.9)

** *** *** 

 Does not watch television at least once a week 21.9 (19.4-24.5) 19.3 (16.9-21.7) 27.2 (25.5-28.9) 23.4 (21.9-24.9) 49.3 (34.6-64.1) 

 Watches television at least once a week 18.4 (14.1-22.6) 10.9 (7.3-14.6) 16.4 (14.1-18.6) 18.6 (16.5-20.6) 42.4 (40.3-44.5) 

* * * 

 Does not listen to the radio at least once a week 23.3 (19.0-27.7) 16.8 (11.2-22.3) 25.6 (23.0-28.1) 22.7 (20.9-24.5) 45.8 (42.3-49.3) 

 Listens to the radio at least once a week 20.4 (18.0-22.9) 18.3 (16.0-20.6) 22.4 (20.7-24.1) 20.5 (18.9-22.1) 39.7 (36.7-42.7) 

** *** * 

 At least one form of media less than once per week 21.8 (19.4-24.2) 18.9 (16.6-21.3) 24.8 (23.2-26.4) 22.3 (21.0-23.5) 43.7 (40.9-46.4) 

 All three media at least once a week 17.0 (11.9-22.0) 10.4 (5.9-14.8) 15.9 (12.9-18.8) 18.6 (15.9-21.2) 40.4 (37.1-43.7) 

*** 

 At least one form of media at least once a week 20.2 (17.8-22.7) 18.3 (16.0-20.6) 21.6 (20.0-23.2) 20.6 (19.1-22.2) 42.4 (40.3-44.5) 

 No media at least once a week 25.0 (19.9-30.0) 17.4 (11.3-23.5) 30.2 (27.2-33.3) 22.9 (20.7-25.2) 51.4 (35.3-67.5) 

Total age 15-49 21.0 (18.8-23.3) 18.1 (15.9-20.2) 23.2 (21.7-24.7) 21.3 (20.0-22.6) 42.5 (40.4-44.6) Age 50 to highest age na na 31.2 (22.6-39.9) 31.7 (27.0-36.4) 40.0 (34.3-45.6) na na 

Total age 15 to highest age 21.0 (18.8-23.3) 18.7 (16.6-20.8) 23.9 (22.4-25.4) 22.1 (20.8-23.4) 42.5 (40.4-44.6) 

Continued...

55
Appendix Table A1—Continued

Characteristics 

Armenia 2005 Azerbaijan 2006 Egypt 2008 Moldova 2005 Ukraine 2007 

Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** *** *** *** ***  15-24 years 35.6 (30.2-41.0) 22.3 (18.0-26.6) 25.4 (22.9-28.0) 40.8 (36.8-44.7) 36.0 (31.8-40.1)  25-34 years 76.3 (70.4-82.2) 61.0 (56.1-65.9) 43.9 (40.7-47.1) 60.5 (55.7-65.3) 55.1 (51.0-59.2)  35-49 years 74.1 (69.1-79.2) 62.8 (58.7-66.9) 47.0 (44.0-49.9) 57.3 (53.3-61.3) 59.6 (55.7-63.5)  50 years and over na na 54.7 (47.5-62.0) 43.4 (39.1-47.7) 46.4 (41.1-51.7) na na 

Marital status *** *** *** *** *** 

 Never married 42.2 (36.9-47.5) 28.5 (24.5-32.5) 27.6 (25.1-30.2) 40.4 (36.6-44.2) 39.3 (35.5-43.2) 

 Currently married 73.8 (69.7-77.9) 61.3 (58.3-64.3) 45.8 (43.4-48.2) 57.8 (54.7-61.0) 55.0 (51.3-58.7)  Formerly married -- -- 71.9 (51.7-92.1) 65.3 (45.2-85.4) 78.2 (69.1-87.2) 72.0 (65.5-78.5) Education * *** ** *** 

 No education -- -- -- -- 48.1 (42.8-53.4) -- -- -- -- 

 Primary -- -- -- -- 51.8 (47.4-56.1) -- -- -- -- 

 Secondary 61.8 (57.6-66.0) 50.8 (48.2-53.5) 37.3 (35.1-39.5) 54.3 (51.3-57.2) 57.8 (54.5-61.1)  Higher 56.6 (49.8-63.3) 41.6 (34.9-48.4) 23.0 (19.3-26.6) 42.9 (37.7-48.1) 45.1 (41.0-49.2) 

Residence 

 Urban 60.3 (55.5-65.2) 49.2 (45.3-53.1) 39.5 (36.5-42.4) 49.9 (46.9-52.9) 50.8 (46.9-54.7) 

 Rural 61.0 (55.0-67.0) 48.7 (45.5-51.9) 36.1 (33.8-38.4) 54.2 (50.2-58.2) 53.7 (50.2-57.2) Occupation *** *** *** *** *** 

 Not working 33.9 (27.6-40.3) 26.1 (21.6-30.7) 15.0 (12.5-17.4) 41.7 (37.3-46.1) 30.7 (26.1-35.3) 

 Professional/technical/managerial 67.8 (59.6-76.0) 44.7 (37.3-52.1) 34.5 (30.5-38.5) 42.5 (34.9-50.0) 38.8 (33.1-44.4) 

 Clerical -- -- -- -- 38.8 (29.6-47.9) -- -- 52.9 (39.8-65.9) 

 Sales and services 77.4 (69.6-85.3) 55.0 (47.4-62.6) 46.8 (42.4-51.1) 55.2 (46.6-63.9) 54.0 (49.0-59.1)  Skilled manual 77.1 (70.0-84.3) 66.1 (61.7-70.5) 54.0 (50.7-57.4) 60.5 (56.5-64.6) 65.0 (60.8-69.3) 

 Unskilled manual 76.0 (64.8-87.2) 51.8 (41.5-62.1) 52.7 (44.2-61.2) 70.7 (60.8-80.7) 71.4 (63.8-79.1) 

 Agriculture 75.6 (67.9-83.3) 58.8 (52.2-65.4) 37.3 (33.1-41.4) 58.4 (51.8-65.0) 51.8 (39.5-64.1) Household wealth quintile * * *** *** 

 Lowest 65.0 (58.3-71.7) 57.1 (51.9-62.2) 35.7 (31.6-39.8) 62.3 (56.4-68.1) 61.4 (55.8-67.0)  Second 59.9 (52.5-67.4) 44.6 (38.6-50.6) 39.8 (36.1-43.6) 56.1 (49.4-62.7) 53.5 (48.9-58.1)  Middle 59.2 (51.9-66.4) 50.7 (45.4-56.1) 39.5 (35.7-43.3) 53.2 (47.7-58.8) 55.3 (50.5-60.1)  Fourth 54.2 (45.8-62.7) 47.6 (41.2-54.1) 40.5 (36.1-44.9) 47.0 (42.0-52.1) 51.3 (45.3-57.2) 

 Highest 65.9 (58.9-72.8) 45.8 (39.2-52.5) 32.2 (28.4-36.0) 46.6 (42.2-51.1) 42.7 (36.3-49.2) Migration status - times slept away from home in last 12 months 

 None 62.5 (58.3-66.7) na na na na 51.7 (48.4-55.0) na na  1-4 51.1 (42.6-59.6) na na na na 55.4 (50.0-60.8) na na  5 or more 60.1 (47.0-73.2) na na na na 51.0 (45.4-56.6) na na Exposure to mass media * ** * ***  Does not read a newspaper at least once a week 60.9 (56.4-65.4) 51.1 (48.2-54.0) 37.5 (35.3-39.7) 54.7 (51.3-58.0) 58.4 (54.9-61.9) 

 Reads a newspaper at least once a week 59.8 (53.6-66.0) 44.7 (39.6-49.8) 31.2 (27.7-34.8) 49.0 (45.2-52.8) 48.3 (44.6-52.1) 

*** 

 Does not watch television at least once a week -- -- 51.6 (40.0-63.2) 35.9 (27.6-44.2) 68.7 (60.9-76.5) 56.8 (43.3-70.3) 

 Watches television at least once a week 60.5 (56.7-64.2) 48.9 (46.2-51.6) 37.7 (35.8-39.6) 50.8 (48.0-53.7) 51.6 (48.6-54.5) 

** 

 Does not listen to the radio at least once a week 60.4 (56.2-64.6) 52.6 (49.4-55.8) 37.5 (34.9-40.0) 55.7 (50.3-61.1) 53.2 (49.3-57.2) 

 Listens to the radio at least once a week 60.8 (55.2-66.4) 45.1 (41.2-49.0) 37.7 (35.3-40.2) 51.5 (48.7-54.4) 51.0 (47.5-54.5) 

** * ** 

 At least one form of media less than once per week 60.6 (56.5-64.7) 51.0 (48.3-53.7) 36.4 (34.3-38.5) 54.3 (51.1-57.4) 55.4 (52.3-58.6)  All three media at least once a week 60.5 (53.9-67.0) 42.7 (37.3-48.1) 33.6 (29.1-38.1) 48.8 (44.7-52.9) 48.6 (44.4-52.7) 

* 

 At least one form of media at least once a week 60.5 (56.7-64.2) 48.7 (46.0-51.4) 35.9 (33.9-37.8) 51.7 (49.0-54.4) 51.7 (48.7-54.6) 

 No media at least once a week -- -- 57.6 (45.0-70.2) 39.6 (27.0-52.2) 67.7 (56.1-79.4) 53.5 (32.4-74.6) 

Total age 15-49 60.6 (56.8-64.4) 49.0 (46.4-51.6) 37.6 (35.7-39.4) 52.3 (49.7-55.0) 51.6 (48.6-54.6) Age 50 to highest age na na 54.7 (47.5-62.0) 43.4 (39.1-47.7) 46.4 (41.1-51.7) na na 

Total age 15 to highest age 60.6 (56.8-64.4) 49.7 (47.3-52.1) 38.4 (36.6-40.2) 51.1 (48.6-53.6) 51.6 (48.6-54.6) 

Continued...

56
Appendix Table A1—Continued

Characteristics 

Uzbekistan 2002 Bangladesh 2007 India 2005/06 Maldives 20091 Nepal 2006 

Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** * *** * ***  15-24 years 12.8 (9.7-15.8) 63.2 (56.5-69.9) 19.2 (18.3-20.0) 47.3 (37.6-57.0) 16.7 (13.5-19.8)  25-34 years 26.6 (22.7-30.5) 55.6 (51.9-59.3) 36.1 (35.0-37.2) 51.2 (45.1-57.2) 33.0 (28.4-37.6)  35-49 years 33.6 (29.2-37.9) 62.3 (59.7-64.9) 43.8 (42.7-44.9) 47.9 (43.4-52.5) 44.8 (40.2-49.5)  50 years and over 26.8 (19.2-34.4) 59.4 (54.6-64.2) 45.0 (42.9-47.0) 38.5 (31.9-45.1) 48.7 (43.6-53.8) Marital status *** *** * *** 

 Never married 11.8 (8.3-15.3) na na 18.8 (18.0-19.6) na na 13.7 (10.6-16.8)  Currently married 29.5 (26.5-32.5) 60.1 (57.8-62.4) 40.4 (39.5-41.3) 48.2 (44.4-52.0) 37.6 (34.3-41.0) 

 Formerly married 33.3 (13.9-52.8) 59.6 (36.2-83.0) 48.6 (44.0-53.2) 64.9 (50.6-79.1) 42.1 (26.0-58.1) 

Education *** *** * *** 

 No education -- -- 73.4 (69.8-77.0) 50.1 (48.5-51.7) 50.4 (44.2-56.6) 50.5 (45.7-55.3)  Primary 17.5 (10.8-24.2) 63.9 (60.5-67.3) 43.1 (41.7-44.5) 53.6 (48.3-58.8) 38.4 (34.1-42.8) 

 Secondary 23.6 (20.7-26.5) 51.4 (47.3-55.5) 26.5 (25.8-27.3) 49.0 (42.4-55.6) 20.4 (16.6-24.3) 

 Higher 28.6 (23.1-34.2) 35.0 (29.3-40.6) 19.8 (18.5-21.1) 34.1 (21.2-46.9) 13.6 (9.2-17.9) 

Residence *** ** *** 

 Urban 31.7 (27.6-35.8) 54.3 (50.3-58.2) 28.7 (27.7-29.8) 48.5 (40.7-56.3) 28.0 (24.9-31.0) 

 Rural 19.0 (15.9-22.0) 61.8 (59.1-64.6) 35.0 (34.1-35.9) 49.5 (46.0-53.0) 30.7 (27.4-34.0) Occupation *** ** *** 

 Not working na na na na 9.6 (8.8-10.5) -- -- 11.8 (7.4-16.1)  Professional/technical/managerial na na na na 22.8 (20.9-24.7) 48.2 (39.6-56.8) 14.3 (9.9-18.7)  Clerical na na na na 27.3 (25.0-29.7) 40.8 (28.9-52.7) 37.9 (28.9-46.9) 

 Sales and services na na na na 33.1 (31.7-34.5) 37.5 (30.0-45.0) 28.8 (22.7-35.0)  Skilled manual na na na na 39.4 (38.3-40.5) 51.5 (45.3-57.8) 32.4 (26.6-38.2) 

 Unskilled manual na na na na na na -- -- 40.2 (34.6-45.8) 

 Agriculture na na na na 38.2 (36.9-39.5) 58.5 (51.7-65.3) 33.0 (28.9-37.2) 

Household wealth quintile *** *** *** 

 Lowest na na 70.9 (66.1-75.7) 42.9 (41.1-44.8) 56.9 (49.7-64.0) 45.1 (38.4-51.8) 

 Second na na 65.4 (60.9-70.0) 39.5 (38.0-40.9) 50.7 (44.3-57.0) 35.7 (31.4-40.0) 

 Middle na na 61.7 (57.1-66.3) 35.1 (33.9-36.3) 47.0 (41.5-52.6) 28.9 (25.0-32.8) 

 Fourth na na 56.9 (52.2-61.6) 29.1 (27.9-30.3) 42.7 (34.1-51.4) 22.6 (18.9-26.3) 

 Highest na na 46.4 (42.0-50.8) 21.7 (20.7-22.7) 50.4 (41.0-59.7) 24.4 (20.6-28.2) 

Migration status - times slept away from home in last 12 months *** *** 

 None 21.5 (18.9-24.0) na na 28.9 (27.9-29.9) na na na na  1-4 32.5 (24.0-40.9) na na 32.4 (31.3-33.4) na na na na  5 or more 42.6 (29.6-55.7) na na 36.4 (35.4-37.5) na na na na Exposure to mass media *** *** *** 

 Does not read a newspaper at least once a week na na 66.0 (63.3-68.6) 39.7 (38.7-40.7) 52.0 (47.5-56.6) 34.8 (31.8-37.8) 

 Reads a newspaper at least once a week na na 46.9 (43.0-50.8) 26.4 (25.7-27.2) 46.5 (41.4-51.5) 19.9 (17.0-22.8) 

*** *** 

 Does not watch television at least once a week na na 60.2 (56.3-64.2) 39.3 (38.1-40.4) 60.6 (40.9-80.2) 36.9 (33.5-40.3) 

 Watches television at least once a week na na 60.1 (57.4-62.7) 28.8 (28.1-29.6) 48.8 (45.1-52.5) 21.9 (19.2-24.6) 

*** *** 

 Does not listen to the radio at least once a week na na 59.2 (56.6-61.9) 33.9 (33.0-34.7) 50.6 (42.8-58.4) 39.2 (35.1-43.2) 

 Listens to the radio at least once a week na na 61.5 (58.0-65.1) 31.2 (30.3-32.1) 48.6 (44.8-52.5) 27.6 (25.0-30.2) 

** *** *** 

 At least one form of media less than once per week na na 61.3 (58.9-63.6) 34.9 (34.2-35.7) 51.1 (46.5-55.7) 33.5 (30.5-36.5)  All three media at least once a week na na 49.9 (43.0-56.9) 25.4 (24.3-26.4) 45.9 (40.4-51.4) 18.2 (15.6-20.8) 

* *** *** 

 At least one form of media at least once a week na na 59.1 (56.6-61.6) 30.4 (29.7-31.1) 48.8 (45.1-52.5) 27.6 (25.1-30.1) 

 No media at least once a week na na 64.4 (60.1-68.7) 42.1 (40.5-43.7) -- -- 42.7 (37.6-47.7) 

Total age 15-49 23.8 (21.4-26.2) 60.1 (57.8-62.4) 32.7 (32.0-33.4) 49.1 (45.5-52.8) 30.2 (27.4-33.0) Age 50 to highest age 26.8 (19.2-34.4) 59.4 (54.6-64.2) 45.0 (42.9-47.0) 38.5 (31.9-45.1) 48.7 (43.6-53.8) 

Total age 15 to highest age 24.1 (21.9-26.2) 60.0 (57.9-62.1) 33.5 (32.8-34.1) 47.0 (43.9-50.2) 32.5 (30.1-34.9) 

Continued...

57 
Appendix Table A1—Continued

Characteristics 

Timor-Leste 2009/10 Bolivia 2008 Dominican Republic 2007 

Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** *** ***  15-24 years 49.9 (46.9-52.9) 32.4 (29.6-35.3) 4.1 (3.4-4.7)  25-34 years 82.2 (79.5-84.8) 48.5 (45.3-51.6) 10.0 (8.7-11.3)  35-49 years 72.1 (69.2-75.0) 43.8 (40.8-46.7) 17.7 (16.4-19.0)  50 years and over na na 42.3 (38.6-46.0) 19.6 (17.7-21.5) Marital status *** *** ***  Never married 53.5 (50.8-56.2) 32.9 (30.3-35.5) 4.5 (3.9-5.2)  Currently married 76.0 (73.8-78.3) 45.7 (43.3-48.2) 12.1 (11.2-13.1)  Formerly married 76.1 (64.3-87.9) 57.0 (46.4-67.6) 20.9 (18.6-23.2) Education *** *** ***  No education 70.9 (67.1-74.6) 66.0 (45.1-86.9) 22.0 (18.8-25.2)  Primary 72.5 (69.4-75.5) 47.5 (44.6-50.4) 13.5 (12.4-14.6)  Secondary 60.8 (58.2-63.3) 36.9 (34.3-39.5) 7.0 (6.1-7.8)  Higher 60.6 (52.3-68.9) 38.6 (35.1-42.1) 5.5 (4.2-6.8) Residence * *** *  Urban 62.5 (58.9-66.2) 38.2 (35.7-40.6) 9.8 (8.9-10.6)  Rural 66.9 (64.8-69.0) 46.0 (43.1-48.9) 11.2 (10.3-12.0) Occupation *** ***  Not working 38.7 (33.3-44.1) 20.6 (16.9-24.4) na na  Professional/technical/managerial 72.8 (66.9-78.6) 43.6 (40.3-47.0) na na  Clerical -- -- 42.6 (33.1-52.1) na na  Sales and services 76.5 (71.7-81.4) 37.8 (31.7-44.0) na na  Skilled manual 80.4 (66.3-94.4) 43.5 (39.6-47.4) na na  Unskilled manual 71.1 (60.8-81.4) 36.1 (26.6-45.6) na na  Agriculture 67.7 (65.4-70.1) 49.3 (45.8-52.9) na na Household wealth quintile *** ***  Lowest 65.4 (61.6-69.1) 55.1 (51.1-59.1) 15.1 (13.9-16.3)  Second 67.5 (63.9-71.2) 40.4 (36.4-44.4) 12.1 (10.5-13.7)  Middle 67.5 (63.6-71.4) 41.1 (36.6-45.5) 8.6 (7.3-9.9)  Fourth 67.3 (63.7-70.8) 36.7 (32.8-40.6) 7.0 (5.7-8.2)  Highest 61.5 (57.7-65.4) 35.8 (32.2-39.3) 7.7 (6.3-9.1) Migration status - times slept away from home in last 12 months **  None na na na na 10.5 (9.8-11.3)  1-4 na na na na 8.5 (7.5-9.6)  5 or more na na na na 11.3 (9.5-13.1) Exposure to mass media ** ***  Does not read a newspaper at least once a week 66.2 (64.1-68.3) 43.5 (40.9-46.0) 11.8 (10.9-12.7)  Reads a newspaper at least once a week 63.9 (60.2-67.6) 38.4 (35.8-40.9) 8.6 (7.8-9.5) 

** *** *** 

 Does not watch television at least once a week 67.8 (65.3-70.2) 49.8 (46.2-53.5) 15.5 (13.1-17.9)  Watches television at least once a week 62.8 (60.0-65.6) 38.6 (36.5-40.8) 9.6 (9.0-10.3) 

 * 

 Does not listen to the radio at least once a week 64.6 (62.1-67.0) 38.3 (32.4-44.1) 11.9 (10.3-13.6)  Listens to the radio at least once a week 67.2 (64.5-69.9) 41.1 (39.1-43.1) 9.9 (9.2-10.7) 

 ** *** 

 At least one form of media less than once per week 66.1 (64.0-68.1) 43.2 (40.9-45.5) 11.8 (10.9-12.6)  All three media at least once a week 63.2 (58.0-68.4) 38.0 (35.3-40.8) 8.4 (7.4-9.3) 

 *** 

 At least one form of media at least once a week 64.9 (62.6-67.1) 40.9 (39.0-42.9) 10.0 (9.3-10.7)  No media at least once a week 67.0 (64.1-69.9) 36.7 (22.4-51.1) 16.2 (13.0-19.4) Total age 15-49 65.7 (63.9-67.6) 40.9 (39.0-42.8) 10.2 (9.5-10.8) Age 50 to highest age na na 42.3 (38.6-46.0) 19.6 (17.7-21.5) Total age 15 to highest age 65.7 (63.9-67.6) 41.1 (39.3-42.8) 11.3 (10.7-11.9) Note: While the analysis for age includes men 50 years and over, the analysis for all other variables is restricted to those age 15-49. -- indicates that an estimate is based on fewer than 25 unweighted cases and has been suppressed. CI: Confidence interval; na: Not available; * p<0.05; ** p<0.01; *** p<0.001 1The response rate for the men's survey in the 2009 Maldives DHS was inordinately low (interviews were completed with only 54 percent of the men who were eligible for interview). 

58 
Appendix Table A2. Correlates of current cigarette smoking among women age 15-49 in countries with >5% prevalence of smoking, 1999-2009

Characteristics 

Namibia 2006/07 Sierra Leone 2008 Jordan 2009 Moldova 2005 Turkey 2003 

Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** *** *** *** ***  15-24 years 3.0 (2.4-3.7) 2.1 (1.5-2.7) 3.9 (2.2-5.6) 7.4 (6.2-8.5) 23.7 (21.0-26.4) 

 25-34 years 5.5 (4.2-6.8) 7.6 (6.5-8.7) 6.8 (5.4-8.2) 8.9 (7.7-10.2) 31.9 (29.9-33.9)  35-49 years 8.7 (7.1-10.2) 8.3 (6.9-9.7) 11.6 (9.9-13.3) 5.8 (4.9-6.7) 25.7 (23.6-27.8) 

Marital status *** *** *** *** *** 

 Never married 3.3 (2.5-4.1) 1.1 (0.6-1.6) na na 5.8 (4.6-7.0) na na 

 Currently married 7.9 (6.5-9.3) 6.9 (6.0-7.7) 8.2 (7.2-9.1) 6.3 (5.5-7.1) 26.7 (25.2-28.1) 

 Formerly married 9.3 (6.0-12.6) 11.2 (8.0-14.3) 20.1 (13.5-26.8) 17.2 (14.4-20.0) 47.1 (39.6-54.6) Education * *** * *** *** 

 No education 7.4 (4.9-10.0) 7.0 (6.0-7.9) 8.7 (5.7-11.7) -- -- 16.7 (14.3-19.1) 

 Primary 4.0 (3.1-4.9) 6.2 (4.6-7.7) 9.3 (6.5-12.0) 14.4 (0.0-29.2) 23.2 (21.6-24.9) 

 Secondary 5.6 (4.5-6.7) 3.4 (2.3-4.4) 9.7 (8.4-11.0) 6.0 (5.2-6.7) 42.9 (39.6-46.3)  Higher 5.6 (2.7-8.4) 0.6 (0.0-1.6) 6.8 (4.9-8.6) 11.3 (9.8-12.8) 45.5 (40.3-50.7) Residence *** * *** *** ***  Urban 8.5 (7.0-10.1) 5.0 (4.2-5.9) 9.3 (8.2-10.5) 13.6 (12.3-14.8) 32.8 (31.0-34.7) 

 Rural 2.3 (1.8-2.8) 6.6 (5.7-7.5) 5.4 (4.3-6.5) 2.3 (1.5-3.1) 15.0 (12.6-17.3) Employed in the last 12 months *** *** *** 

 Yes 6.4 (5.3-7.6) 6.7 (5.9-7.6) na na 8.6 (7.6-9.6) 27.8 (25.4-30.2)  No 4.1 (3.3-4.8) 3.7 (2.5-4.8) na na 5.3 (4.4-6.3) 27.6 (26.0-29.2) 

Cash earnings (among those who worked) *** * *** *** 

 Yes 8.5 (6.9-10.1) 8.5 (6.7-10.3) na na 9.2 (8.1-10.3) 37.6 (34.4-40.8)  No 1.2 (0.6-1.9) 6.1 (5.2-7.1) na na 3.7 (1.6-5.8) 13.5 (11.4-15.6) 

Household wealth quintile *** * *** *** *** 

 Lowest 0.5 (0.2-0.9) 6.7 (5.2-8.2) 6.2 (4.8-7.5) 1.2 (0.4-1.9) 17.0 (14.3-19.8) 

 Second 2.0 (1.2-2.7) 6.6 (5.0-8.1) 6.1 (4.7-7.6) 2.4 (1.3-3.5) 21.5 (18.9-24.1) 

 Middle 3.1 (2.2-3.9) 6.3 (4.8-7.7) 7.5 (5.9-9.2) 3.1 (2.2-4.0) 25.2 (22.6-27.9)  Fourth 7.6 (5.7-9.6) 6.8 (5.4-8.2) 10.5 (8.0-13.0) 8.4 (7.0-9.9) 29.4 (26.8-31.9)  Highest 10.6 (8.2-12.9) 4.2 (3.2-5.3) 13.7 (10.0-17.3) 16.8 (15.0-18.7) 40.0 (37.2-42.7) 

Maternity status * *** *** *** 

 Pregnant 4.7 (2.2-7.2) 4.5 (2.6-6.5) 2.9 (1.5-4.4) 0.8 (0.0-2.0) 15.0 (11.5-18.5) 

 Breastfeeding (not pregnant) 3.5 (2.1-4.8) 6.0 (4.6-7.4) 5.4 (3.7-7.1) 2.3 (0.6-3.9) 19.6 (16.7-22.5)  Neither 5.7 (4.8-6.5) 6.2 (5.4-7.1) 10.5 (9.2-11.8) 7.5 (6.8-8.3) 29.7 (28.0-31.4) Exposure to mass media *** ** *** *** 

 Does not read a newspaper at least once a week 3.5 (2.9-4.1) 6.2 (5.5-7.0) na na 5.7 (4.9-6.5) 22.0 (20.5-23.5)  Reads a newspaper at least once a week 7.2 (5.8-8.7) 3.4 (1.8-4.9) na na 8.2 (7.3-9.2) 41.4 (38.7-44.0) 

*** * 

 Does not watch television at least once a week 3.0 (2.4-3.7) 6.2 (5.5-7.0) na na 5.1 (3.2-6.9) na na  Watches television at least once a week 8.2 (6.6-9.7) 4.5 (2.7-6.2) na na 7.3 (6.6-8.1) na na  Does not listen to the radio at least once a week 5.3 (3.7-6.9) 5.5 (4.7-6.4) na na 7.7 (6.4-9.0) na na 

 Listens to the radio at least once a week 5.3 (4.4-6.2) 6.6 (5.6-7.7) na na 7.0 (6.2-7.8) na na 

*** ** * 

 At least one form of media less than once per week 3.9 (3.3-4.6) 6.2 (5.5-6.9) na na 6.5 (5.7-7.3) na na 

 All three media at least once a week 8.6 (6.7-10.4) 2.0 (0.3-3.7) na na 7.9 (6.9-8.9) na na 

** * 

 At least one form of media at least once a week 5.6 (4.7-6.5) 6.6 (5.5-7.6) na na 7.3 (6.6-8.0) na na 

 No media at least once a week 3.1 (1.9-4.3) 5.6 (4.8-6.5) na na 3.3 (1.2-5.4) na na 

Continued... 

59 
Appendix Table A2—Continued

Characteristics 

Ukraine 2007 Kazakhstan 1999 Nepal 2006 Philippines 2008 Bolivia 2008 

Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** ** *** *** ***  15-24 years 16.9 (14.6-19.1) 8.8 (7.0-10.6) 3.3 (2.4-4.2) 3.5 (2.8-4.1) 7.3 (6.4-8.2) 

 25-34 years 17.4 (15.0-19.7) 10.4 (8.6-12.2) 12.8 (10.7-15.0) 4.9 (4.1-5.8) 8.5 (7.5-9.5) 

 35-49 years 12.4 (10.8-14.0) 6.9 (5.6-8.2) 33.7 (30.7-36.7) 6.8 (6.0-7.7) 10.3 (9.3-11.3) Marital status *** *** *** *** *** 

 Never married 17.2 (14.6-19.8) 8.9 (7.2-10.7) 1.0 (0.5-1.6) 3.8 (3.0-4.5) 9.2 (8.1-10.3) 

 Currently married 12.0 (10.5-13.5) 6.6 (5.6-7.6) 18.0 (16.4-19.5) 5.3 (4.7-5.9) 7.3 (6.6-8.0) 

 Formerly married 22.6 (19.4-25.8) 17.7 (14.4-20.9) 35.3 (28.8-41.9) 10.6 (8.1-13.2) 16.0 (13.5-18.4) Education *** *** ***  No education † † † (†) 25.7 (23.5-27.9) 11.8 (6.8-16.8) 8.4 (6.2-10.7) 

 Primary † † † (†) 7.7 (6.0-9.4) 7.6 (6.5-8.8) 6.3 (5.6-7.1) 

 Secondary 15.5 (13.6-17.4) 8.7 (7.6-9.8) 0.7 (0.4-1.0) 4.6 (4.0-5.3) 7.8 (6.9-8.7) 

 Higher 14.7 (13.0-16.3) 7.8 (6.0-9.5) 0.5 (0.0-1.2) 3.9 (3.2-4.6) 16.0 (14.1-17.8) 

Residence *** *** *** * *** 

 Urban 17.9 (16.1-19.7) 12.3 (10.7-14.0) 8.6 (7.4-9.7) 5.5 (4.7-6.3) 10.2 (9.2-11.1)  Rural 7.9 (6.3-9.5) 3.7 (2.9-4.4) 16.5 (14.8-18.1) 4.5 (3.8-5.1) 5.8 (4.9-6.6) 

Employed in the last 12 months *** ** *** *** ***  Yes 16.5 (14.8-18.1) 10.0 (8.7-11.2) 17.8 (16.2-19.4) 6.1 (5.3-6.8) 9.7 (8.9-10.5) 

 No 11.0 (9.4-12.7) 7.2 (6.0-8.4) 3.7 (2.8-4.6) 3.8 (3.2-4.3) 6.1 (5.3-7.0) 

Cash earnings (among those who worked) *** ***  Yes 16.5 (14.9-18.1) 10.7 (9.4-12.0) 19.1 (16.6-21.7) 6.0 (5.3-6.8) 10.6 (9.7-11.5)  No 13.6 (0.6-26.7) 4.1 (1.7-6.6) 17.2 (15.4-19.0) 6.2 (4.1-8.3) 5.8 (4.4-7.1) 

Household wealth quintile *** *** *** ***  Lowest 10.1 (7.6-12.7) 1.8 (0.7-2.8) 29.1 (26.4-31.9) 6.2 (5.0-7.4) 6.2 (5.0-7.4) 

 Second 8.7 (6.9-10.5) 3.2 (1.8-4.7) 18.0 (15.1-20.9) 5.6 (4.5-6.6) 5.3 (4.2-6.4) 

 Middle 17.1 (13.9-20.3) 4.5 (2.9-6.1) 15.6 (13.3-17.8) 5.2 (4.1-6.3) 6.7 (5.6-7.9) 

 Fourth 17.0 (14.4-19.6) 13.9 (11.4-16.5) 10.1 (8.4-11.9) 4.2 (3.3-5.1) 8.0 (6.8-9.1) 

 Highest 19.3 (16.1-22.5) 14.1 (12.0-16.1) 5.5 (4.5-6.4) 4.6 (3.7-5.6) 14.9 (13.3-16.4) Maternity status *** *** ** *** ***  Pregnant 3.9 (0.0-8.0) 2.1 (0.0-4.2) 9.7 (7.0-12.5) 2.3 (1.2-3.4) 4.1 (2.3-6.0) 

 Breastfeeding (not pregnant) 5.3 (1.4-9.2) 1.8 (0.4-3.2) 13.7 (11.5-15.8) 3.9 (2.8-5.0) 3.4 (2.6-4.2) 

 Neither 15.6 (14.2-17.0) 9.2 (8.3-10.2) 16.3 (14.7-17.8) 5.4 (4.8-6.0) 10.1 (9.3-10.9) Exposure to mass media * *** *** ***  Does not read a newspaper at least once a week 13.0 (11.1-14.8) 6.1 (4.7-7.6) 16.9 (15.4-18.4) 5.0 (4.5-5.6) 7.0 (6.3-7.7)

 Reads a newspaper at least once a week 15.7 (14.1-17.4) 10.0 (8.8-11.2) 0.6 (0.0-1.2) 5.1 (4.3-6.0) 11.6 (10.5-12.8) 

*** *** 

 Does not watch television at least once a week 18.2 (10.5-25.9) 6.3 (3.4-9.1) 20.0 (18.1-21.9) 5.6 (4.4-6.8) 6.0 (5.0-7.0)

 Watches television at least once a week 15.0 (13.6-16.4) 8.7 (7.8-9.7) 7.4 (6.0-8.9) 5.0 (4.4-5.5) 9.4 (8.6-10.2) 

  ** * * 

 Does not listen to the radio at least once a week 13.0 (11.1-14.8) 7.5 (6.4-8.5) 20.9 (18.7-23.0) 5.6 (4.7-6.5) 7.6 (6.3-8.8) 

 Listens to the radio at least once a week 16.1 (14.4-17.8) 10.3 (8.6-12.1) 11.5 (10.1-12.9) 4.8 (4.2-5.3) 8.9 (8.1-9.6) 

** *** *** *** 

 At least one form of media less than once per week 13.1 (11.6-14.7) 7.4 (6.4-8.4) 16.5 (15.0-18.0) 5.0 (4.4-5.5) 7.3 (6.6-7.9)  All three media at least once a week 16.7 (14.7-18.6) 11.5 (9.7-13.3) 0.5 (0.0-1.0) 5.2 (4.2-6.2) 11.8 (10.7-13.0) 

*** * ** 

 At least one form of media at least once a week 15.0 (13.6-16.4) 8.8 (7.8-9.7) 11.3 (10.0-12.7) 4.9 (4.4-5.4) 8.8 (8.1-9.5) 

 No media at least once a week 20.7 (8.9-32.4) 4.6 (1.4-7.9) 24.2 (22.1-26.3) 6.8 (4.9-8.7) 5.3 (3.5-7.1) 

Continued... 

60 
Appendix Table A2—Continued

Characteristics 

Dominican Republic 2007 Nicaragua 2001 Peru 2007/08 

Percent (95% CI) Percent (95% CI) Percent (95% CI) 

Age group *** ***  15-24 years 1.8 (1.4-2.2) 3.4 (2.8-4.0) 7.7 (6.7-8.8) 

 25-34 years 5.6 (4.8-6.4) 4.7 (3.7-5.6) 6.3 (5.2-7.3) 

 35-49 years 11.9 (10.9-12.8) 8.3 (7.3-9.4) 6.5 (5.5-7.5) 

Marital status *** *** *** 

 Never married 1.5 (1.0-2.0) 3.6 (2.6-4.6) 9.1 (8.0-10.2)  Currently married 7.5 (6.8-8.1) 5.3 (4.6-6.0) 4.7 (4.0-5.4)  Formerly married 9.1 (7.7-10.5) 7.3 (6.0-8.5) 11.3 (8.8-13.7) 

Education *** *** *** 

 No education 18.7 (14.4-23.0) 3.7 (2.7-4.8) 1.2 (0.4-2.0)  Primary 9.6 (8.8-10.4) 3.7 (3.1-4.4) 2.2 (1.6-2.8)  Secondary 4.0 (3.3-4.7) 6.3 (5.4-7.3) 6.1 (5.1-7.2) 

 Higher 2.8 (1.9-3.6) 9.4 (6.5-12.4) 12.3 (10.7-13.8) 

Residence *** *** 

 Urban 6.1 (5.5-6.7) 7.1 (6.3-7.9) 8.9 (7.9-9.8) 

 Rural 7.0 (6.3-7.7) 2.0 (1.6-2.5) 1.5 (1.1-1.9) Employed in the last 12 months *** ***  Yes 7.3 (6.8-7.9) 7.6 (6.7-8.4) 7.2 (6.4-8.0)  No 5.3 (4.8-5.9) 3.1 (2.5-3.8) 5.9 (4.7-7.0) Cash earnings (among those who worked) ***  Yes 7.4 (6.7-8.0) 7.9 (7.0-8.8) 8.7 (7.7-9.7)  No 7.5 (4.3-10.7) 5.0 (2.7-7.3) 1.9 (1.3-2.6) Household wealth quintile *** *** *** 

 Lowest 9.8 (8.6-10.9) 2.0 (1.4-2.7) 1.7 (0.9-2.6)  Second 8.2 (7.1-9.3) 3.1 (2.2-4.1) 1.8 (1.2-2.4) 

 Middle 5.8 (4.9-6.7) 4.1 (3.0-5.2) 3.2 (2.4-4.0) 

 Fourth 4.5 (3.8-5.2) 5.5 (4.3-6.7) 5.5 (4.3-6.7)  Highest 4.6 (3.6-5.7) 9.4 (7.8-11.0) 13.3 (11.7-15.0) 

Maternity status *** *** *** 

 Pregnant 2.7 (1.3-4.1) 1.3 (0.1-2.6) 1.1 (0.3-1.9) 

 Breastfeeding (not pregnant) 3.4 (2.3-4.5) 3.1 (2.0-4.2) 2.4 (1.5-3.4)  Neither 6.7 (6.2-7.2) 5.8 (5.3-6.4) 7.8 (7.0-8.7) Exposure to mass media *** *** *** 

 Does not read a newspaper at least once a week 7.9 (7.2-8.5) 4.4 (3.8-5.0) 5.2 (4.5-5.8) 

 Reads a newspaper at least once a week 4.9 (4.2-5.6) 6.3 (5.3-7.2) 10.5 (8.9-12.2) 

*** *** *** 

 Does not watch television at least once a week 9.4 (8.0-10.8) 2.5 (2.0-3.0) 3.4 (2.8-4.0)  Watches television at least once a week 6.0 (5.6-6.5) 6.4 (5.7-7.2) 8.7 (7.7-9.7) 

*** ** 

 Does not listen to the radio at least once a week 7.9 (6.9-9.0) 4.4 (3.2-5.6) 5.6 (4.5-6.7)  Listens to the radio at least once a week 6.0 (5.5-6.4) 5.4 (4.8-6.0) 7.5 (6.6-8.3) 

*** *** *** 

 At least one form of media less than once per week 7.7 (7.1-8.3) 4.4 (3.9-5.0) 5.7 (5.1-6.4)  All three media at least once a week 4.5 (3.9-5.2) 6.6 (5.6-7.7) 11.1 (9.2-13.0) 

** *** *** 

 At least one form of media at least once a week 6.2 (5.8-6.7) 5.4 (4.9-6.0) 7.5 (6.7-8.3)  No media at least once a week 9.1 (7.1-11.2) 2.3 (1.3-3.3) 2.8 (1.9-3.6) -- indicates that an estimate is based on fewer than 25 unweighted cases and has been suppressed. 

CI: Confidence interval na: Not available * p<0.05; ** p<0.01; *** p<0.001 

61 
62 

Appendix Table A3a. Percent distribution of men age 15-49 who currently smoke cigarettes by number of cigarettes 

smoked in the past 24 hours, 2002-10 

Region and country 

Year of 

survey 0 1-2 3-5 6-9 10+ 

Don't 

know/ 

missing Total 

Number of 

cigarette 

smokers 

Sub-Saharan Africa 

 Ethiopia 2005 6.0 14.9 28.1 17.8 31.0 2.3 100.0 645 

 Ghana 2008 5.1 31.5 36.9 16.0 5.8 4.7 100.0 289 

 Kenya 2008/09 0.9 17.7 35.8 15.5 29.4 0.8 100.0 600 

 Lesotho 2009 9.9 20.2 33.7 15.2 15.5 5.5 100.0 1,032 

 Liberia 2007 1.6 16.1 32.6 26.7 21.1 1.9 100.0 948 

 Madagascar 2008/09 0.6 17.4 42.1 16.4 22.0 1.4 100.0 2,188 

 Mozambique 2003 11.3 26.7 35.3 13.4 13.1 0.2 100.0 367 

 Namibia1 2006/07 4.1 16.7 36.3 15.8 26.0 1.1 100.0 891 

 Nigeria 2008 3.1 24.8 39.7 13.5 16.7 2.3 100.0 1,187 

 Rwanda 2005 12.4 32.2 32.4 10.2 12.5 0.3 100.0 608 

 Sierra Leone 2008 0.6 7.0 35.2 15.8 39.0 2.5 100.0 1,020 

 Swaziland 2006/07 8.2 23.5 35.3 14.0 16.7 2.2 100.0 576 

 Tanzania 2004/05 2.8 28.8 47.3 12.4 8.6 0.2 100.0 547 

 Uganda 2006 5.8 30.0 35.6 12.1 15.9 0.6 100.0 421 

 Zambia 2007 7.3 26.4 38.6 13.0 13.8 1.0 100.0 1,378 

 Zimbabwe 2005/06 5.2 18.5 32.9 14.6 26.7 2.1 100.0 1,438 

North Africa/West Asia/Europe 

 Albania 2008/09 0.4 1.1 3.5 2.0 92.8 0.2 100.0 1,318 

 Armenia 2005 0.0 0.5 3.3 2.7 91.7 1.8 100.0 867 

 Azerbaijan 2006 0.0 0.8 2.2 2.1 93.1 1.8 100.0 1,065 

 Egypt 2008 0.2 1.0 4.2 3.7 90.0 0.9 100.0 1,706 

 Moldova 2005 0.0 3.1 7.2 5.8 83.4 0.4 100.0 1,029 

 Ukraine 2007 0.0 1.0 4.4 4.5 89.3 0.7 100.0 1,692 

Central Asia 

 Uzbekistan 2002 7.3 9.2 18.8 12.8 40.1 11.8 100.0 574 

South and Southeast Asia 

 Bangladesh 2007 41.3 8.7 16.0 8.7 25.2 0.1 100.0 1,888 

 India2 2005/06 9.1 18.6 20.2 9.1 42.8 0.2 100.0 22,350 

 Maldives3 2009 2.0 6.8 13.3 9.7 66.2 1.9 100.0 664 

 Nepal 2006 3.2 26.0 29.3 12.2 29.4 0.0 100.0 1,112 

 Timor-Leste 2009/10 0.7 12.4 26.7 20.6 39.6 0.0 100.0 2,686 

Latin America/Caribbean 

 Dominican Republic 2007 8.0 17.0 24.7 11.2 37.9 1.2 100.0 2,517 

1

The Namibia survey asked about cigarettes smoked in the last 24 hours, including rolled cigarettes. 

2

The India survey asked about cigarettes or bidis smoked in the last 24 hours. 3

The response rate for the men's survey in the 2009 Maldives DHS was inordinately low (interviews were completed with only 54 percent of the men who were 

eligible for interview). 
63 

Appendix Table A3b. Percent distribution of women age 15-49 who currently smoke cigarettes by number of cigarettes 

smoked in the past 24 hours, 2001-10 

Region and country 

Year of 

survey 0 1-2 3-5 6-9 10+ 

Don't 

know/ 

missing Total 

Number of 

cigarette 

smokers 

Sub-Saharan Africa 

 Cameroon 2004 0.0 31.7 30.4 13.8 6.0 18.1 100.0 76 

 Congo Democratic Republic 2007 0.0 25.7 45.9 16.4 3.6 8.5 100.0 46 

 Ethiopia 2005 0.0 12.3 37.7 1.6 2.1 46.4 100.0 76 

 Guinea 2005 2.7 11.2 38.4 27.3 20.5 0.0 100.0 55 

 Kenya 2008/09 0.8 20.4 36.8 3.8 23.1 15.1 100.0 39 

 Liberia 2007 0.0 13.3 26.5 16.7 3.9 39.5 100.0 67 

 Madagascar 2008/09 0.0 28.6 26.9 14.3 17.4 12.8 100.0 131 

 Mozambique 2003 8.5 57.1 24.4 2.9 6.5 0.6 100.0 163 

 Namibia1 2006/07 3.9 16.1 32.8 15.2 31.2 0.9 100.0 515 

 Nigeria 2008 0.0 17.9 26.4 13.5 8.4 33.9 100.0 66 

 Rwanda 2005 8.3 46.3 26.9 2.7 7.5 8.4 100.0 34 

 Senegal 2005 0.0 15.2 18.1 12.6 14.0 40.1 100.0 31 

 Sierra Leone 2008 0.0 38.0 36.4 8.4 11.1 6.0 100.0 463 

 Swaziland 2006/07 0.0 27.4 21.4 14.0 20.2 16.9 100.0 59 

 Tanzania 2004/05 0.0 35.6 35.3 13.2 1.2 14.6 100.0 53 

 Uganda 2006 6.2 51.6 24.0 0.0 6.0 12.2 100.0 70 

 Zambia 2007 0.0 39.2 23.7 6.9 3.5 26.6 100.0 56 

 Zimbabwe 2005/06 0.0 18.3 14.2 3.1 18.8 45.6 100.0 28 

North Africa/West Asia/Europe 

 Albania 2008/09 3.5 10.5 15.5 8.2 61.0 1.3 100.0 293 

 Armenia 2005 0.0 14.4 20.9 4.3 54.9 5.4 100.0 64 

 Egypt 2008 0.0 2.4 16.6 0.8 44.7 35.4 100.0 39 

 Moldova 2005 0.0 16.4 26.1 14.1 40.0 3.4 100.0 625 

 Turkey 2003 2.7 19.7 23.3 12.5 41.7 0.1 100.0 2,220 

 Ukraine 2007 2.5 7.9 27.9 19.9 41.7 0.1 100.0 902 

Central Asia 

 Uzbekistan 2002 7.8 6.9 30.1 3.4 39.5 12.3 100.0 46 

South and Southeast Asia 

 Cambodia 2005 0.0 27.7 33.5 12.0 22.3 4.5 100.0 985 

 India2 2005/06 1.9 21.9 34.8 13.0 25.6 2.8 100.0 1,832 

 Indonesia 2007 2.5 34.2 29.2 15.5 14.4 4.1 100.0 807 

 Maldives 2009 7.2 13.3 35.2 10.0 17.3 17.0 100.0 167 

 Nepal 2006 1.6 19.8 40.3 17.7 20.5 0.0 100.0 1,681 

 Philippines 2008 3.2 26.8 31.7 8.5 25.0 4.9 100.0 666 

 Timor-Leste 2009/10 0.0 50.5 27.2 10.5 9.5 2.3 100.0 434 

Latin America/Caribbean 

 Bolivia 2008 57.7 27.9 9.2 1.7 2.4 1.1 100.0 1,447 

 Dominican Republic 2007 6.4 21.5 28.9 10.9 28.9 3.4 100.0 1,751 

 Haiti 2005/06 0.0 26.6 30.0 12.2 15.1 16.1 100.0 298 

 Honduras 2005/06 17.8 39.4 24.3 6.8 10.7 1.0 100.0 348 

 Nicaragua 2001 17.8 41.0 20.6 8.2 9.9 2.4 100.0 549 

 Peru 2004/08 61.8 23.5 7.9 2.4 2.9 1.4 100.0 1,157 

1

The Namibia survey asked about cigarettes smoked in the last 24 hours, including rolled cigarettes. 

2

The India survey asked about cigarettes or bidis smoked in the last 24 hours. 
64 

Appendix Table A4. Percentage of men who currently smoke cigarettes or use other tobacco products by age group, 

according to country and region, 2002-10 

Region and country 

Year of 

survey 

Percent 

using any 

tobacco (95% CI) 

Percent using 

manufactured 

cigarettes (95% CI) 

Percent 

using other 

smoked 

tobacco (95% CI) 

Percent 

using 

smokeless (95% CI) 

Sub-Saharan Africa 

 Ethiopia 2005 

 15-49 10.6 (9.3-11.9) 8.1 (7.0-9.3) 1.0 (0.5-1.5) 3.0 (2.3-3.7) 

 50-59 22.2 (18.2-26.2) 11.9 (8.3-15.6) 3.7 (1.6-5.8) 10.1 (7.2-13.1) 

 15-59 11.7 (10.4-12.9) 8.5 (7.4-9.6) 1.2 (0.7-1.8) 3.7 (3.0-4.4) 

 Ghana 2008 

 15-49 6.8 (5.9-7.6) 6.2 (5.4-7.0) 0.6 (0.3-0.8) 0.9 (0.6-1.3) 

 50-59 19.0 (15.1-22.8) 16.0 (12.5-19.6) 2.3 (0.9-3.8) 4.4 (2.3-6.5) 

 15-59 8.1 (7.2-9.0) 7.3 (6.5-8.2) 0.8 (0.5-1.1) 1.3 (0.9-1.7) 

 Kenya 2008/09 

 15-49 18.9 (16.5-21.2) 17.5 (15.2-19.8) 1.1 (0.4-1.8) 1.8 (1.2-2.4) 

 50-54 37.8 (29.2-46.4) 28.6 (20.7-36.6) 5.1 (1.1-9.1) 6.2 (1.3-11.0) 

 15-54 20.0 (17.7-22.3) 18.2 (16.0-20.4) 1.4 (0.7-2.1) 2.1 (1.3-2.8) 

 Lesotho 2009 

 15-49 34.5 (32.4-36.6) 34.5 (32.4-36.6) 5.7 (4.8-6.6) 1.3 (0.8-1.7) 

 50-59 30.8 (25.2-36.5) 30.8 (25.2-36.5) 4.5 (2.4-6.7) 2.6 (0.5-4.7) 

 15-59 34.1 (32.1-36.1) 34.1 (32.1-36.1) 5.6 (4.7-6.5) 1.4 (0.9-1.9) 

 Liberia1

 2007 

 15-49 16.2 (14.6-17.8) 15.2 (13.6-16.7) 0.8 (0.4-1.2) 2.3 (1.6-3.1) 

 Madagascar 2008/09 

 15-49 47.3 (45.6-49.0) 28.2 (26.7-29.7) 1.7 (1.3-2.1) 22.6 (20.9-24.3) 

 50-59 62.3 (58.5-66.2) 24.2 (21.0-27.5) 1.8 (0.9-2.8) 41.1 (37.1-45.2) 

 15-59 48.9 (47.3-50.6) 27.7 (26.3-29.2) 1.7 (1.4-2.1) 24.6 (23.0-26.3) 

 Malawi 2004 

 15-49 20.7 (18.6-22.7) 16.3 (14.5-18.1) 0.1 (0.0-0.2) 0.3 (0.2-0.5) 

 50-54 37.8 (29.4-46.1) 23.9 (16.6-31.3) 0.0 (--) 2.5 (0.4-4.6) 

 15-54 21.4 (19.4-23.4) 16.6 (14.8-18.4) 0.1 (0.0-0.2) 0.4 (0.2-0.6) 

 Mozambique 2003 

 15-49 24.3 (21.9-26.6) 14.2 (12.4-16.0) 0.2 (0.0-0.6) na na 

 50-64 44.7 (38.5-50.9) 13.0 (9.0-17.0) 0.0 (--) na na 

 15-64 27.2 (24.6-29.7) 14.0 (12.3-15.7) 0.2 (0.0-0.5) na na 

 Namibia1

 2006/07 

 15-49 23.7 (21.8-25.5) 20.9 (19.2-22.7) 0.9 (0.6-1.2) 1.8 (1.3-2.4) 

 Nigeria 2008 

 15-49 11.5 (10.7-12.3) 8.9 (8.2-9.6) 0.7 (0.5-0.9) 3.2 (2.7-3.6) 

 50-59 17.8 (15.6-20.0) 9.6 (7.9-11.2) 0.5 (0.2-0.8) 8.8 (7.3-10.4) 

 15-59 12.2 (11.4-13.0) 9.0 (8.3-9.6) 0.7 (0.5-0.9) 3.8 (3.3-4.2) 

 Rwanda 2005 

 15-49 19.4 (18.0-20.8) 13.9 (12.6-15.1) 3.4 (2.8-4.1) na na 

 50-59 47.2 (42.7-51.6) 18.3 (14.6-22.1) 20.9 (17.2-24.6) na na 

 15-59 21.7 (20.4-23.0) 14.2 (13.1-15.4) 4.9 (4.2-5.6) na na 

 Sierra Leone 2008 

 15-49 37.4 (35.1-39.7) 36.7 (34.5-38.9) 0.4 (0.1-0.7) 1.3 (0.8-1.9) 

 50-59 44.6 (38.2-51.1) 41.9 (35.5-48.2) 1.4 (0.0-3.1) 3.2 (1.5-4.9) 

 15-59 38.1 (36.0-40.3) 37.2 (35.1-39.3) 0.5 (0.2-0.8) 1.5 (1.0-2.0) 

 Swaziland1

 2006/07 

 15-49 16.7 (15.2-18.1) 13.8 (12.5-15.2) 1.4 (0.9-1.9) 2.8 (2.3-3.4) 

 Tanzania1

 2004/05 

 15-49 22.0 (19.8-24.3) 21.0 (18.8-23.3) 0.4 (0.1-0.6) na na 

 Uganda 2006 

 15-49 21.7 (19.4-24.0) 18.1 (15.9-20.2) 1.8 (1.1-2.6) 3.9 (3.1-4.8) 

 50-54 40.5 (31.1-49.8) 31.2 (22.6-39.9) 6.6 (2.4-10.9) 7.0 (2.3-11.7) 

 15-54 22.6 (20.4-24.8) 18.7 (16.6-20.8) 2.1 (1.3-2.8) 4.1 (3.1-5.0) 

 Zambia 2007 

 15-49 23.6 (22.0-25.1) 23.2 (21.7-24.7) 1.2 (0.8-1.6) 0.2 (0.1-0.4) 

 50-59 33.0 (28.3-37.8) 31.7 (27.0-36.4) 1.6 (0.5-2.7) 1.0 (0.2-1.9) 

 15-59 24.3 (22.8-25.8) 23.9 (22.4-25.4) 1.2 (0.8-1.6) 0.3 (0.2-0.4) 

 Zimbabwe 2005/06 

 15-49 22.8 (21.5-24.1) 21.3 (20.0-22.6) 3.0 (2.5-3.5) 1.9 (1.6-2.3) 

 50-54 43.5 (37.6-49.5) 40.0 (34.3-45.6) 5.4 (2.9-7.8) 7.1 (4.0-10.2) 

 15-54 23.7 (22.4-25.0) 22.1 (20.8-23.4) 3.1 (2.6-3.6) 2.1 (1.8-2.5) 

Continued... 
65 

Appendix Table A4—Continued 

Region and country 

Year of 

survey 

Percent 

using any 

tobacco (95% CI) 

Percent using 

manufactured 

cigarettes (95% CI) 

Percent 

using other 

smoked 

tobacco (95% CI) 

Percent 

using 

smokeless (95% CI) 

North Africa/West Asia/Europe

 Albania1 2008/09 

 15-49 42.5 (40.4-44.6) 42.5 (40.4-44.6) 2.1 (1.2-2.9) na na 

 Armenia1 2005 

 15-49 60.6 (56.9-64.4) 60.6 (56.8-64.4) 0.9 (0.0-2.1) 1.8 (0.9-2.8) 

 Azerbaijan 2006 

 15-49 49.1 (46.5-51.7) 49.0 (46.4-51.6) 0.5 (0.1-0.9) 0.3 (0.1-0.5) 

 50-59 54.7 (47.5-62.0) 54.7 (47.5-62.0) 0.0 (--) 0.0 (--) 

 15-59 49.8 (47.4-52.2) 49.7 (47.3-52.1) 0.4 (0.1-0.8) 0.2 (0.1-0.4) 

 Egypt 2008 

 15-49 42.6 (40.7-44.5) 37.6 (35.7-39.4) 8.4 (7.4-9.4) 0.2 (0.1-0.4) 

 50-59 52.5 (48.2-56.7) 43.4 (39.1-47.7) 12.2 (9.4-15.0) 0.2 (0.0-0.4) 

 15-59 44.0 (42.2-45.8) 38.4 (36.6-40.2) 8.9 (8.0-9.9) 0.2 (0.1-0.4) 

 Moldova 2005 

 15-49 52.3 (49.7-55.0) 52.3 (49.7-55.0) 0.1 (0.0-0.2) 0.1 (0.0-0.3) 

 50-59 46.4 (41.1-51.7) 46.4 (41.1-51.7) 0.1 (0.0-0.3) 0.1 (0.0-0.4) 

 15-59 51.1 (48.6-53.6) 51.1 (48.6-53.6) 0.1 (0.0-0.2) 0.1 (0.0-0.2) 

 Ukraine1

 2007 

 15-49 52.2 (49.3-55.2) 51.6 (48.6-54.6) 3.6 (2.8-4.4) 0.3 (0.1-0.4) 

Central Asia 

 Uzbekistan2

 2002 

 15-49 51.2 (48.0-54.4) 23.8 (21.4-26.2) na na 31.8 (28.5-35.0) 

 50-59 48.4 (38.9-57.8) 26.8 (19.2-34.4) na na 23.3 (16.2-30.5) 

 15-59 51.0 (47.9-54.0) 24.1 (21.9-26.2) na na 31.1 (28.0-34.1) 

South and Southeast Asia

 Bangladesh3

 2007 

 15-49 69.3 (67.2-71.5) 60.1 (57.8-62.4) 0.0 (--) 19.8 (17.6-21.9) 

 50-54 76.4 (72.4-80.4) 59.4 (54.6-64.2) 0.0 (--) 30.7 (25.9-35.4) 

 15-54 70.3 (68.4-72.3) 60.0 (57.9-62.1) 0.0 (--) 21.4 (19.2-23.5) 

 India3

 2005/06 

 15-49 57.0 (56.3-57.7) 32.7 (32.0-33.4) 0.6 (0.5-0.8) 36.9 (36.1-37.7) 

 50-54 67.0 (65.1-68.8) 45.0 (42.9-47.0) 1.3 (0.8-1.8) 34.5 (32.4-36.6) 

 15-54 57.6 (56.9-58.3) 33.5 (32.8-34.1) 0.7 (0.5-0.8) 36.7 (35.9-37.5) 

 Maldives4

 2009 

 15-49 53.0 (49.2-56.9) 49.1 (45.5-52.8) 0.3 (0.0-0.6) 6.0 (4.6-7.4) 

 50-64 55.2 (48.7-61.7) 38.5 (31.9-45.1) 1.9 (0.3-3.6) 18.7 (13.8-23.5) 

 15-64 53.5 (50.2-56.8) 47.0 (43.9-50.2) 0.7 (0.2-1.1) 8.5 (7.0-9.9) 

 Nepal 2006 

 15-49 53.4 (51.2-55.6) 30.2 (27.4-33.0) 1.4 (0.8-2.0) 36.2 (34.3-38.2) 

 50-59 78.4 (73.9-82.8) 48.7 (43.6-53.8) 4.2 (2.0-6.4) 45.4 (39.0-51.8) 

 15-59 56.5 (54.5-58.5) 32.5 (30.1-34.9) 1.7 (1.1-2.4) 37.4 (35.3-39.4) 

 Timor-Leste1

 2009/10 

 15-49 69.5 (67.7-71.3) 65.7 (63.9-67.6) 23.2 (21.5-24.9) 2.5 (1.8-3.1) 

Latin America/Caribbean

 Bolivia 2008 

 15-49 na na 40.9 (39.0-42.8) na na na na 

 50-64 na na 42.3 (38.6-46.0) na na na na 

 15-64 na na 41.1 (39.3-42.8) na na na na 

 Dominican Republic 2007 

 15-49 11.7 (10.9-12.4) 10.2 (9.5-10.8) 0.1 (0.0-0.1) 1.9 (1.6-2.2) 

 50-59 23.1 (21.0-25.2) 19.6 (17.7-21.5) 0.5 (0.3-0.8) 4.6 (3.8-5.5) 

 15-59 13.0 (12.3-13.7) 11.3 (10.7-11.9) 0.1 (0.1-0.2) 2.2 (1.9-2.5) 

(--) indicates that no respondents used that form of tobacco and therefore confidence intervals are not estimated. 

na: Not available 

1

Only men 15-49 were interviewed. 

2

The Uzbekistan survey only assessed current smoking status if respondents ever smoked at least 100 cigarettes in their entire life. 3

The Bangladesh and India surveys asked about smoking cigarettes or bidis. 

4

The response rate for the men's survey in the 2009 Maldives DHS was inordinately low (interviews were completed with only 54 percent of the men who were 

eligible for interview).