DHS Analytical Studies No. 53 

An Inventory of Alcohol-Related Questions in the 

Demographic and Health Surveys and an Analysis of 

Alcohol Use and Unsafe Sex in Sub-Saharan Africa 

Lindsay Mallick 

Shireen Assaf 

ICF International 

Rockville, Maryland, USA 

September 2015 

Corresponding author: Lindsay Mallick, International Health and Development, ICF International, 530 

Gaither Road, Suite 500, Rockville, MD 20850, USA; phone: +1 301-572-0211; fax: +1 301–572-0950; 

email: Lindsay.Mallick@icfi.com 
Acknowledgment: The authors are grateful for the comments provided by Sarah Woolf-King and Kia 

Reinis on an earlier version of the report. The authors thank Elizabeth Britton for a thorough and rapid 

search of questions in all surveys and Tom Pullum for developing Stata code to extract data on alcohol in 

DHS surveys. The authors would also like to thank Bryant Robey and Sidney Moore for editing the report 

and Natalie La Roche for formatting it. 

Editors: Bryant Robey and Sidney Moore 

Document Production: Natalie La Roche 

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

Development (USAID) through The DHS Program (#AIDOAA-C-13-00095). The views expressed are 

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

The DHS Program assists countries worldwide in the collection and use of data to monitor and evaluate 

population, health, and nutrition programs. For additional information about The DHS Program contact: 

DHS Program, ICF International, 530 Gaither Road, Suite 500, Rockville, MD 20850, USA. Phone: +1 

301-407-6500; fax: +1 301-407-6501; email: reports@dhsprogram.com; Internet: www.dhsprogram.com. 

Recommended citation: 

Mallick, Lindsay and Shireen Assaf. 2015. An Inventory of Alcohol-Related Questions in the Demographic 

and Health Surveys and an Analysis of Alcohol Use and Unsafe Sex in Sub-Saharan Africa. DHS Analytical 

Studies No. 53. Rockville, Maryland, USA: ICF International.
iii 

Contents 

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

Figures ......................................................................................................................................................... v

Abstract ........................................................................................................................................................ ix

Executive Summary ..................................................................................................................................... xi

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

1.1. Measuring Global Variations in Alcohol Use ........................................................................... 2

1.2. Prevalence of Alcohol Consumption across the World ............................................................ 3

1.3. The Link between Alcohol and Risky Sexual Behaviors in Sub-Saharan Africa ..................... 3

2. Data and Methods ..................................................................................................................................... 7

2.1. Inventory of Alcohol-Use Questions in DHS Surveys ............................................................. 7

2.2. Prevalence of Ever Consuming Alcohol ................................................................................... 9

2.3. Regression Analysis of Unsafe Sex in Sub-Saharan Africa ...................................................... 9

3. Results ..................................................................................................................................................... 13

3.1. Inventory of Alcohol-related Questions in DHS Surveys ....................................................... 13

3.2. Prevalence of Ever Having Consumed Alcohol ..................................................................... 18

3.3. Alcohol Use and Unsafe Sex in Sub-Saharan Africa .............................................................. 21

4. Discussion ............................................................................................................................................... 31

4.1. Review of Findings ................................................................................................................. 31

4.2. Limitations .............................................................................................................................. 33

4.3. Considerations for Future Research ........................................................................................ 35

5. Conclusion .............................................................................................................................................. 37

References ................................................................................................................................................... 39

v 

Tables 

Table 1. Characteristics of DHS surveys that include questions on alcohol consumption, 

1987-2014 ........................................................................................................................... 8 

Table 2. HIV prevalence among men and women age 15-49 in sub-Saharan Africa, 

DHS surveys 2001-2014 ..................................................................................................... 9 

Table 3. DHS surveys that include questions related to alcohol consumption (ever, current, 

recent, typical), 1987-2014 ............................................................................................... 13 

Table 4. DHS surveys that include questions related to frequency or quantity of alcohol 

consumption, 1987-2014 .................................................................................................. 15 

Table 5. DHS surveys that include questions related to heavy alcohol consumption, 

1987-2014 ......................................................................................................................... 16 

Table 6. Questions on alcohol consumption included in DHS surveys by type of response 

elicited (yes/no, numerical, categorical) ........................................................................... 18 

Table 7. Alcohol consumption among men and women age 15-49 in Lesotho, Namibia, 

Swaziland and Zambia, DHS surveys 2006-2014 ............................................................ 22 

Table 8. Variables used in the regression analyses for men or women age 15-49 who have 

had sexual intercourse in the past 12 months, DHS surveys in sub-Saharan Africa, 

2001-2014 ......................................................................................................................... 23 

Table 9. Variables used in the regression analysis for men or women age 15-49 who have had 

sexual intercourse in the past 12 months and have ever consumed alcohol or currently 

drink, DHS surveys in sub-Saharan Africa, 2006-2014 .................................................... 25 

Table 10. Unadjusted (UA) and adjusted (AD) logistic regressions of unsafe sex for men and 

women age 15-49 who had intercourse in the past 12 months, DHS surveys in subSaharan Africa, 2001-2014 ............................................................................................... 26 

Table 11. Unadjusted (UA) and adjusted (AD) logistic regressions of unsafe sex for men and 

women age 15-49 who have ever consumed alcohol or currently drink and have had 

sexual intercourse in the past 12 months, DHS surveys in sub-Saharan Africa, 

2006-2014 ......................................................................................................................... 28 

Table 12. AUDIT-C Questionnaire and Scoring .............................................................................. 36 

Figures 

Figure 1. Percent of males and females who have ever had an alcoholic drink, 

sub-Saharan Africa ........................................................................................................... 19 

Figure 2. Percent of males and females who have ever had an alcoholic drink, 

Asia and Europe ................................................................................................................ 20 

Figure 3. Percent of males and females who have ever had an alcoholic drink, 

Latin America ................................................................................................................... 20 

Figure 4. Percentage HIV positive, percentage who had unsafe sex with last sex partner, 

and percentage who consumed alcohol at last sex, DHS surveys in 

sub-Saharan Africa, 2001-2014 ........................................................................................ 24 

vii 

Preface 

The Demographic and Health Surveys (DHS) Program is one of the principal sources of international data 

on fertility, family planning, maternal and child health, nutrition, mortality, environmental health, 

HIV/AIDS, malaria, and provision of health services. 

One of the objectives of The DHS Program is to analyze DHS data and provide findings that will be useful 

to policymakers and program managers in low- and middle-income countries. DHS Analytical Studies serve 

this objective by providing in-depth research on a wide range of topics, typically including several countries 

and applying multivariate statistical tools and models. These reports are also intended to illustrate research 

methods and applications of DHS data that may build the capacity of other researchers. 

The topics in the DHS Analytical Studies series are selected by The DHS Program in consultation with the 

U.S. Agency for International Development. 

It is hoped that the DHS Analytical Studies will be useful to researchers, policymakers, and survey 

specialists, particularly those engaged in work in low- and middle-income countries. 

Sunita Kishor 

Director, The DHS Program 

ix 

Abstract 

This report provides an overview of DHS survey questions related to alcohol consumption and an analysis 

of outcomes from these questions in DHS surveys. It first examines the questions on alcohol use and the 

response categories in all surveys that included questions about ever, typical, or current alcohol 

consumption. The inventory found that alcohol questions were included in 65 surveys in 42 developing 

countries between 1987 and 2014, and 19 different questions related to alcohol consumption were 

identified. The most common question asked if the respondent had ever drunk alcohol. Responses to this 

question were used to calculate the prevalence of ever-drinking in 36 surveys. Prevalence varied 

substantially within and across regions and between men and women. The study then uses multivariable 

logistic regression to examine the association between alcohol use and unsafe sex in eight countries in subSaharan Africa known to have high HIV prevalence. The regression analysis of the global association 

between self-reported drinking status and unsafe sex was not found to be significant except among men in 

Zambia, where the odds of engaging in unsafe sex for a current drinker were lower than for a non-drinker 

(opposite the expected outcome). At the event level, alcohol consumption at last sex was an inconsistent 

predictor of unsafe sex. For both men and women, the strongest predictor of engaging in unsafe sex was 

age of respondent—higher odds for those 15-24 compared with those 35 and older. For women, lifetime 

number of sexual partners also strongly predicted unsafe sex. The authors suggest using validated scales to 

assess harmful drinking. 

KEY WORDS: alcohol, heavy drinking, harmful drinking, risky sexual behavior, unsafe sex, condom, 

event-level study, sub-Saharan Africa 

xi 

Executive Summary 

Introduction 

The consumption of alcohol in various forms is—and has historically been—common in many countries. 

Levels of alcohol use, along with commercial production and distribution of alcohol, are rising in low- and 

middle-income countries, as their economies develop. The increase in alcohol consumption has many 

health-related consequences. Alcohol use is among the top three leading risk factors for disease burden, just 

behind high blood pressure and tobacco use, and contributes to over 200 types of diseases. There are also 

strong associations between alcohol use and some infectious diseases, including HIV/AIDS. Some research 

studies and review articles have found a relationship between alcohol use and risky sexual behavior or other 

outcomes related to HIV/AIDS, although other studies have found no relationship. 

This report reviews survey questions and data related to alcohol use in countries that have conducted 

Demographic and Health Surveys (DHS). The report has two main objectives: The first is to present an 

inventory of the alcohol-related questions included in DHS surveys and to provide an overview of the 

questions and response options. The second objective is to present examples of analyses that can be 

conducted with existing DHS data on alcohol use. The examples include 1) calculating the prevalence of 

ever-drinking and 2) examining alcohol use as a predictor of unsafe sex. The report presents results from 

logistic regression analyses of data from selected DHS surveys and AIS surveys (AIDS Indicator Surveys) 

carried out in sub-Saharan countries with high HIV prevalence. The analyses examine the association 

between alcohol use and unsafe sex, which is defined in this report as sex with a non-cohabitating partner 

without the use of a condom at last intercourse. 

Methods 

For the inventory of alcohol-related questions, The DHS Program Survey Search tool populated a list of all 

DHS surveys that included questions on alcohol use. The list was then narrowed to include only questions 

that pertained directly to respondent’s ever, current, or typical alcohol use, reducing the list to 65 surveys, 

which were included in the inventory. Prevalence of ever-drinking was calculated only using surveys that 

asked all adults if they had ever consumed alcohol. For analysis of the relationship between alcohol 

consumption and health behavior (in selected sub-Saharan countries with high HIV prevalence), logistic 

regressions were performed on DHS and AIS data using alcohol-related factors as the main independent 

variables and unsafe sex as the dependent variable, or outcome. The sub-Saharan countries analyzed 

included Kenya (men and women), Lesotho (only men), Mozambique (only women), Namibia (men and 

women), Swaziland (men and women), Uganda (only women), Zambia (men and women), and Zimbabwe 

(men and women). 

Results 

Among the 65 surveys in the inventory, the authors found 19 different non-comparable questions on 

alcohol. The most common question was about ever having had an alcoholic drink. Using this question, the 

study assessed the prevalence of ever-drinking, which was found to vary greatly across countries and 

regions. The highest prevalence in DHS surveys was among men in the Dominican Republic 2002 survey 

(92 percent), while the lowest prevalence was among women in the Haiti 2000 survey, the India 2005-06 

survey, and the Malawi 2000 survey (approximately two percent each). Within countries, there were 

substantial differences between men and women in the percentage ever-drinking. The largest differential 

was in the Guyana 2009 survey, a difference of 43 percentage points between men and women. The smallest 

difference, 15 percentage points, was in the Ukraine 2007 survey.
xii 

The logistic regression analysis conducted on selected sub-Saharan countries found that drinking status was 

not a significant predictor of risky sexual behavior, except among men in Zambia, where being a current 

drinker had lower odds of engaging in unsafe sex as opposed to being a non-drinker. In some countries, 

drinking at last sex was a significant predictor of unsafe sex; this was the case for men in Lesotho and 

Swaziland, men and women in Zambia, and women in Uganda. Among men and women, however, in all 

countries studied the strongest predictor of unsafe sex was age of respondent (higher for those 15-24 

compared with those 35 or older). Among women, lifetime number of sexual partners was also a strong 

predictor of unsafe sex. 

Discussion and Recommendations 

The inventory of alcohol-related questions revealed substantial variation across surveys in both the types 

of questions asked and the response options. Even similar questions showed small variations in wording 

that make comparison of results across countries difficult. Across all regions and countries, a higher 

percentage of men compared with women reported ever consuming alcohol in their lifetime. The size of 

the male-female gap in ever-drinking differed substantially among countries. 

The regression analysis found that men surveyed in the sub-Saharan countries studied drink more than 

women, as other studies also have shown. This was true for general alcohol-drinking status (drinks 

currently/ever/or not), frequency of alcohol consumption, and drinking at last sex. An association between 

alcohol consumption at last sex and risky sexual behavior was found in Zambia for both men and women, 

in Lesotho men, Swaziland men, and Ugandan women. The pathways and effects of alcohol on risky sexual 

behavior appear generally to differ between men and women, although there were variations in the results 

by both gender and country. 

The variation in alcohol-related questions and responses, as well as the inconsistent findings on drinking 

status as a predictor of unsafe sex, suggests that a validated scale to assess alcohol use could yield a more 

consistent, comparable measure. Expert research in the field has supported the use of validated scales, such 

as AUDIT-C, developed by the World Health Organization (WHO). Adopting a standardized set of 

questions would allow researchers to monitor alcohol consumption and to make multi-country comparisons, 

which could inform policy decisions and focus interventions where needed. With the wide ranging 

consequences of heavy drinking for people’s health, including risky sexual behavior, and increasing alcohol 

consumption in developing countries, there is a global responsibility to monitor alcohol consumption and 

harmful use of alcohol worldwide. 
1 

1. Introduction 

The consumption of alcohol in various forms is—and has historically been—common in many countries 

and cultures around the world (McGovern 2009); however, wherever alcohol is consumed there are 

associated health problems. Although many people abstain from drinking alcohol, it remains a major 

contributing factor to international morbidity and mortality (Rehm, Mathers, et al. 2009). The latest global 

status report on alcohol and health by the World Health Organization (WHO) found that, worldwide, six 

percent of all deaths and five percent of the burden of disease and injury are attributable to alcohol use; it 

is among the top three leading risk factors for disease burden, just behind high blood pressure and tobacco 

use, including secondhand smoke (WHO 2014). Alcohol use contributes to over 200 types of diseases and 

injuries, including cancer, cardiovascular disease, liver cirrhosis, motor vehicle accidents, and epilepsy 

(Hahn, Woolf-King, and Muyindike 2011; Lim et al. 2013; Rehm, Mathers, et al. 2009; WHO 2014). 

Studies have also found associations between alcohol and some infectious diseases, such as HIV/AIDS and 

tuberculosis (Baliunas et al. 2010; Hahn, Woolf-King, and Muyindike 2011; Lönnroth et al. 2008; Rehm, 

Samokhvalov, et al. 2009). Additionally, alcohol use causes indirect harm to others, through injury, 

homicide, abuse, neglect, and fetal alcohol syndrome (WHO 2014). While light and moderate alcohol 

consumption can have some health benefits for individuals, such as reduced occurrence of cardiovascular 

disease (Rehm, Mathers, et al. 2009; WHO 2014), it is clear that heavy alcohol use has consequences that 

can lead to health-related, psychosocial, legal, and economic problems (Bush et al. 1998; Casswell, You, 

and Huckle 2011). 

Several studies have found that alcohol use in low- and middle-income countries (LMICs) is rising, along 

with economic development and increased production and distribution of commercially produced alcohol 

(Obot 2006; Odejide and Ibadan 2006; Peltzer and Ramlagan 2009; Rehm, Mathers, et al. 2009). However, 

few studies have examined the consequences of increasing alcohol use, particularly in sub-Saharan Africa 

(Babor 2010; Obot 2006). Currently, there is little information available on harmful drinking patterns in 

low-income countries (Clausen et al. 2009). Survey data on alcohol consumption could be used to identify 

specific drinking customs that lead to health and/or social problems (Greenfield et al. 2006; Stockwell et 

al. 2004). Additionally, survey data could provide insight in areas where official statistics on alcohol 

consumption are not collected. It is important to ensure that survey data accurately reflect alcohol 

consumption patterns and adequately describe the associations between alcohol use and health outcomes. 

This report seeks to provide insight on questions related to alcohol use in the DHS questionnaire and to 

provide examples of how to examine associations between alcohol consumption and various outcomes 

measured by DHS surveys. The report has two main objectives. The first is to examine how questions 

related to alcohol use are included in DHS surveys in LMICs in regions worldwide, with an overview of 

the questions asked and the response options. The second objective is to provide examples of how alcoholrelated questions in the DHS can be used in analytical studies. 

Two analyses are carried out to meet these objectives. The first is a calculation of the prevalence of ever 

having consumed alcohol, using 36 DHS surveys. The second is an analysis that predicts risky sexual 

behavior, specifically unsafe sex, which is defined in this report as sex with a non-marital, non-cohabitating 

partner without the use of a condom at last intercourse. This analysis uses data from several DHS surveys 

carried out in countries with high HIV prevalence in sub-Saharan Africa; therefore, the focus of this analysis 

will be on this region. Unsafe sex was selected for investigation because of the link found by several studies 

between alcohol consumption, several risky sexual behavior outcomes, and HIV infection (Dimbuene, 

Emina, and Sankoh 2014; Fisher, Bang, and Kapiga 2007; Kalichman et al. 2007; Woolf-King and Maisto 

2011; Woolf-King et al. 2013). Additionally, the DHS questionnaire used in most countries contains a 

specific question on alcohol use at last sex; therefore, analysis of the data can establish a direct link between 

alcohol use and the behavioral outcome of interest. The authors conclude with technical guidance on the 
2 

use of alcohol-related questions in future DHS surveys. The technical guidance is designed to promote the 

use of a more quantifiable and standardized measure of alcohol consumption to produce more meaningful 

results from research on alcohol consumption and risky sexual behavior. 

1.1. Measuring Global Variations in Alcohol Use 

The point at which alcohol use becomes harmful has been defined in various contexts. The threshold of 

heavy use, compared to light or moderate use, as endorsed by the US Department of Health and Human 

Services, is when the level of consumption exceeds three drinks on any day or seven drinks per week for 

women or four drinks on any day or 14 drinks per week for men (DHHS 2010). Light or moderate use, in 

contrast, is defined as one drink per day for women and two per day for men. The National Institute on 

Alcohol Abuse and Alcoholism labels binge drinking, also heavy episodic drinking, as four or more drinks 

(women) or five or more drinks (men) in approximately two hours (NIAAA 2004). WHO has a more lenient 

standard for heavy episodic drinking—six or more drinks on one occasion, at least monthly (WHO 2014). 

Regardless of the cut points for classification of type of use—heavy vs. moderate or light—there is a doseresponse effect related to volume of alcohol consumption and the potential for risks incurred (Rehm et al. 

2003; Shield, Parry, and Rehm 2014). That is, the higher the volume, the more risk for harm. Alcohol use 

falls along a spectrum that ranges from the highest consumption and most risk to abstinence or low-risk 

(Saitz 2005). Long-term or lifetime volume, is associated with chronic, social or health problems and 

alcohol dependence; high quantities of alcohol in one episode, such as binge drinking, can contribute to 

acute problems such as accidents or risk-taking behavior (Chersich and Rees 2010; Saitz 2005). Binge 

drinking also has the immediate physiological consequences of alcohol toxicity on organs and tissues 

(WHO 2014). Consistent with the WHO International Classification of Diseases, 10th Revision, and the 

WHO global strategy to reduce the harmful use of alcohol, harmful drinking is used in this paper to mean 

any drinking or pattern of drinking that is known to cause mental, physical, or social harm (WHO 1992, 

2010). 

Certain patterns of drinking, for example drinking without food or drinking in a heavy episodic fashion, are 

linked to more harmful consequences and vary across cultures (Rehm et al. 2003). Although researchers 

have studied patterns of alcohol use through questionnaire screening in Europe and North America since 

the mid-20th century, the nuances of alcohol consumption in LMICs are less clear. Surveys carried out in 

these populations less commonly include questions on alcohol use (Demers, Room, and Bourgault 2000). 

The limited number of surveys reported in the literature have found that drinking patterns differ by culture, 

religion, gender, context, and social acceptability (Demers, Room, and Bourgault 2000; Peltzer and 

Ramlagan 2009). Compared with drinking patterns characterized by low levels of alcohol consumption and 

especially during mealtimes, some LMIC, such as those in sub-Saharan Africa, exhibit alcohol consumption 

behaviors that are typically heavy, albeit occasional, and usually take place at social gatherings (Chersich 

and Rees 2010; Demers, Room, and Bourgault 2000; Obot 2006; Peltzer and Ramlagan 2009). In Uganda, 

for example, it is common to drink home-brewed alcohol from a communal pot at social gatherings, using 

various means—large spoons, straws, or various sized containers, for example—which can affect the 

amount of alcohol consumed (Hahn, Woolf-King, and Muyindike 2011; Papas et al. 2010). The alcohol 

content of drinks, whether commercially or locally produced, also vary significantly (Greenfield and Kerr 

2008; Papas et al. 2010; Stockwell et al. 2004). In Kenya, for example, there are two traditional home brews, 

busaa and chang’aa. The US standard drink size for busaa ranges from 0.6 to 2.7 drinks, while the standard 

drink size for chang’aa ranges from 1.4 to 8.3 drinks (Papas et al. 2010). In Namibia, one qualitative study 

found that the drinking patterns are either abstention or heavy episodic drinking—light or moderate 

drinking is not part of the drinking culture (LeBeau and Yoder 2006). Along with diverse customs affecting 

what type of alcohol or how much alcohol is consumed, consumption also varies by the time of year or day 

of the week. In some areas, drinking typically occurs more frequently and is heavier on weekends than 

weekdays, and around holidays or festivities (Stockwell et al. 2004). 
3 

To account for variation in drinking patterns both between and within countries, researchers have suggested 

more detailed methods of collecting information on alcohol consumption (Greenfield and Kerr 2008; 

Stockwell et al. 2004). A comprehensive set of questions in surveys could provide an accurate picture of 

volume or quantity and pattern of drinking and provide data that enable researchers to study the context and 

consequences of alcohol use, particularly harmful alcohol use, in different settings. While WHO collects 

data from their member states around the world on alcohol use and several alcohol-related indicators, 

individual-level data are not available for public use (WHO 2014). Additionally, data on other health 

outcomes are not analyzed in this global status report and the potential for analysis is limited. 

1.2. Prevalence of Alcohol Consumption across the World 

In its 2014 version of the “Global status report on alcohol and health”, WHO documents alcohol 

consumption around the world (WHO 2014). The report finds that the highest per capita alcohol 

consumption is in high-income countries; however, total consumption varies across and within regions. In 

addition to economic factors, these variations can be attributed to abstention rates (i.e. non-drinkers), culture 

or religion, and other sociodemographic factors (WHO 2014). The global abstention rate is 48 percent, with 

the highest rates in the Eastern Mediterranean Region (90 percent), the lowest in the Americas and Europe 

(approximately 20 percent for each), with the African Region being in between (57 percent). Per capita 

consumption was found to be positively associated with the prevalence of heavy episodic drinking in the 

general population; however, among current drinkers, the relationship was not consistent (WHO 2014). For 

example, in the African Region, although total alcohol per capita consumption was low, among drinkers it 

was higher than in both the Americas and Europe. This implies that among those who drink in Africa, 

alcohol is consumed heavily. In addition, the pattern of drinking, as examined in the WHO report, was 

found to be riskier in sub-Saharan Africa than in North America and Western Europe. In fact, the WHO 

report finds that over 95 percent of LMICs have a score of three or more (out of five) in the ranking of risky 

drinking globally (WHO 2014). 

1.3. The Link between Alcohol and Risky Sexual Behaviors in Sub-Saharan Africa 

One concern about the consequences of alcohol use is its possible link to HIV infection, particularly in subSaharan Africa, where HIV prevalence is the highest in the world (Hahn, Woolf-King, and Muyindike 

2011). Several studies and review articles have found a relationship between alcohol consumption and risky 

sexual behaviors—for example, sex with multiple partners, sex with casual partners, unprotected sex, 

transactional sex, and sexual coercion—as well as increased risk of contracting HIV or STI infection 

(Cooper 2002; Fisher, Bang, and Kapiga 2007; Kalichman et al. 2007; Leigh and Stall 1993; Woolf-King 

and Maisto 2011). However, the nature of this relationship is complex, and may be either causal or spurious 

(Cooper 2002, 2006). The theory of alcohol myopia and the expectancy theory support a causal explanation 

by describing the pharmacological or psychological mechanisms by which alcohol use leads to risky sexual 

behavior. In the alcohol myopia theory, risky sexual behavior is explained by the diminished cognitive 

abilities of drinkers, which causes them to focus on the most salient cues in their environment, thereby 

affecting their behavior and judgment (Cooper 2006; MacDonald et al. 2000; Weinhardt and Carey 2000). 

In expectancy theory, an individual’s behavior is explained by his or her pre-existing beliefs on alcohol and 

its effects, which cause people to act in ways expected of them (Cooper 2002, 2006). Cooper (2006) also 

describes a reverse causal explanation in which individuals who want to engage in risky sex will use alcohol 

to facilitate their desire. Because most studies on alcohol use and risky sexual behavior are cross-sectional, 

it is not possible to know in which direction the causal relationship goes, if one exists. However, one 

experimental study on men who have sex with men has found support for the hypothesis of the enhanced 

effect of alcohol on sexual risks by both sexual arousal and expectancies (Maisto et al. 2012). Alternatively, 

a spurious or third-variable explanation does not emphasize a direct link between alcohol and risky sexual 

behavior but rather describes the importance of other individual variables, such as personality and attributes 

that directly affect behavior (Cooper 2002, 2006). In other words, coping mechanisms, risk-seeking 
4 

behavior, or lifestyle could cause these behaviors, whether drinking or having risky sex. A longitudinal 

study involving 7,511 discrete sexual events revealed that the majority of differences in risky behaviors 

were explained at the within-person level—that is, changes in personality, the situation, and the relationship 

context (Cooper 2010). 

Review articles on the link between alcohol and risky sex have grouped studies into three main types: global 

association studies, situational association studies, and event-level studies (Cooper 2002; Kalichman et al. 

2007; Leigh and Stall 1993; Woolf-King and Maisto 2011). Global association studies examine whether a 

person who engages in one behavior (alcohol intake, including frequency) is more likely to engage in 

another behavior (risky sexual activity, such as sex with multiple or casual partners and unsafe sex). These 

studies include examining the relationship between alcohol consumption and HIV or other STI status. While 

the review by Leigh and Stall (1993) mainly focused on studies conducted in the United States and 

European countries, Cooper (2002) focused on studies involving college students and youth, while still 

other reviews focused on studies in sub-Saharan Africa (Kalichman et al. 2007; Woolf-King and Maisto 

2011). All of these review articles found that the majority of global association studies support an 

association between history (or frequency) of alcohol use and several risky sexual behavior outcomes, 

including HIV and STI status. Cooper (2002), however, found an inconsistent relationship between alcohol 

consumption and protective behaviors such as condom use. 

Situational association studies examine the link between risky sexual behavior and use of alcohol at the 

same time (or situation) as the sexual activity, while event-level studies examine a specific occasion (for 

example, the last sexual encounter). In general, the findings from situational association studies support the 

findings of global association studies, that there is an association between alcohol use and risky sexual 

behavior, while findings from event-level studies are mixed. Leigh and Stall (1993) found several studies 

that indicate no relationship between substance abuse (drugs or alcohol) and use of condoms or other 

contraceptives in recent encounters. Cooper (2002) found that drinking was strongly associated with 

decreased protective behaviors among younger individuals at first intercourse, and at events that occurred 

in the distant past. A review article covering only event-level studies from the United States (Weinhardt 

and Carey 2000) did not support a link between alcohol use and protective behaviors (such as condom use). 

Woolf-King and Maisto (2011) found two event-level studies in South Africa, both of which showed a 

significant negative effect of alcohol consumption and condom use. The event-level study by Myer, 

Mathews, and Little (2002) in South Africa found that alcohol use was negatively associated with condom 

use, and Kiene et al. (2008) found that consuming alcohol before sex by either or both partners, in a sample 

of HIV-positive men and women in South Africa, was significantly associated with an increased proportion 

and an increased number of unprotected sexual events reported per day. An event-level study of countries 

in sub-Saharan Africa by Kiene and Subramanian (2013) found that among men in Southern Africa, being 

drunk before most recent sex had a negative effect on condom use with steady partners, but that among 

women, the effect was only marginally significant. The study also found that in Southern and Eastern Africa 

men had increased odds of condom use during most recent sex with casual partners if they were drunk 

(Kiene and Subramanian 2013). 

The review of sub-Saharan African studies by (Woolf-King and Maisto 2011) discusses the importance of 

the partner in unsafe sex, including partner drunkenness and partner type. Qualitative studies revealed 

situations in which women were forced to have sex after their partners returned home from drinking. This 

finding was also supported by a few of the quantitative studies in the review, such as in the event-level 

study by Kiene et al. (2008), which found that the odds for engaging in unprotected sex were highest when 

the male partner had been drinking. Similarly, data from the 2006 Uganda Demographic and Health Survey 

found that intoxication before last sex was only a significant predictor of unprotected sex when the woman’s 

partner was intoxicated and not when the woman herself was intoxicated (Tumwesigye, Wanyenze, and 

Greenfield 2012). A study among women bar and hotel workers in Northern Tanzania found that alcohol 

use two hours before sex was not a significant predictor of condom use (Fisher, Cook, and Kapiga 2010). 
5 

Partner type is also an important factor with regards to unsafe sex, especially in terms of HIV risk. Having 

sex outside of a cohabiting relationship without using a condom has greater risk of HIV infection than 

marital sex (Ezzati 2004). The review by Woolf-King and Maisto (2011) also found several studies that 

indicate an increased likelihood of having multiple and/or casual partners with different measures of alcohol 

consumption. The same review found that self-reported harmful alcohol use was associated with increased 

likelihood of participating in transactional sex (Woolf-King and Maisto 2011). Another qualitative study in 

Namibia noted the well-known transactional relationship that occurs at bars (LeBeau and Yoder 2009). In 

this report, it was common knowledge that women who frequent bars and allow men to buy them drinks 

are expected have intercourse with the man; often this exchange is unprotected because it involves drinking. 

Sex-workers also frequent bars in the area studied (LeBeau and Yoder 2009). 

The conflicting findings in the literature on the link between alcohol consumption and risky behaviors 

(including unsafe sex), especially in event-level studies, highlight the need for more studies in this area. 

The analysis in this report will explore the link between alcohol consumption and unsafe sex in sub-Saharan 

Africa using both a global measure of alcohol consumption and an event-level measure. Meanwhile, the 

inventory of alcohol-related questions in DHS surveys will provide an overview of how these questions are 

asked, which will aid in assessing the inclusion of variables related to alcohol use in future surveys. 

7 

2. Data and Methods 

Several methodologies were applied in this study to meet the objectives. The first examined alcohol-related 

questions in the DHS surveys by creating an inventory of all questions related to alcohol consumption that 

have been included in DHS surveys. The second used two analyses to examine the relationship between 

alcohol consumption and health behaviors: 1) the prevalence of ever-drinking in DHS surveys, and 2) 

alcohol consumption as a main predictor of unsafe sex in sub-Saharan Africa. 

2.1. Inventory of Alcohol-Use Questions in DHS Surveys 

2.1.1. Data used in inventory 

A search through all DHS surveys produced a list of 139 surveys that contained alcohol-related questions. 

In a second step, surveys that only asked questions about the consequences of alcohol use were excluded. 

Examples of such questions were: “To lower your hypertension or high blood pressure, are you [...] cutting 

down on alcohol?” or “Have you ever had difficulties at work or school because of drinking?” Surveys 

were also excluded if the questions were about the partner’s alcohol use—such as, “Does your husband 

drink alcohol/Did your last husband drink alcohol?”—if the survey did not also ask questions about the 

respondent’s ever, typical, or current consumption of alcohol. Three surveys were excluded because they 

only asked about drinking during pregnancy. Additionally, surveys that only asked questions about alcohol 

at last sex—for example, “The last time you had sexual intercourse with this person, did you or this person 

drink alcohol?”—were excluded from the inventory unless there were additional direct questions about the 

respondent’s alcohol consumption. Table 1 shows the characteristics of the 65 surveys remaining in the 

inventory of DHS questions related to alcohol consumption, following these exclusions. 
8 

Table 1. Characteristics of DHS surveys that include questions on alcohol consumption, 1987-2014 

Country Year Type 

Eligibility 

criteria 

Number of 

women 

Eligibility 

criteria 

Number of 

men 

Eligibility 

criteria 

sub-Saharan Africa 

Benin 2006 DHS All women, 15-49 17,794 All men, 15-64 5,321 All men, 15-64 

Benin 2001 DHS All women, 15-49 6,219 All men, 15-64 2,709 All men, 15-64 

Burkina Faso 2003 DHS All women, 15-49 12,477 All men, 15-59 3,605 All men, 15-59 

Cape Verde 2005 DHS All women, 15-49 5,505 All men, 15-59 2,644 All men, 15-59 

Equatorial Guinea 2011 DHS All women, 15-49 3,575 All men, 15-59 1,825 All men, 15-59 

Ethiopia 2011 DHS All women, 15-49 16,515 All men, 15-59 14,110 All men, 15-59 

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

Kenya 2003 DHS All women, 15-49 8,195 All men, 15-54 3,578 All men, 15-54 

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

Lesotho 2004 DHS All women, 15-49 7,095 All men, 15-59 2,797 All men, 15-59 

Liberia 2013 DHS All women, 15-49 9,239 All men, 15-49 4,118 All men, 15-49 

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

Madagascar 2003-04 DHS All women, 15-49 7,949 All men, 15-59 2,432 All men, 15-59 

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

Malawi 2000 DHS All women, 15-49 13,220 All men, 15-54 3,092 All men, 15-54 

Mozambique 2009 AIS All women, 15-64* 6,413 All men, 15-64 4,799 All men, 15-64 

Mozambique 2003 DHS All women, 15-49 12,418 All men, 15-64 12,418 All men, 15-64 

Namibia 2013 DHS All women, 15-49 9,176 All men, 15-64 4,481 All men, 15-64 

Namibia 2006-07 DHS All women, 15-49 9,804 All men, 15-49 3,915 All men, 15-49 

Namibia 2000 DHS All women, 15-49 6,755 All men, 15-59 2,954 All men, 15-59 

Nigeria 2003 DHS Ever married, 15-49 9,223 All men, 15-59 3,549 All men, 15-59 

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

Rwanda 2000 DHS All women, 15-49 10,421 All men, 15-59 2,717 All men, 15-59 

South Africa 2003 DHS All women, 15-49 7,401 All men, 15-59 3,118 All men, 15-59 

South Africa 1998 DHS All women, 15-49 11,735 n/a n/a n/a 

Swaziland 2006-07 DHS All women, 15-49 4,987 All men, 15-59 4,156 All men, 15-59 

Uganda 2000-01 DHS All women, 15-49 7,246 All men, 15-54 1,962 All men, 15-54 

Zambia 2013-14 DHS All women, 15-49 16,411 All men, 15-59 14,773 All men, 15-59 

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

Zambia 2001-02 DHS All women, 15-49 7,658 All men, 15-59 2,145 All men, 15-59 

Zimbabwe 1999 DHS All women, 15-49 5,907 All men, 15-54 2,609 All men, 15-54 

Asia and Europe 

Albania 2008-09 DHS All women, 15-49 7,584 All men, 15-49 3,013 All men, 15-49 

Armenia 2000 DHS All women, 15-49 6,430 All men, 15-54 1,719 All men, 15-54 

Azerbaijan 2006 DHS All women, 15-49 8,444 All men, 15-59 2,558 All men, 15-59 

India 2005-06 DHS All women, 15-49 124,385 All men, 15-59 74,369 All men, 15-59 

India 1998-99 DHS Ever married, 15-49 89,199 n/a n/a n/a 

Indonesia 2012 DHS All women, 15-49 45,607 Ever married, 15-54 9,306 Ever married, 15-54 

Indonesia 2012 Special Never married, 15-24 8,902 Never married, 15-24 10,980 Never married, 15-24

Indonesia 2007 Special Never married, 15-24 8,481 Never married, 15-24 10,830 Never married, 15-24

Indonesia 2002-03 Special Ever married, 15-24 1,815 Ever married, 15-24 2,341 Ever married, 15-24 

Kazakhstan 1999 DHS All women, 15-49 4,800 All men, 15-59 1,440 All men, 15-59 

Kyrgyz Republic 2012 DHS All women, 15-49 8,208 All men, 15-59 2,413 All men, 15-59 

Maldives 2009 DHS Ever married, 15-49 7,131 All men, 15-64 1,727 All men, 15-64 

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

Nepal 2001 DHS Ever married, 15-49 8,726 Ever married, 15-19 2,261 Ever married, 15-19 

Philippines 2003 DHS All women, 15-49 13,633 All men, 15-54 4,766 All men, 15-54 

Turkmenistan 2000 DHS All women, 15-49 7,919 n/a n/a n/a 

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

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

Latin America/ Caribbean 

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

Colombia 2010 DHS All women, 13-49 53,521 n/a n/a n/a 

Dominican Republic 2013 DHS All women, 15-49 9,372 All men, 15-59 10,306 All men, 15-59 

Dominican Republic 2013 Special All women, 15-49 1,707 All men, 15-59 2,101 All men, 15-59 

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

Dominican Republic 2007 Special All women, 15-49 1,575 All men, 15-59 1,820 All men, 15-59 

Dominican Republic 2002 DHS All women, 15-49 23,384 All men, 15-59 2,833 All men, 15-59 

Guatemala 1987 DHS All women, 15-44 5,459 n/a n/a n/a 

Guyana 2009 DHS All women, 15-49 4,996 All men, 15-49 3,522 All men, 15-49 

Haiti 2012 DHS All women, 15-49 14,287 All men, 15-59 9,493 All men, 15-59 

Haiti 2005-06 DHS All women, 15-49 10,757 All men, 15-59 4,958 All men, 15-59 

Haiti 2000 DHS All women, 15-49 10,159 All men, 15-59 3,171 All men, 15-59 

Honduras 2011-12 DHS All women, 15-49 22,757 All men, 15-59 7,120 All men, 15-59 

Peru 2013 Continuous All women, 15-49 22,920 n/a n/a n/a 

Peru 2012 Continuous All women, 15-49 23,888 n/a n/a n/a 

Peru 2011 Continuous All women, 15-49 22,517 n/a n/a n/a 

 
9 

2.1.2. Methods of conducting inventory 

A comprehensive list of DHS questions on alcohol was prepared and the questions were grouped by type, 

including 1) ever and current drinking, 2) frequency and quantity of drinking, and 3) heavy drinking. A 

Stata program enabled both the download of the corresponding datasets as well as tabulation of all questions 

and response options for questions containing the words “drink,” “drunk,” and “alcohol”. 

2.2. Prevalence of Ever Consuming Alcohol 

2.2.1. Data used in calculating prevalence 

The question “Have you ever had an alcoholic drink?” was asked in 49 surveys in four regions. Four of 

these surveys were excluded from the prevalence calculations because the question was only asked of youth 

(ages 15-24), for example, in certain surveys in Liberia and Indonesia. Nine surveys were excluded because 

the data were not available in the public domain. Ultimately, a total of 36 surveys were used to calculate 

the adult prevalence of “ever having consumed alcohol.” 

2.2.2. Methods of calculating prevalence 

The prevalence of ever drinking alcohol was calculated from responses to survey questions that asked if a 

respondent had ever consumed alcohol. Missing values or respondents who said that they “don’t know” 

were excluded from this calculation. Sample weights were applied to the prevalence calculation for each 

survey. 

2.3. Regression Analysis of Unsafe Sex in Sub-Saharan Africa 

2.3.1. Data used in regression analysis 

To examine the link between alcohol consumption and a health behavior outcome, regressions were 

performed using alcohol-related variables as the main independent variables and unsafe sex as an outcome 

(dependent variable). Data from DHS surveys (including one AIS survey) in countries in sub-Saharan 

Africa with high HIV prevalence were selected for analysis (Table 2). Only countries with surveys that 

included questions on alcohol consumption, either drinking status (ever or current) or alcohol consumption 

at last sex, were used in the analysis. These included Kenya 2008-2009 DHS (men and women), Lesotho 

2009 DHS (men only), Mozambique 2009 AIS (women only), Namibia 2013 DHS (men and women), 

Swaziland 2006-2007 DHS (men and women), Uganda 2001 AIS (women only), Zambia 2013-2014 DHS 

(men and women), and Zimbabwe 2005-2006 DHS (men and women). 

Table 2. HIV prevalence among men and women age 15-49 in sub-Saharan Africa, DHS 

surveys 2001-2014 

 Women Men 

Country and survey year HIV prevalence Number of women HIV prevalence Number of men 

Kenya 2008-2009 8.0 3,641 4.3 3,066 

Lesotho 2009 26.7 3,778 18.0 2,856 

Mozambique 2009 13.1 5,229 9.2 3,832 

Namibia 2013 16.9 4,051 10.9 3,680 

Swaziland 2006-2007 31.1 4,424 19.7 3,763 

Uganda 2001 8.3 10,883 6.1 8,673 

Zambia 2013-2014 15.1 14,719 11.3 13,140 

Zimbabwe 2005-2006 21.1 6,947 14.5 5,848 

Note: Figures in bold indicate surveys included in the regression analysis. 

 
10 

2.3.2. Construction of variables 

Unsafe sex was defined as sex within the last year with a non-cohabiting partner and without the use of a 

condom at last intercourse (Ezzati 2004). A non-cohabitating partner includes any non-marital partner not 

currently living with the respondent, such as boyfriend/girlfriend, casual acquaintance, or commercial sex 

worker. While some studies do not consider a non-cohabiting boyfriend/girlfriend as a casual relationship, 

this type of relationship was included in our outcome variable because having sex outside of a cohabiting 

relationship, without using a condom, is thought to carry a greater risk of HIV infection than marital sex 

(Ezzati 2004). At the same time, other measures of risky sexual behavior were not useful for this analysis. 

For example, having multiple partners, sex with a casual acquaintance, and having transactional sex all 

have very low frequencies, especially among women. 

Two types of alcohol variables were included as independent variables in the regressions: 1) global levelgeneral alcohol use—i.e. did the respondent ever drink or does the respondent currently drink, and if they 

drink, how frequently; and 2) event-level alcohol consumption, that is, drinking at last sexual event. The 

DHS surveys from Kenya, Mozambique, Uganda, and Zimbabwe did not include global questions on 

general alcohol use but did include questions on alcohol consumption at last sex. For Lesotho, Namibia, 

Swaziland, and Zambia, general alcohol questions were asked. In Lesotho and Namibia, the question 

referred to ever-consuming alcohol, while in Swaziland and Zambia, the question pertained to whether or 

not the respondent currently drinks alcohol. Each of these four surveys also asked about frequency of 

alcohol consumption; however, the questions and response categories differed among the surveys. 

Therefore, the alcohol frequency variable was coded separately for these countries. Namibia asked about 

frequency and quantity of alcohol use in general, but did not ask about alcohol use at last sex. For Swaziland, 

the answers to the alcohol frequency question were categorical and these categories were not changed for 

the analysis. For Lesotho, Namibia, and Zambia the responses to the question about frequency of alcohol 

use were numerical and these were generally categorized according to the distributions, with zero including 

those respondents who reported not drinking or not drinking in the time period specified by the question. 

Only Namibia asked about the quantity of alcohol the respondent drank in the specified time period; this 

was also categorized according to the distribution of the numerical responses, but it was not included in the 

regression analysis because it was the only country with this type of question and therefore no comparisons 

could be made. 

The event-level question on alcohol consumption at last sexual event reads “The last time you had sexual 

intercourse with this/second/third1

 person, did you or this person drink alcohol?” and assesses whether the 

respondent or their partner were drunk. It contained these categorical responses: no, respondent drunk only, 

partner drunk only, both drunk, neither drunk but consumed alcohol. Due to the low frequencies in the 

responses that do not include ‘no’, this variable was coded as a binary variable to indicate whether the 

respondent consumed alcohol (i.e. combined respondent drunk, both drunk, and neither drunk but consumed 

alcohol) or did not consume alcohol (combined no and partner drunk only). Because this variable links 

alcohol consumption directly with the same occasion as the outcome (last sexual intercourse), it allows for 

a type of event-level analysis as described in the literature review. 

The remaining independent variables included in the analysis were respondent’s age (15-24, 25-34, 35 and 

over); locality by wealth (urban, rural non-poor, rural poor); respondent’s education level (none or primary, 

secondary or more); and total lifetime number of sexual partners (one, two, three, four or more for women, 

and one-two, three-four, five-six, seven or more for men). The locality-by-wealth variable was created 

because of the high association between locality and the wealth index. All countries except Namibia had 

 

1

 The question on alcohol use at last sexual event is asked three times: in relation to the last sexual partner, second to 

last sexual partner, and third to last partner. For the purposes of this report, the authors only examine condom use with 

last (most recent) sexual partner. 
11 

very low frequencies for the urban poor category (urban locality combined with the three lowest quintiles 

of the wealth index). Therefore, urban poor and urban non-poor were combined into one category to 

represent urban. Rural poor included respondents in a rural locality and also in the two lowest quintiles of 

the wealth index (poorest and poor), and rural non-poor included rural respondents in the three highest 

quintiles of the wealth index (middle, rich, and richer). Education of the partner was not included in the 

analysis because this was highly correlated with the respondent’s education. Finally, lifetime number of 

sexual partners contained numerical responses that were categorized differently for women and men 

because of the different distributions of this variable by gender. 

2.3.3. Regressions 

The regressions were restricted to men and women who had sex in the past 12 months and were age 15-49. 

A stratified sampling design was used, with the strata variable created from the locality (urban/rural 

residence) and region for each country. Unadjusted and adjusted logistic regressions were performed for all 

the countries. A separate analysis was conducted for the countries that had general alcohol consumption 

questions (Lesotho, Namibia, Swaziland and Zambia) and only included ever- or current drinkers. Alcohol 

frequency was an independent variable in the analysis; it was used to examine whether higher frequency of 

drinking (among drinkers) increased the odds of unsafe sex. All analyses were conducted with Stata/SE 

software, version 13.0. 

13 

3. Results 

3.1. Inventory of Alcohol-related Questions in DHS Surveys

Sixty-five surveys carried out in 42 countries between 1987 and 2014 contained 19 different questions 

related to alcohol consumption. Six of those surveys did not include a man’s questionnaire. Although most 

surveys asked questions about alcohol of both men and women—in countries where both were surveyed—

some surveys only asked alcohol-related questions of one or the other (men or women). For example, DHS 

surveys in Benin in 2001 and 2006 asked the questions of women only, while Ethiopia 2011 and Nepal 

2001 asked the questions of men only. Other surveys asked questions about alcohol only to a subsample of 

youth age 15-24, or the survey itself only included this population, as in Indonesia (Special DHS 2002-03, 

2007, 2012). Tables 3 through 5 present the 65 surveys by region and type of question asked: alcohol 

consumption (ever, current, recent, typical), frequency or quantity of alcohol consumption, and heavy 

alcohol consumption. Table 3 shows surveys that asked about ever or current drinking as well as age at first 

drink, recent drinking, and type of drink typically consumed. The most common question was “Have you 

ever consumed alcohol?” or something similar such as “Have you ever had an alcoholic drink?” This 

general question was asked in 49 of the 65 surveys. At least one question about current drinking, such as 

“Do you drink?” or “Do you currently drink alcohol?” or “Did you drink in the last two weeks/month/ . . 

.?” was asked in 22 surveys. 

Table 3. DHS surveys that include questions related to alcohol consumption (ever, current, 

recent, typical), 1987-2014 

Country and survey year 

Have you ever 

consumed 

alcoholic 

beverages? 

How old were 

you when you 

had your first 

drink? 

Do you 

[currently] drink 

alcohol? 

Did you drink in 

the last [time 

period]? 

What type of 

alcoholic 

beverage do you 

typically drink?

sub-Saharan Africa 

Benin 2006 DHS**  -- -- -- -- 

Benin 2001 DHS**  -- -- -- -- 

Burkina Faso 2003 DHS  -- -- -- -- 

Cape Verde 2005 DHS**  -- -- -- -- 

Equatorial Guinea 2011 DHS  -- -- -- -- 

Ethiopia 2011 DHS*  -- -- -- -- 

Ghana 2008 DHS -- --  [7 days] -- 

Kenya 2003 DHS  -- -- -- -- 

Lesotho 2009 DHS*  -- -- -- -- 

Lesotho 2004 DHS  -- -- -- -- 

Liberia 2013 DHS -- -- -- [month] -- 

Liberia 2007 DHS***  -- -- -- -- 

Madagascar 2003-2004 DHS  -- -- -- -- 

Malawi 2004 DHS  -- -- -- -- 

Malawi 2000 DHS**  -- -- -- -- 

Mozambique 2009 AIS  -- -- -- -- 

Mozambique 2003 DHS  --  -- 

Namibia 2013 DHS  -- -- [2 weeks] -- 

Namibia 2006-07  -- -- -- -- 

Namibia 2000 DHS  -- -- -- -- 

Nigeria 2003 DHS  -- -- -- -- 

Rwanda 2005 DHS*  -- -- -- -- 

Rwanda 2000 DHS  -- -- -- -- 

South Africa 2003 DHS  -- -- [12 months] -- 

South Africa 1998 DHS  --  -- -- 

Swaziland 2006-07 DHS** -- --  -- -- 

Uganda 2000-01 DHS  --  -- -- 

Zambia 2013-14 DHS -- --  -- -- 

Zambia 2007 DHS -- --  -- -- 

Zambia 2001-02 DHS  -- -- -- -- 

Zimbabwe 1999 DHS** -- -- -- -- -- 

(Continued)
14 

Table 3. − Continued 

Country and survey year 

Have you ever 

consumed 

alcoholic 

beverages? 

How old were 

you when you 

had your first 

drink? 

Do you 

[currently] drink 

alcohol? 

Did you drink in 

the last [time 

period]? 

What type of 

alcoholic 

beverage do you 

typically drink?

Asia and Europe 

Albania, 2008, DHS  -- -- [12 months] -- 

Armenia 2000 DHS  --  -- -- 

Azerbaijan 2006 DHS* -- -- -- -- -- 

India 2005-06 DHS  -- -- -- -- 

India 1998-99 DHS****  -- -- -- -- 

Indonesia 2012 DHS   -- -- -- 

Indonesia 2012 Special***   -- -- -- 

Indonesia 2007 Special***   -- -- -- 

Indonesia 2002-03 Special***   -- -- -- 

Kazakhstan 1999 DHS  -- -- -- -- 

Kyrgz Republic 2012 DHS   -- -- -- 

Maldives 2009 DHS***  -- -- -- -- 

Moldova 2005 DHS -- -- -- -- -- 

Nepal 2001 DHS*  -- -- -- -- 

Philippines 2003 DHS*  -- -- -- -- 

Turkmenistan 2000 DHS**  --  -- -- 

Ukraine 2007 DHS  -- -- -- -- 

Uzbekistan 2002 Special  -- -- [12 months] -- 

Latin America/Caribbean 

Bolivia 2008 -- --  -- -- 

Colombia 2010 DHS** -- --  -- -- 

Dominican Republic 2013 DHS -- -- -- [30 days] -- 

Dominican Republic 2013 Special -- -- -- [30 days] -- 

Dominican Republic 2007 DHS  -- -- -- -- 

Dominican Republic 2007 Special  -- -- -- -- 

Dominican Republic 2002  -- -- -- -- 

Guatemala 1987 DHS** -- -- -- -- 

Guyana 2009 DHS -- -- -- [30 days] -- 

Haiti 2012 DHS  -- -- -- 

Haiti 2005-06 DHS  -- -- -- 

Haiti 2000 DHS  -- -- -- -- 

Honduras 2011-2012 DHS  -- -- -- -- 

Peru 2013 Continuous**  -- -- 

[12 months and 

3 months ] 

Peru 2012 Continuous** -- -- -- [month] 

Peru 2011 Continuous** -- -- -- [month] 

Note: * men only, ** women only, *** youth age 15-24 only (women and men),   head of household only 

Table 4 shows that questions on the frequency of drinking were asked fairly consistently in 46 surveys. The 

question was often phrased as, “During the last [time period], how many days did you drink?” The most 

common time period was three months (in 23 surveys), although some surveys referred to seven days, two 

weeks, 30 days, one month, or 12 months. Some surveys referred to “occasions” or “times”, rather than 

“days”. Table 4 also shows that questions on the quantity of alcohol consumed were less likely to be 

included in surveys. Only 14 surveys asked about specific quantity of alcohol consumed, with variations 

focused on the quantity of recent drinking or the average amount consumed.
15 

Table 4. DHS surveys that include questions related to frequency or quantity of alcohol consumption, 

1987-2014 

 Frequency of Drinking Quantity 

Country and survey year 

During the last 

[time period], 

how many days 

did you drink? 

How often/ 

frequently do 

you drink 

alcoholic 

beverages? 

In the past [time 

period], on the days 

that you drank, how 

many drinks did you 

usually have? 

How many 

drinks do you 

have in a 

week/ 

weekend? 

When you drink 

alcohol, how 

many drinks do 

you have each 

day? 

In the past 30 days, 

what was the largest 

number of drinks you 

had on a single 

occasion? 

sub-Saharan Africa 

Benin 2006 DHS**  [3 months] -- -- -- -- --

Benin 2001 DHS** [3 months] -- -- -- -- --

Burkina Faso 2003 DHS [3 months] -- -- -- -- --

Cape Verde 2005 DHS** -- -- -- -- -- --

Equatorial Guinea 2011 DHS [3 months] -- -- -- -- --

Ethiopia 2011 DHS* [30 days] -- -- -- -- --

Ghana 2008 DHS [7 days] -- -- -- -- --

Kenya 2003 DHS [month] -- -- -- -- --

Lesotho 2009 DHS* [3 months] -- -- -- -- --

Lesotho 2004 DHS [3 months] -- -- -- -- --

Liberia 2013 DHS [month] -- [month] -- -- --

Liberia 2007 DHS*** -- -- -- -- -- --

Madagascar 2003-2004 DHS [3 months] -- -- -- -- --

Malawi 2004 DHS -- -- -- -- -- --

Malawi 2000 DHS** [3 months] -- -- -- -- --

Mozambique 2009 AIS [12 months] -- -- -- -- --

Mozambique 2003 DHS [3 months]  -- -- -- --

Namibia 2013 DHS [2 weeks] -- [2 weeks] -- -- --

Namibia 2006-07 [month] -- -- -- -- --

Namibia 2000 DHS [month] -- -- -- -- --

Nigeria 2003 DHS [3 months] -- -- -- -- --

Rwanda 2005 DHS* [3 months] -- -- -- -- --

Rwanda 2000 DHS [3 months] -- -- -- -- --

South Africa 2003 DHS [12 months] -- [7 days] --  --

South Africa 1998 DHS -- -- -- -- [week/weekend] --

Swaziland 2006-07 DHS** --  -- -- -- --

Uganda 2000-01 DHS [30 days] -- -- -- -- --

Zambia 2013-14 DHS [7 days] -- -- -- -- --

Zambia 2007 DHS [7 days] -- -- -- -- --

Zambia 2001-02 DHS 

[1 month- men] 

[3 months- women] -- -- -- -- -- 

Zimbabwe 1999 DHS** [30 days] -- -- -- -- --

Asia and Europe -- 

Albania, 2008, DHS --  -- --  --

Armenia 2000 DHS [3 months] -- -- -- [week/weekend] --

Azerbaijan 2006 DHS* [month]  [month] -- -- --

India 2005-06 DHS --  -- -- -- --

India 1998-99 DHS**** -- -- -- -- -- --

Indonesia 2012 DHS [3 months] -- -- -- -- --

Indonesia 2012 Special*** [3 months] -- -- -- -- --

Indonesia 2007 Special*** [3 months] -- -- -- -- --

Indonesia 2002-03 Special*** [3 months] -- -- -- -- --

Kazakhstan 1999 DHS [3 months] -- -- -- -- --

Kyrgz Republic 2012 DHS --  [month] -- -- --

Maldives 2009 DHS*** [month] -- -- -- -- --

Moldova 2005 DHS --  [month] -- -- --

Nepal 2001 DHS* [7 days] -- -- -- -- --

Philippines 2003 DHS* [month] -- -- -- -- --

Turkmenistan 2000 DHS** -- -- --  -- --

Ukraine 2007 DHS --  [month] -- -- --

Uzbekistan 2002 Special -- -- -- -- -- --

Latin America/Caribbean --

Bolivia 2008 -- -- -- -- -- --

Colombia 2010 DHS** -- -- -- -- -- --

Dominican Republic 2013 DHS [30 days] -- -- -- -- --

Dominican Republic 2013 Special [30 days] -- -- -- -- --

Dominican Republic 2007 DHS [3 months] -- -- -- -- --

Dominican Republic 2007 Special [3 months] -- -- -- -- --

Dominican Republic 2002 [3 months] -- -- -- -- --

Guatemala 1987 DHS** --  -- -- -- --

Guyana 2009 DHS [30 days] -- -- --  

Haiti 2012 DHS --  -- -- -- --

Haiti 2005-06 DHS -- -- -- -- -- --

Haiti 2000 DHS [3 months] -- -- -- -- --

Honduras 2011-2012 DHS --  -- -- -- --

Peru 2013 Continuous** [30 days] --

Peru 2012 Continuous** [month] -- [last time]  -- --

Peru 2011 Continuous** [month] -- [last time]  -- -- 

Note: * men only, ** women only, *** youth age 15-24 only (women and men),   head of household only
16 

Table 5 shows that 44 surveys asked some variation of a question regarding heavy drinking, although the 

questions are mostly subjective and do not always specify a quantity of drinking that would allow for the 

clear classification of heavy or heavy episodic use. Eight different questions on heavy drinking were asked, 

some as general as, “Have you ever been drunk after drinking alcohol?” to more specific questions such as, 

“In the past [time period], how many times did you have four or more standard drinks of alcohol on one 

occasion?” Among the questions about heavy drinking, the question “In the last [time period], how many 

days have you been drunk?” was the most common, appearing in 19 surveys. Again, three months was the 

most common time period, used in 14 surveys. 

Table 5. DHS surveys that include questions related to heavy alcohol consumption, 1987-2014 

Country and survey year 

In the past 

[time period], 

have there been 

days when you 

had more than 

usual? 

In the past [time 

period], how 

many times did 

you have four or 

more standard 

drinks (glasses, 

cups) of 

alcoholic drinks 

on one 

occasion? 

In the past 

[time period], 

how many 

drinks did you 

have on the 

days that you 

drank more 

than usual? 

How often 

did you 

drink that 

amount 

(more than 

usual)? 

Have you 

ever been 

drunk after 

drinking 

alcohol? 

In the last 

[time period], 

how many 

days have 

you been 

drunk? 

In the last 

[time period] 

months, how 

often have 

you gotten 

drunk? 

Do you 

usually 

binge 

drink? 

sub-Saharan Africa 

Benin 2006 DHS**  -- -- -- --  [3 months] -- -- 

Benin 2001 DHS** -- -- -- --  [3 months] -- -- 

Burkina Faso 2003 DHS -- -- -- --  [3 months] -- -- 

Cape Verde 2005 DHS** -- -- -- --  -- [3 months] -- 

Equatorial Guinea 2011 DHS -- -- -- -- -- -- [ever] -- 

Ethiopia 2011 DHS* -- -- -- -- -- -- -- -- 

Ghana 2008 DHS* -- -- -- -- -- -- 

[no time 

specified] -- 

Kenya 2003 DHS -- -- -- -- -- -- -- -- 

Lesotho 2009 DHS* -- -- -- --  [3 months] -- -- 

Lesotho 2004 DHS -- -- -- --  [3 months] -- -- 

Liberia 2013 DHS -- -- -- --  -- -- -- 

Liberia 2007 DHS*** -- -- -- --  -- -- -- 

Madagascar 2003-2004 DHS -- -- -- --  [3 months] -- -- 

Malawi 2004 DHS -- -- -- -- -- -- 

[no time 

specified] -- 

Malawi 2000 DHS** -- -- -- --  [3 months] -- -- 

Mozambique 2009 AIS -- -- -- -- -- -- -- -- 

Mozambique 2003 DHS -- -- -- --  [3 months] -- -- 

Namibia 2013 DHS -- -- -- --  -- -- -- 

Namibia 2006-07 -- -- -- --  [month] -- -- 

Namibia 2000 DHS -- -- -- --  [month] -- -- 

Nigeria 2003 DHS -- -- -- --  [3 months] -- -- 

Rwanda 2005 DHS* -- -- -- --  -- -- -- 

Rwanda 2000 DHS -- -- -- --  -- -- -- 

South Africa 2003 DHS -- -- -- --  -- -- -- 

South Africa 1998 DHS -- -- -- --  -- -- -- 

Swaziland 2006-07 DHS** -- -- -- --  [3 months] -- -- 

Uganda 2000-01 DHS -- -- -- --  [30 days] -- -- 

Zambia 2013-14 DHS -- -- -- -- -- -- -- -- 

Zambia 2007 DHS -- -- -- -- -- -- -- -- 

Zambia 2001-02 DHS -- -- -- -- 

[1 month-men] 

[3 monthswomen] -- -- 

Zimbabwe 1999 DHS** -- -- -- -- -- [30 days] -- -- 

(Continued)
17 

Table 5. − Continued 

Country and survey year 

In the past 

[time period], 

have there been 

days when you 

had more than 

usual? 

In the past [time 

period], how 

many times did 

you have four or 

more standard 

drinks (glasses, 

cups) of 

alcoholic drinks 

on one 

occasion? 

In the past 

[time period], 

how many 

drinks did you 

have on the 

days that you 

drank more 

than usual? 

How often 

did you 

drink that 

amount 

(more than 

usual)? 

Have you 

ever been 

drunk after 

drinking 

alcohol? 

In the last 

[time period], 

how many 

days have 

you been 

drunk? 

In the last 

[time period] 

months, how 

often have 

you gotten 

drunk? 

Do you 

usually 

binge 

drink? 

Asia and Europe 

Albania, 2008, DHS -- -- -- -- -- -- -- --

Armenia 2000 DHS -- -- -- -- -- -- -- --

Azerbaijan 2006 DHS* [3 months] --   -- -- -- -- 

India 2005-06 DHS -- -- -- -- -- -- -- --

India 1998-99 DHS**** -- -- -- -- -- -- -- --

Indonesia 2012 DHS -- -- -- --  -- -- -- 

Indonesia 2012 Special*** -- -- -- --  -- -- --

Indonesia 2007 Special*** -- -- -- --  -- -- --

Indonesia 2002-03 Special*** -- -- -- --  -- -- -- 

Kazakhstan 1999 DHS -- -- -- --  [3 months] -- --

Kyrgz Republic 2012 DHS [3 months] --   -- -- -- -- 

Maldives 2009 DHS*** -- -- -- -- -- -- -- --

Moldova 2005 DHS 

[1 monthwomen] 

[3 months-men] --

[1 monthwomen] 

[3 months-men] -- -- -- -- --

Nepal 2001 DHS* -- -- -- -- -- -- -- --

Philippines 2003 DHS* -- -- -- -- -- -- -- -- 

Turkmenistan 2000 DHS** -- -- -- --  -- -- --

Ukraine 2007 DHS [3 months] -- [3 months] -- -- -- -- --

Uzbekistan 2002 Special -- -- -- -- -- -- -- -- 

Latin America/Caribbean 

Bolivia 2008 -- -- -- -- -- -- -- --

Colombia 2010 DHS** -- -- -- -- -- [12 months] -- -- 

Dominican Republic 2013 DHS -- [30 days] -- -- -- -- -- --

Dominican Republic 2013 Special -- [30 days] -- -- -- -- -- --

Dominican Republic 2007 DHS -- -- -- -- -- -- -- -- 

Dominican Republic 2007 Special -- -- -- -- -- -- -- --

Dominican Republic 2002 -- -- -- --  [3 months] -- --

Guatemala 1987 DHS** -- -- -- -- -- -- -- -- 

Guyana 2009 DHS -- -- -- -- -- -- -- --

Haiti 2012 DHS -- -- -- --  -- -- --

Haiti 2005-06 DHS -- -- -- --  -- -- -- 

Haiti 2000 DHS -- -- -- --  [3 months] -- --

Honduras 2011-2012 DHS -- -- -- -- -- -- -- 

Peru 2013 Continuous** -- -- -- -- -- -- -- --

Peru 2012 Continuous** -- -- -- -- -- -- -- --

Peru 2011 Continuous** -- -- -- -- -- -- -- -- 

Note: * men only, ** women only, *** youth age 15-24 only (women and men),   head of household only

Table 6 lists all 19 of the alcohol-related questions from the DHS surveys by type of response elicited—

yes or no (dichotomous), numerical (continuous), and categorical responses. This table highlights a major 

technical problem faced by researchers analyzing alcohol consumption. Similar types of questions involve 

different types of response options, therefore limiting comparison across countries. For example, questions 

about frequency of drinking can elicit either numerical or categorical responses, depending on the survey. 

An even greater problem occurs when the same question appears in different surveys but with different 

response options, a situation that can lead to overlapping categories or subjective measures. For example, 

response options to questions about frequency of drinking such as, “How often do you drink alcohol?” vary 

across surveys, as in this example from the Swaziland 2006-07 DHS: 

Less than once a month

Once a month

Once a week

2-3 times per week

Every day

Other (specify)
18 

Compared with the Albania 2008 DHS:

5 or more days per week 

1-4 days per week 

1-3 days per month

Less than once a month

Or the Honduras 2011-2012 DHS: 

Frequently 

Sometimes 

Almost never 

These different response options make it impossible to compare results across surveys. For example in 

Swaziland (2006-07), the category “once a week” could potentially be compared with either “1-3 days per 

month” or “1-4 days per week” in the Albania 2008 survey. Likewise, “1-4 days per week” in Albania could 

fall under either “once a week” or the “2-3 three times per week” in the Swaziland 2006-07 survey. 

Table 6. Questions on alcohol consumption included in DHS 

surveys by type of response elicited (yes/no, numerical, 

categorical) 

Questions eliciting a dichotomous (yes/no) response: 

Have you ever consumed alcoholic beverages? 

Do you [currently] drink alcohol? 

Did you drink in the last [time period]? 

In the past [time period], have there been days when you had more than usual? 

Have you ever been drunk after drinking alcohol? 

Do you usually binge drink? 

Questions eliciting a numerical response? 

How old were you when you had your first drink? 

During the last [time period], how many days did you drink? 

In the past [time period], on the days that you drank, how many drinks did you usually have? 

How many drinks do you have in a week/ weekend? 

When you drink alcohol, how many drinks do you have each day? 

In the last [time period], how many days have you been drunk? 

In the past [time period], how many drinks did you have on the days that you drank more than usual? 

In the past 30 days, what was the largest number of drinks you had on a single occasion? 

In the past [time period], how many times did you have four or more standard drinks (glasses, cups) of 

alcoholic drinks on one occasion? 

Questions eliciting a categorical response: 

What type of drink do you have most often? 

How often/frequently do you drink alcoholic beverages? 

How often did you drink that amount (more than usual)? 

In the last [time period] months, how often have you gotten drunk? 

3.2. Prevalence of Ever Having Consumed Alcohol 

The most common question, “Have you ever had an alcoholic drink?” appropriately elicits a yes or no 

response across all surveys where that question was asked. Using this question, prevalence of ever-drinking 

among all adults surveyed was assessed using data from 36 surveys in three regions. Figures 1 through 3 

show the regional percentages of men and women who have ever had an alcoholic drink. Among men in 

sub-Saharan Africa (Figure 1), the range is from 30 percent in the Malawi 2000 survey to 76 percent in the 

Rwanda 2005 survey. Among women in sub-Saharan Africa, the range is from two percent in the Malawi 

2000 survey to 58 percent in the Rwanda 2000 survey. Although not all surveys asked this question of both 

men and women, the survey with the largest differential between men and women in ever consuming 

alcohol was the Zambia 2001-02 survey, with a difference of 40 percentage points (63 percent for men and 
19 

23 percent for women). Ethiopia (2011) and Burkina Faso (2003) had the smallest differences between men 

and women, at around 10 percentage points each. 

Figure 1. Percent of males and females who have ever had an alcoholic drink, sub-Saharan Africa 

 

30

50

31

47

63

55

44

65

64

55

61

69

61

74

54

76

2

8

12

13

19

23

26

29

35

36

36

38

39

45

50

50

52

58

0 20 40 60 80 100

Malawi 2000 DHS

Malawi 2004 DHS

Kenya 2003 DHS

Nigeria 2003 DHS

Mozambique 2003 DHS

Zambia 2001-02 DHS

Lesotho 2004 DHS

Benin 2006 DHS

Burkina Faso 2003 DHS

Namibia 2006-07

Namibia 2000 DHS

Benin 2001 DHS

Mozambique 2009 AIS

Ethiopia 2011 DHS

Namibia 2013 DHS

Madagascar 2003-04 DHS

Uganda 2000-01 DHS

Rwanda 2000 DHS

Lesotho 2009 DHS

Rwanda 2005 DHS

Women

Men
20 

Figure 2 shows that in the Asia and Europe region, the Ukraine 2007 survey had the highest percentages of 

ever-drinking (90 percent for men and 85 percent for women), while the India 2005-06 survey had the 

lowest percentages of ever-drinking (32 percent for men and two percent for women). The gap between 

men and women was largest in the Armenia 2000 survey (37 percentage points) and smallest in the Ukraine 

2007 survey (5 percentage points). 

Figure 2. Percent of males and females who have ever had an alcoholic drink, Asia and Europe 

Figure 3 shows that in Latin America, men and women in the Dominican Republic had the highest 

percentages of ever-drinking (92 percent for men in the 2002 survey and 72 percent for women in both the 

2002 and 2007 surveys), while men and women in the Haiti 2000 survey had the lowest levels of everdrinking (22 percent and 2 percent, respectively). The smallest differentials between men and women were 

in the Dominican Republic 2007 survey and the Dominican Republic 2007 Special survey (15-16 

percentage points). The largest differential was in the Guyana 2009 survey—a difference of 43 percentage 

points between men and women. 

Figure 3. Percent of males and females who have ever had an alcoholic drink, Latin America 

32

65

86

85

90

68

71

83

2

32

49

78

85

0 20 40 60 80 100

India 2005-06 DHS

Albania 2008 DHS

Armenia 2000 DHS

Kazakhstan 1999 DHS

Ukraine 2007 DHS

Nepal 2001 DHS

Kyrgz Republic 2012 DHS

Philippines 2003 DHS

Women

Men

22

34

51

65

65

83

92

89

2

6

11

22

25

67

72

72

0 20 40 60 80 100

Haiti 2000 DHS

Honduras 2011-2012 DHS

Haiti 2005-06 DHS

Guyana 2009 DHS

Haiti 2012 DHS

Domincan Republic 2007 Special

Domincan Republic 2002 DHS

Domincan Republic 2007 DHS

Women

Men
21 

One other finding of note regarding the alcohol questions in DHS surveys is the general lack of specification 

of what constitutes a standard drink size. In the United States, a bottle of beer (12 oz) with 5 percent alcohol, 

a glass of wine (5 oz) with 12 percent alcohol, or a shot of liquor (1.5 oz) with 40 percent alcohol are 

considered standard drink sizes (DHHS 2010). Only three surveys (Azerbaijan 2006, Moldova 2005, and 

Ukraine 2007) defined a standard drink by the amount of pure alcohol in different types of beverages and 

specified the different sizes for each type.

3.3. Alcohol Use and Unsafe Sex in Sub-Saharan Africa

3.3.1. Descriptive results 

Table 7 summarizes the alcohol-related variables in DHS data for Lesotho, Namibia, Swaziland, and 

Zambia. These countries were used in the logistic regressions of unsafe sex, along with Kenya, 

Mozambique, Swaziland (men), Uganda, and Zimbabwe; however, the latter four countries do not appear 

in Table 7 because they did not include general questions about alcohol consumption, only questions about 

alcohol consumption at last sex. As indicated in Table 3, the question on alcohol consumption was for 

lifetime drinking status (ever drank alcohol) in Lesotho and Namibia and for current drinking status 

(currently drink alcohol) in Swaziland and Zambia. As Table 7 shows, almost half the men in Lesotho and 

half the women in Namibia, as well as 61 percent of men in Namibia, reported that they ever drank alcohol. 

In Namibia, reported alcohol use was higher among men than women (61 percent compared with 50 percent, 

respectively). In Namibia the frequency and the quantity of alcohol consumption was also higher among 

men than women. Approximately 32 percent of men in Namibia reported having had two or more drinks in 

the last two weeks compared with 14 percent of women, and 16 percent of the men reported drinking an 

average of four drinks or more per day compared with seven percent of women.

In Swaziland and Zambia the question on alcohol consumption was for current drinking status rather than 

ever-drinking status. For women in both Swaziland and Zambia, current alcohol consumption was relatively 

low, at about 10 percent or below. More Zambian men than women reported that they currently drink 

alcohol (37 percent versus 10 percent). The frequency of alcohol consumption among Zambian men was 

also higher than women—20 percent of men in Zambia reported drinking two or more drinks in the last 

week compared with three percent of women. Among women in Swaziland, only three percent reported 

that they drank once a week or more. 
22 

Table 7. Alcohol consumption among men and women age 15-49 in Lesotho, Namibia, Swaziland 

and Zambia, DHS surveys 2006-2014 

 

Lesotho 

2009 

Namibia 

2013 

Swaziland 

2006-2007 

Zambia 

2013-2014 

Men Women Men Women Women Men 

Variable % N % N % N % N % N % N 

Ever drank 

Yes 53.3 1,602 49.6 4,545 60.8 2,443 -- -- -- -- -- -- 

No 46.7 1,405 50.4 4,615 39.2 1,577 -- -- -- -- -- -- 

Currently drink 

Yes -- -- -- -- -- -- 7.2 357 10.4 1,707 36.8 4,986

No -- -- -- -- -- -- 92.8 4,627 89.6 14,699 63.2 8,573

Alcohol frequency: number of days had one 

drink in the last 2 weeks 

0 -- -- 78.2 7,067 60.4 2409 -- -- -- -- -- -- 

1 -- -- 7.9 713 8.0 319 -- -- -- -- -- -- 

2+ -- -- 13.9 1,258 31.6 1259 -- -- -- -- -- -- 

Alcohol frequency: How often do you drink 

alcohol 

Does not drink -- -- -- -- -- -- 92.9 4,627 -- -- -- -- 

Once a month or less -- -- -- -- -- -- 4.3 214 -- -- -- -- 

Once a week -- -- -- -- -- -- 1.7 87 -- -- -- -- 

More than once a week -- -- -- -- -- -- 1.0 51 -- -- -- -- 

Alcohol frequency: Days drank alcohol in 

the last week 

0 -- -- -- -- -- -- -- -- 93.9 15,372 70.2 9,508

1 -- -- -- -- -- -- -- -- 3.2 523 9.6 1,299

2+ -- -- -- -- -- -- -- -- 2.9 483 20.2 2,729

Alcohol frequency: Number of days drank 

alcohol in the last 3 months 

None 62.6 1,764 -- -- -- -- -- -- -- -- -- -- 

1-3 18.1 508 -- -- -- -- -- -- -- -- -- -- 

4-9 8.8 247 -- -- -- -- -- -- -- -- -- -- 

10-90 10.5 297 -- -- -- -- -- -- -- -- -- -- 

Average number of alcoholic drinks 

consumed per day in the last 2 weeks 

0 -- -- 79.7 7,067 62.3 2,409 -- -- -- -- -- -- 

1 -- -- 5.7 503 6.4 247 -- -- -- -- -- -- 

2 -- -- 4.4 388 9.0 347 -- -- -- -- -- -- 

3 -- -- 3.0 270 6.5 250 -- -- -- -- -- -- 

4+ -- -- 7.2 636 15.9 616 -- -- -- -- -- -- 

Table 8 shows the variables used in the regression analysis of men or women age 15-49 who had sexual 

intercourse in the past 12 months. The question on alcohol consumption at last (most recent) sex was 

available for all the countries in the analysis except Namibia, which only asked about general alcohol 

consumption. Women in Uganda reported the highest proportion drinking alcohol at last sex (13 percent); 

the highest for men was in Zambia (12 percent) (Table 8). As with general alcohol consumption, in Kenya, 

Swaziland, Zambia, and Zimbabwe—all of the countries where surveys for both men and women were 

conducted, except for Namibia, where this question was not asked—men were more likely than women to 

report drinking at last sex. In Kenya, Mozambique, Swaziland, Zambia, and Zimbabwe the proportions of 

women who reported drinking at last sex were low (approximately 2-3 percent). Figure 4 summarizes the 

DHS data on alcohol consumption, unsafe sex, and HIV-positive status in the sub-Saharan countries 

included in the analysis. Unsafe sex was most common among men in Lesotho (21 percent), followed by 

men in Swaziland (20 percent), and women in Namibia (19 percent); unsafe sex was lowest in Zimbabwe 

among women (6 percent) and men (9 percent). 

 
23 

Table 8. Variables used in the regression analyses for men or women age 15-49 who have had sexual 

intercourse in the past 12 months, DHS surveys in sub-Saharan Africa, 2001-2014 

Surveys that have alcohol consumption questions 

Lesotho 

2009 

Namibia 

2013 

Swaziland 

2006-2007 

Zambia 

2013-2014 

Men Women Men Women Women Men 

Variable % N % N % N % N % N % N 

Unsafe sex with last sex partner

Yes 21.1 477 19.3 1,281 12.9 383 20.2 693 10.9 1334 15.2 1,519

No 78.9 1,780 80.7 5,351 87.1 2,581 79.8 2,745 89.1 10,909 84.8 8,506

Age 

15-24 39.8 899 31.9 2,121 31.8 942 37.3 1,283 30.5 3,737 26.5 2,656

25-34 33.8 763 35.9 2,383 35.1 1,041 33.8 1,165 38.9 4,772 35.5 3,561

35+ 39.8 899 32.2 2,135 33.1 983 28.9 994 30.5 3,743 38.0 3,810

Locality by wealth 

Urban 28.6 646 58.6 3,889 59.8 1,775 27.8 957 42.6 5,218 42.9 4,298

Rural non-poor 37.8 854 16.1 1,066 16.6 492 39.8 1,369 21.3 2,611 21.8 2,191

Rural poor 33.5 757 25.4 1,683 23.6 699 32.4 1,115 36.1 4,424 35.3 3,538

Education level 

None or primary 61.3 1,384 23.8 1,580 29.9 888 42.1 1,448 60.7 7,425 45.9 4,598

Secondary or more 38.7 873 76.2 5,059 70.1 2,079 57.9 1,993 39.8 4,815 54.1 5,424

Ever drank 

Yes 59.2 1,336 54.5 3,612 67.9 2,013 -- -- -- -- -- --

No 40.8 921 45.5 3,016 32.1 953 -- -- -- -- -- --

Currently drink 

Yes -- -- -- -- -- -- 8.8 301 11.7 1,439 44.3 4,446

No -- -- -- -- -- -- 91.2 3,137 88.3 10,811 55.7 5,580

Alcohol consumption at last sex 

Yes 8.4 191 -- -- -- -- 1.5 52 3.4 411 11.8 1,184

No 91.6 2,066 -- -- -- -- 98.5 3,375 96.6 11,815 88.2 8,827

Lifetime number of sexual partners (women) 

1 -- -- 29.7 1,938 -- -- 35.7 1,190 44.8 5,473 -- --

2 -- -- 30.4 1,980 -- -- 30.2 1,007 31.1 3,799 -- --

3 -- -- 21.1 1,375 -- -- 18.6 620 14.8 1,813 -- --

4+ -- -- 18.9 1,230 -- -- 15.6 520 9.2 1,127 -- --

Lifetime number of sexual partners (men)

1-2 27.1 578 -- -- 28.7 791 -- -- -- -- 26.8 2,661

3-4 27.8 592 -- -- 24.8 684 -- -- -- -- 31.1 3,095

5-6 17.9 381 -- -- 16.0 442 -- -- -- -- 18.5 1,842

7+ 27.2 579 -- -- 30.5 842 -- -- -- -- 23.6 2,346

Surveys that do not ask about general alcohol consumption but do ask whether the 

respondent or respondent's partner were drinking during most recent sex 

Kenya 

2008-2009 

Mozambique

2009 

Swaziland

2006-2007 

Uganda 

2001 

Zimbabwe 

2005-2006 

Women Men Women Men Women Women Men 

Variables % N % N % N % N % N % N % N 

Unsafe sex with last sex partner

Yes 11.2 671 11.8 275 14.5 1,199 17.2 426 10.7 1,578 6.0 353 8.8 385

No 88.8 5,307 88.2 2,048 85.5 7,081 82.8 2,051 89.3 13,225 94.0 5,526 91.2 3,996

Age 

15-24 29.5 1,765 25.9 601 33.6 2,788 30.5 755 29.5 4,365 34.7 2,039 28.9 1,195

25-34 39.7 2,373 37.4 870 34.7 2,880 37.0 918 36.4 5,395 39.0 2,293 42.3 1,751

35+ 30.8 1,843 36.7 853 31.7 2,634 32.5 805 34.1 5,050 26.3 1,547 28.9 1,195

Locality by wealth 

Urban 25.8 1,545 30.5 708 33.1 2,749 35.2 873 19.7 2,923 35.8 2,107 41.0 1,798

Rural non-poor 40.6 2,429 40.1 932 32.8 2,726 38.7 959 44.0 6,515 26.7 1,567 26.2 1,149

Rural poor 33.6 2,008 29.4 683 34.1 2,827 26.1 646 36.3 5,372 37.5 2,205 32.7 1,435

Education level 

None or primary 67.7 4,052 53.8 1,249 81.5 6,767 39.5 979 70.5 10,448 40.6 2,389 28.6 1,255

Secondary or more 32.3 1,930 46.2 1,074 18.5 1,535 60.5 1,498 29.5 4,363 59.4 3,491 71.4 3,127

Alcohol consumption at last sex 

Yes 1.6 97 6.8 159 2.6 219 8.2 202 13.3 1,966 1.9 113 9.3 407

No 98.4 5,869 93.2 2,164 97.4 8,049 91.8 2,273 86.7 12,837 98.1 5,763 90.7 3,950

Lifetime number of sexual partners (women) 

1 42.5 2,519 -- -- 29.6 2,267 -- -- 25.0 3,602 66.8 3,914 -- --

2 30.4 1,800 -- -- 25.2 1,927 -- -- 23.7 3,409 20.8 1,220 -- --

3 16.5 978 -- -- 16.7 1,280 -- -- 18.2 2,617 7.5 440 -- --

4+ 10.6 627 -- -- 28.5 2,182 -- -- 33.1 4,770 4.9 284 -- --

Lifetime number of sexual partners (men) 

1-2 -- -- 28.0 583 -- -- 21.8 501 -- -- -- -- 33.7 1,447

3-4 -- -- 25.4 529 -- -- 27.5 631 -- -- -- -- 28.2 1,211

5-6 -- -- 17.8 371 -- -- 19.8 453 -- -- -- -- 16.3 699

7+ -- -- 28.7 596 -- -- 30.9 709 -- -- -- -- 21.8 936
24 

Figure 4. Percentage HIV positive, percentage who had unsafe sex with last sex partner, and 

percentage who consumed alcohol at last sex, DHS surveys in sub-Saharan Africa, 2001-2014 

Table 9 shows the variables used in the regression analysis of men or women age 15-49 who had sexual 

intercourse in the past 12 months and who ever consumed alcohol or currently drink alcohol. The proportion 

of men who reported drinking at last sex was 13 percent in Lesotho and 25 percent in Zambia. 

Approximately 10 percent of women drinkers in Swaziland reported drinking at last sex compared with 14 

percent of women drinkers in Zambia. It is important to note that the frequencies are small. For example, 

in the Swaziland survey, after selecting for women who were drinkers and who had sex in the past 12 

months, only 29 of 299 women reported drinking at last sex. Unsafe sex among drinkers was highest for 

men in Lesotho and for women in Namibia and Swaziland (20-24 percent). Proportions in the highest 

alcohol frequency category (2+) were greater for men than for women in Namibia (57 percent and 31 

percent, respectively) and Zambia (54 percent and 46 percent, respectively) (see Table 9). 

 

31.1

21.1

19.7

18.0

16.9

15.1 14.5

13.1

11.3 10.9

8.3 8.0

4.3

6.0

17.2

21.1

19.3

10.9

8.8

14.5 15.2

12.9

10.7 11.2 11.8

1.5 1.9

8.2 8.4

3.4

9.3

2.6

11.8

13.3

1.6

6.8

0

5

10

15

20

25

30

35

HIV+ Unsafe sex with last sex partner Alcohol consumption at last sex
25 

Table 9. Variables used in the regression analysis for men or women age 15-49 who 

have had sexual intercourse in the past 12 months and have ever consumed alcohol or 

currently drink, DHS surveys in sub-Saharan Africa, 2006-2014 

 

Lesotho 

2009 

Namibia 

2013 

Swaziland 

2006-2007

Zambia 

2013-2014 

Men Women Men Women Women Men 

Variable % N % N % N % N % N % N 

Unsafe sex with last sex partner 

Yes 20.2 270 20.0 722 12.9 259 23.9 72 14.1 203 11.5 509

No 79.8 1,066 80.0 2,886 87.1 1,752 76.1 229 85.9 1,236 88.5 3,936

Age 

15-24 35.3 471 31.2 1,128 33.2 669 30.8 93 19.5 281 16.9 753

25-34 35.2 470 36.9 1,332 36.5 735 29.5 89 40.4 582 39.4 1,750

35+ 29.5 394 31.9 1,153 33.2 669 39.7 120 40.1 577 43.7 1,942

Locality by wealth 

Urban 33.0 440 59.5 2,151 59.2 1,192 42.0 127 59.9 861 50.0 2,225

Rural non-poor 36.8 492 16.8 608 17.3 349 27.4 82 11.4 164 15.1 670

Rural poor 30.2 404 23.6 854 23.5 472 30.6 92 28.7 414 34.9 1,551

Education level 

None or primary 58.0 774 22.2 801 28.5 574 42.1 127 54.2 780 45.6 2,025

Secondary or more 42.0 562 77.8 2,811 71.5 1,438 57.9 174 45.8 659 54.4 2,416

Alcohol frequency: Number of days drank 

alcohol in the last 3 months 

None 22.7 267 -- -- -- -- -- -- -- -- -- -- 

1-3 35.9 422 -- -- -- -- -- -- -- -- -- -- 

4-9 18.3 215 -- -- -- -- -- -- -- -- -- -- 

10-90 23.2 272 -- -- -- -- -- -- -- -- -- -- 

Alcohol frequency: In past 2 weeks 

None -- -- 51.5 1,808 30.5 605 -- -- -- -- -- -- 

1 -- -- 17.4 610 12.9 255 -- -- -- -- -- -- 

2+ -- -- 31.1 1,092 56.7 1,125 -- -- -- -- -- -- 

Alcohol frequency: how often do you drink 

Once month or less -- -- -- -- -- -- 60.1 178 -- -- -- -- 

Once a week -- -- -- -- -- -- 24.3 72 -- -- -- -- 

> Once week -- -- -- -- -- -- 15.6 46 -- -- -- -- 

Alcohol frequency: In past week 

None -- -- -- -- -- -- -- -- 38.7 547 18.2 804

1 -- -- -- -- -- -- -- -- 32.1 454 26.1 1,156

2+ -- -- -- -- -- -- -- -- 29.3 414 55.7 2,465

Alcohol consumption at last sex 

Yes 13.1 175 -- -- -- -- 9.7 29 14.1 203 25.4 1,127

No 86.9 1,161 -- -- -- -- 90.3 270 85.9 1,234 74.6 3,308

Lifetime number of sexual partners (women) 

1 -- -- 25.7 910 -- -- 14.0 39 30.1 428 -- -- 

2 -- -- 30.3 1,075 -- -- 20.3 57 29.0 413 -- -- 

3 -- -- 22.3 790 -- -- 25.8 72 19.7 280 -- -- 

4+ -- -- 21.7 767 -- -- 39.9 111 21.1 300 -- -- 

Lifetime number of sexual partners (men) 

1-2 20.4 256 -- -- 27.9 517 -- -- -- -- 19.6 863

3-4 27.3 343 -- -- 24.2 449 -- -- -- -- 31.7 1,394

4-6 18.6 235 -- -- 16.8 312 -- -- -- -- 19.7 865

7+ 33.7 424 -- -- 31.1 576 -- -- -- -- 29.0 1,275

3.3.2. Regression results 

3.3.2.1. Alcohol variables 

Table 10 summarizes the unadjusted and adjusted logistic regressions for unsafe sex, which include the 

general alcohol consumption variable (ever drank and currently drink), to examine global associations and 

the event-level variable: alcohol consumption at last sex. In general, the global association between alcohol 

consumption and unsafe sex appeared weak, especially for lifetime drinking status. Ever-drinking was not 

a significant predictor of unsafe sex in Lesotho and Namibia, and current drinking status was only 

significant among men in Zambia, where current drinkers were less likely to engage in unsafe sex compared 

with non-drinkers (OR 0.7, p <0.001). 
26 

The event-level analysis revealed that alcohol consumption at last sex was a significant predictor of unsafe 

sex among men in Lesotho (OR 1.8, p<0.01), men in Swaziland (OR 3.1, p<0.001), women in Zambia (OR 

1.8, p<0.001), men in Zambia (OR 1.9, p<0.001), and women in Uganda (OR 1.3, p<0.01). The results 

indicate that in these countries respondents who drank at last sex had higher odds of engaging in unsafe sex 

compared with respondents who did not drink at last sex. This variable was not a significant predictor 

among women in Swaziland, women and men in Kenya, women in Mozambique, and women and men in 

Zimbabwe. 

Table 10. Unadjusted (UA) and adjusted (AD) logistic regressions of unsafe sex for 

men and women age 15-49 who had intercourse in the past 12 months, DHS surveys 

in sub-Saharan Africa, 2001-2014 

 

Lesotho 

2009 

Namibia 

2013 

Swaziland 

2006-2007 

Zambia 

2013-2014 

Men Women Men Women Women Men 

Variable 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR AD OR

Age 

15-24 3.0** * 4.0*** 2.4*** 2.8*** 2.2*** 2.7*** 3.7*** 4.6*** 5.1*** 5.9*** 20.6*** 24.2***

25-34 1.3 1.4 1.5*** 1.6*** 1.8*** 1.9*** 1.5** 1.6*** 1.2 1.2* 3.0*** 3.2***

35+ Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Locality by wealth 

Urban Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Rural non-poor 4.5*** 3.5*** 1.5*** 1.6*** 1.3 1.1 1.1 1.2 0.8* 1.0 1.2 0.9 

Rural poor 5.5*** 3.9*** 1.6*** 1.7*** 1.7*** 1.4* 1.4** 1.3* 0.8* 1.0 0.9 0.8* 

Education level 

None or primary 3.3*** 3.0*** 1.2* 1.2* 1.6*** 1.8*** 1.3* 1.2* 0.5*** 0.7*** 0.9 1.3** 

Secondary or more Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Ever drank 

Yes 0.9 1.1 1.1 1.1 1.0 0.9 -- -- -- -- -- -- 

No Ref. Ref. Ref. Ref. Ref. Ref. -- -- -- -- -- -- 

Currently drink 

Yes -- -- -- -- -- -- 1.3 1.2 1.4*** 1.2 0.6*** 0.7***

No -- -- -- -- -- -- Ref. Ref. Ref. Ref. Ref. Ref. 

Alcohol consumption at last sex 

Yes 1.4 1.8** -- -- -- -- 1.0 1.3 1.8*** 1.8** 1.1 1.9***

No Ref. Ref. -- -- -- -- Ref. Ref. Ref. Ref. Ref. Ref. 

Lifetime of sexual partners (women) 

1 -- -- Ref. Ref. -- -- Ref. Ref. Ref. Ref. -- -- 

2 -- -- 1.2* 1.4*** -- -- 0.9 1.1 1.4** 1.5*** -- -- 

3 -- -- 1.4** 1.8*** -- -- 1.2 1.6*** 2.3*** 2.8*** -- -- 

4+ -- -- 1.4*** 1.9*** -- -- 1.4** 2.2*** 3.2*** 4.3*** -- -- 

Lifetime of sexual partners (men) 

1-2 Ref. Ref. -- -- Ref. Ref. -- -- -- -- Ref. Ref. 

3-4 1.3 1.5* -- -- 1.1 1.1 -- -- -- -- 0.8* 1.2 

4-6 1.2 1.4 -- -- 1.2 1.3 -- -- -- -- 0.8 1.5***

7+ 1.1 1.6** -- -- 1.4* 1.8** -- -- -- -- 0.9 1.8*** 

Observations 2,115 6,603 2,737 3,348 12,175 10,026

(Continued)
27 

Table 10. − Continued 

 

Kenya 

2008-2009 

Mozambique

2009 

Swaziland

2006-2007 

Uganda 

2001 

Zimbabwe 

2005-2006 

Women Men Women Men Women Women Men 

Variable 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR 

AD 

OR 

UA 

OR AD OR UA OR AD OR 

Age 

15-24 3.0*** 3.4*** 15.0*** 16.3*** 3.8*** 4.8*** 3.6*** 4.1*** 6.5*** 8.7*** 2.3*** 3.0*** 15.8*** 16.9*** 

25-34 1.1 1.1 3.6*** 3.6*** 1.1 1.2 1.7** 1.8** 1.5*** 1.6*** 0.7 0.8 2.1** 2.3*** 

35+ Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Locality by wealth 

Urban Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Rural non-poor 0.6*** 0.7* 2.1** 1.6 0.8 0.9 1.6** 1.4* 0.8** 1.0 0.8 0.8 1.5* 1.2 

Rural poor 0.6** 0.8 1.4 1.0 0.6*** 0.7* 2.0*** 1.4* 0.5*** 0.7*** 0.7 0.7 2.6*** 2.0*** 

Education level 

None or primary 0.8** 0.7** 1.7** 1.7* 0.7*** 0.7** 1.6*** 1.5** 0.6*** 0.8** 0.8 0.9 1.9*** 1.8*** 

Secondary or more Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Alcohol consumption at last sex 

Yes 1.8 1.2 0.9 1.6 1.5 1.3 2.9*** 3.1*** 1.0 1.3** 1.6 1.2 1.0 1.1 

No Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Lifetime number of sexual partners (women) 

1 Ref. Ref. -- -- Ref. Ref. -- -- Ref. Ref. Ref. Ref. -- -- 

2 1.3 1.3 -- -- 2.2*** 2.4*** -- -- 1.3** 1.3** 3.1*** 3.6*** -- -- 

3 1.7** 1.9*** -- -- 2.7*** 3.2*** -- -- 1.4*** 1.8*** 5.7*** 7.0*** -- -- 

4+ 2.9*** 3.8*** -- -- 3.1*** 4.0*** -- -- 1.6*** 2.7*** 7.8*** 10.2*** -- -- 

Lifetime number of sexual partners (men) 

1-2 -- -- Ref. Ref. -- -- Ref. Ref. -- -- -- -- Ref. Ref. 

3-4 -- -- 0.7 0.7 -- -- 0.6* 0.9 -- -- -- -- 0.6* 0.7 

5-6 -- -- 0.6 0.7 -- -- 0.8 1.1 -- -- -- -- 0.6** 0.7 

7+ -- -- 0.7 1.1 -- -- 0.8 1.2 -- -- -- -- 0.8 1.3 

Observations 5,926 2,137 7,454 2,333 14,329 5,819 4,201 

*** p<0.001, ** p<0.01, * p<0.05

Note: Five surveys (Kenya 2008-09, Mozambique 2009, Swaziland 2006-07, Uganda 2001, Zimbabwe 2005-06) do not have alcohol consumption questions but do 

have the question on alcohol use at last sex. 

Table 11 summarizes the same regressions for drinkers (ever drank or currently drink) only. The findings 

were consistent with those presented in Table 10. Alcohol consumption at last sex was again significant for 

men in Lesotho (OR 1.8, p<0.05) and women and men in Zambia (OR 3.3, p<0.001 and OR 1.7, p<0.001, 

respectively). For Zambian women, the magnitude of the ORs increased substantially for current drinkers. 

Among women in Swaziland, this variable remained non-significant. 
28 

Table 11. Unadjusted (UA) and adjusted (AD) logistic regressions of unsafe sex for men and 

women age 15-49 who have ever consumed alcohol or currently drink and have had sexual 

intercourse in the past 12 months, DHS surveys in sub-Saharan Africa, 2006-2014 

 

Lesotho 

2009 

Namibia 

2013 

Swaziland 

2006-2007 

Zambia 

2013-2014 

Men Women Men Women Women Men 

Variable UA OR AD OR UA OR AD OR UA OR AD OR UA OR AD OR UA OR AD OR UA OR AD OR

Age 

15-24 1.8** 3.4*** 2.0*** 2.6*** 1.7* 2.2*** 1.9* 2.8* 4.2*** 4.3*** 11.6*** 13.4***

25-34 1.1 1.3 1.5** 1.6*** 1.7** 1.8** 1.3 1.4 1.6* 1.5 2.6*** 2.7*** 

35+ Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Locality by wealth 

Urban Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Rural non-poor 4.0*** 3.5*** 1.5** 1.6*** 1.2 0.9 1.8 1.8 0.7 0.9 0.9 1.0 

Rural poor 4.8*** 3.2*** 1.7*** 1.8*** 1.7** 1.4 1.3 1.6 0.4*** 0.5** 0.5*** 0.8 

Education level 

None or primary 3.1*** 3.4*** 1.4** 1.4** 1.9*** 2.0*** 1.2 1.2 0.6* 1.2 0.7*** 1.0 

Secondary or more Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. Ref. 

Alcohol frequency: Number of days 

drank alcohol in the last 3 months 

None Ref. Ref. -- -- -- -- -- -- -- -- -- -- 

1-3 0.8 0.7 -- -- -- -- -- -- -- -- -- -- 

4-9 0.9 1.0 -- -- -- -- -- -- -- -- -- -- 

10-90 1.3 1.4 -- -- -- -- -- -- -- -- -- -- 

Alcohol frequency: In past 2 weeks 

None -- -- Ref. Ref. Ref. Ref. -- -- -- -- -- -- 

1 -- -- 0.9 0.9 1.0 1.0 -- -- -- -- -- -- 

2+ -- -- 1.0 1.0 1.3 1.3 -- -- -- -- -- -- 

Alcohol frequency: how often do you 

drink 

Once month or less -- -- -- -- -- -- Ref. Ref. -- -- -- -- 

Once a week -- -- -- -- -- -- 1.5 1.8 -- -- -- -- 

> Once week -- -- -- -- -- -- 1.3 1.4 -- -- -- -- 

Alcohol frequency: In past week 

None -- -- -- -- -- -- -- -- Ref. Ref. Ref. Ref. 

1 -- -- -- -- -- -- -- -- 0.8 0.7 0.7* 0.7* 

2+ -- -- -- -- -- -- -- -- 1.0 0.7 0.9 0.9 

Alcohol consumption at last sex 

Yes 1.6* 1.8* -- -- -- -- 1.5 2.8 2.8*** 3.3*** 1.7*** 1.7*** 

No Ref. Ref. -- -- -- -- Ref. Ref. Ref. Ref. Ref. Ref. 

Lifetime number of sexual partners 

(women) 

1 -- -- Ref. Ref. -- -- Ref. Ref. Ref. Ref. -- -- 

2 -- -- 1.3 1.4* -- -- 1.3 1.8 2.3* 2.1* -- -- 

3 -- -- 1.4* 1.7*** -- -- 1.1 1.5 3.3*** 2.5* -- -- 

4+ -- -- 1.5** 2.0*** -- -- 0.9 1.2 4.5*** 3.6*** -- -- 

Lifetime number of sexual partners 

(men) 

1-2 Ref. Ref. -- -- Ref. Ref. -- -- -- -- Ref. Ref. 

3-4 2.1** 2.4*** -- -- 0.9 0.9 -- -- -- -- 1.2 1.5 

4-6 2.2** 2.5** -- -- 1.1 1.2 -- -- -- -- 1.3 1.7** 

7+ 1.7* 2.0** -- -- 1.3 1.5 -- -- -- -- 1.7** 2.4*** 

Observations 1,087 3,319 1,708 285 1,281 4,241 

*** p<0.001, ** p<0.01, * p<0.05

Table 11 shows that the frequency of alcohol consumption was not a significant predictor of unsafe sex, 

after selecting for ever- or current drinkers, except among men in Zambia. In Zambia, the finding was not 

in the expected direction. Men who reported having one drink in the past week actually had lower odds of 

engaging in unsafe sex compared with men who did not drink (OR 0.7, p<0.05). Because the questions on 

general alcohol consumption were not asked in Kenya, Mozambique, Swaziland (men), Uganda and 

Zimbabwe, this analysis could not be conducted for these populations. 

 
29 

3.3.2.2. Other variables 

The strongest predictors of unsafe sex for all countries in this analysis appear to be age of respondent and 

lifetime number of sexual partners. This pattern was observed especially for the youngest age category (15-

24), for both men and women, and for women who had four or more lifetime sexual partners. As Table 10 

shows, respondents age 15-24 had higher odds of engaging in unsafe sex compared with those age 35 and 

older, for all countries. Among men, the odds ratio in Zambia was 24.2 (p<0.001), and in Kenya and 

Zimbabwe it was between 16 and 17 (p<0.001 for both ORs). The high risk of unsafe sex found in these 

younger age groups may be partially due to the large proportion of unmarried men and women. The odds 

ratios of women’s lifetime number of sexual partners increased with increasing number of sexual partners. 

In all countries, the highest category of lifetime number of sexual partners (four or more) had significant 

odds ratios compared with women with one lifetime partner, with the highest odds ratio for unsafe sex 

found for women in Zimbabwe (OR 10.2, p<0.001). High odds ratios tend to be observed for men and 

women with four or more lifetime partners in the remaining countries; the lowest odds ratio was for women 

in Namibia (OR 1.9, p<0.001). This predictor was not as strong for men, and was not significant for men 

in Kenya, Swaziland, or Zimbabwe. At the same time, however, men in Lesotho, Namibia, and Zambia 

who had seven or more lifetime partners had almost twice the odds of engaging in unsafe sex compared 

with men with one or two lifetime partners. 

For the remaining independent variables, not all countries shared the same direction for odds ratios. For 

example, the locality by wealth categories of rural poor and non-poor had higher odds of engaging in unsafe 

sex compared with urban in men in Lesotho, Namibia, Swaziland, and Zimbabwe. For men in Kenya, 

Mozambique, Uganda, and Zambia the odds were in the opposite direction. Similar differences between 

countries were also found for the education variable, as shown in Table 10. 

31 

4. Discussion 

4.1. Review of Findings 

This report reviewed survey questions and data related to alcohol consumption from DHS surveys. It 

provided an inventory of questions related to alcohol consumption, identified variations in questions and 

response categories, calculated prevalence of ever consuming alcohol, and examined the associations 

between both global and event-level alcohol use and unsafe sex. The inventory of alcohol-use related 

questions revealed substantial variation across surveys in both the types of questions asked and the response 

options. Among the 65 surveys included in the inventory, a total of 19 different non-comparable questions 

related to alcohol consumption were asked, and even similar questions had small variations in wording. In 

addition, when countries asked a comparable question, such as on frequency of drinking, different surveys 

used different response options. These inconsistencies impede multi-country comparisons. 

The inventory found that the most widely asked alcohol-related question was about ever having consumed 

alcohol. Tabulation of the responses showed a large range of prevalence of ever-drinking across countries 

and, in some areas, high rates of abstention. WHO has estimated that about 60 percent of the world’s 

population is lifetime abstainers; also, more women abstain than men, in line with the high rates of 

abstention found in this analysis, particularly among women (WHO 2014). Regionally, the highest 

percentages of having ever consumed alcohol are found in countries in Eastern Europe and Central Asia, 

again in line with estimates from WHO (2014). This report found that over 60 percent of men in Eastern 

Europe and Central Asia have ever drunk alcohol; however, the analysis included only five surveys in an 

interval of 13 years (1999-2012). Across all regions and countries, a higher percentage of men compared 

with women reported having ever consumed alcohol. The gap between men and women in alcohol 

consumption varies substantially among countries, from a difference of five percentage points in the 

Ukraine 2007 survey to 43 percentage points in the Guyana 2009 survey. Similar differentials in the 

prevalence of ever consuming alcohol across countries and between men and women have been reported 

by other studies (Rehm, Mathers, et al. 2009; WHO 2014). 

Several gender differences supported by the literature (Rehm, Mathers, et al. 2009; WHO 2014; WoolfKing and Maisto 2011) were noted in the analysis of unsafe sex in sub-Saharan Africa. First, men drink 

more than women. This was the case for general alcohol drinking status (ever or current drinking), 

frequency of alcohol consumption, and alcohol consumption at last sex. Second, the effects of general 

alcohol use on unsafe sex differ between men and women. For example, in Zambia, men who currently 

drink had significantly lower odds of engaging in risky sex (which was not in the expected direction). In 

contrast, women in Zambia who currently drink were more likely to engage in unsafe sex, although after 

controlling for other variables in the adjusted model, this relationship was no longer significant. Overall, 

the global associations of general drinking status (ever or current drinking and frequency of drinking) do 

not appear to be strong predictors of unsafe sex because drinking status and frequency of drinking were 

only found to be significant predictors of unsafe sex among men in Zambia.

The lack of significance in the statistical association between general drinking status and unsafe sex may 

be due in part to the measure of alcohol consumption being used. In Lesotho and Namibia, the question 

about drinking status was asked for ever-drinking, while in Swaziland and Zambia it was asked for current 

drinking. Despite the differences in the alcohol questions, after adjusting for other variables, a significant 

association was only found for Zambian men, among whom current drinkers were actually less likely to 

engage in unsafe sex compared to those not currently drinking. An association between ever having an 

alcoholic drink and current risky behavior is not expected, because ever drinking is not necessarily 

reflective of current drinking behavior, and does not indicate harmful drinking. The results showed that 

Lesotho and Namibia found no significant associations between ever drinking and unsafe sex in both the 
32 

unadjusted and adjusted regressions. It is possible that a better measure of current alcohol consumption, 

one that includes quantity as well as frequency, might have produced different results. 

For the event-level analysis in which alcohol consumption at last sex was examined as a predictor of unsafe 

sex, this association was only found in a few countries, and mainly for men. The findings of this report 

indicated that men in Lesotho, Zambia, and Swaziland, and women in Zambia and Uganda, had 

significantly higher odds of engaging in unsafe sex with their last sex partner if they consumed alcohol on 

that occasion. Many countries, however, did not show significance for alcohol consumption at last sex, 

including women and men in Kenya and Zimbabwe, and women in Mozambique and Swaziland. While the 

results vary by country, these findings imply that there are pathways and effects of alcohol on unsafe sex 

that differ by gender, as was found in several other studies (Woolf-King and Maisto 2011). In addition, 

because alcohol consumption at last sex is the only survey question on alcohol that is standardized and 

comparable across countries, these inconsistent findings suggest that a link between alcohol consumption 

and unsafe sex depends on the setting. 

This lack of consistent association between alcohol consumption and condom use was also found in a 

review by Weinhardt and Carey (2000), although the review did not include studies from sub-Saharan 

Africa. Among three event-level studies carried out with data from sub-Saharan Africa, one supports our 

findings (Kiene and Subramanian 2013) and two found a significant association between alcohol 

consumption at last sex and unprotected sex (Kiene et al. 2008; Myer, Mathews, and Little 2002). Both of 

the latter two studies, however, were conducted in South Africa and may not be generalizable to other subSaharan countries. In addition, the study by Kiene et al. (2008) only included participants who were HIVpositive, and therefore was not a sample of the general population. The lack of a consensus regarding the 

link between alcohol consumption at last sex and risky sexual behavior perhaps supports a third-variable 

explanation (Cooper 2002, 2006), which states that perhaps within-person variability is more important 

than between-person variability (Cooper 2010). Cooper (2006, p19) states that alcohol’s acute causal effects 

on sexual behavior are more variable than previously thought and “drinking can promote, inhibit, or have 

no effect on behavior, depending on the interplay of factors governing behavior in a particular situation”. 

Several studies in the literature use different outcomes to define risky sexual behavior. This analysis uses 

non-cohabiting partner type and nonuse of condom as the unsafe sex outcome; other studies may define the 

unsafe sex outcome differently. While Weiser et al. (2006) found that in Botswana alcohol consumption 

was a significant predictor of unprotected sex with a non-primary partner, the article did not describe exactly 

what is meant by non-primary partner and whether this includes boyfriend/girlfriend relationships. 

Similarly, Wieser et al. (2006) used unprotected sex with a non-monogamous partner as the unsafe sex 

outcome; however, again it is not clear whether this categorization includes boyfriend/girlfriend 

relationships. A review by Woolf-King and Maisto (2011) examined several global association studies of 

alcohol use with various outcomes including: HIV status (mixed findings), STI infection (mixed findings), 

sexual activity (significant positive association in a small number of studies), sex with multiple or casual 

partners (significant positive associations in several studies), unprotected sex regardless of partner type 

(significant positive associations in several studies), transactional sex (significant positive associations in 

several studies), and sexual coercion (significant positive associations in several studies). Other global 

association studies in sub-Saharan Africa found significant associations between general alcohol 

consumption and other measures of risky sexual behavior outcomes such as HIV infection (Woolf-King 

and Maisto 2011). A meta-analysis of the relationship between alcohol consumption and HIV infection in 

sub-Saharan Africa found a pooled OR (all studies) of 1.61 (95% CI: 1.44-1.80) for HIV infection regarding 

drinkers versus non-drinkers (Woolf-King et al. 2013). The odds of HIV infection were higher for those 

who reported drinking in sexual contexts (OR 1.79, CI: 1.55-2.06). It is important to note that some of the 

studies in the review by Woolf-King and Maisto (2011) included participants from sub-populations, such 

as workers from a specific industry (mining, food, recreation, bar, hotel, armed forces), men who have sex 
33 

with men, and male and female sex workers. These categories are not comparable with analysis of data 

from DHS household surveys. 

Partner’s drinking status may also play an important role in unsafe sex. The study by Kiene and 

Subramanian (2013) used DHS data from sub-Saharan countries to examine the association between 

drunkenness at last sex and condom use at last sex; for women in the study, drunkenness at last sex refers 

to partners’ drunkenness. The study grouped DHS countries into two regions (Southern Africa and East 

Africa), then analyzed the survey results for men and women. The results showed that male partner 

drunkenness at last sex significantly decreased the odds of condom use for men in Southern Africa but not 

for men in East Africa. Male partner drunkenness at last sex was only marginally significant (p=0.08) for 

women in Southern Africa (Kiene and Subramanian 2013). While the outcome variable used in the study 

was not the same as the one used in the present analysis—relationship type was not included in the outcome 

but was included as a covariate—and countries were grouped together for analysis, the results nevertheless 

support our finding of no significant associations between alcohol consumption at last sex and the unsafe 

sex measure for men and women in Kenya and Mozambique, and for women in Zimbabwe. Also, similar 

to the present analysis, Kiene and Subramanian (2013) found significant associations of alcohol 

consumption at last sex among men in Lesotho, Swaziland, and Zambia. When alcohol consumption at last 

sex in the present analysis was coded to match the variable used by Kiene and Subramanian (2013), i.e. 

male partner was drunk, the association with unsafe sex was still found for men in Lesotho and Swaziland. 

When the drunkenness status of the partner was used as a variable for the analysis of women’s unsafe sex, 

this was not found to be significant (results not shown). 

Among women in the present analysis, those in Swaziland reported the highest proportion of unsafe sex but 

also one of the lowest proportions of alcohol consumption, both at last sex and in general (in this case 

current drinking status). Because Swaziland has one of the highest levels of HIV prevalence for women, 

understanding the process through which women engage in unsafe sex requires further study; alcohol does 

not seem to be a factor for women in Swaziland. The same situation is seen for women in Mozambique, 

where almost 16 percent of women reported unsafe sex but only three percent reported alcohol consumption 

at last sex, which was a non-significant predictor of unsafe sex. 

4.2. Limitations 

A major strength of DHS data is the standardization of core questionnaires and formalized modules that 

allow for multi-country comparisons and trend analysis. The results of our inventory of DHS questions 

related to alcohol consumption, however, found that the alcohol questions are not standardized. This poses 

a substantial limitation to analysis of alcohol-related questions and data across countries. Conclusions about 

differences in alcohol consumption across countries or regions are limited to questions using the same 

wording and the same response options. The wording of questions on general alcohol consumption may 

also affect the findings (Bowling 2005; Schuman and Presser 1981). Additionally, type of question about 

alcohol use, frequency versus quantity, and other factors can affect associations between alcohol-related 

predictor variables and outcomes of interest. For example, the review of studies from sub-Saharan countries 

by Kalichman et al. (2007) found that, for people who drink, the quantity of alcohol consumed is a better 

predictor of risky sexual behavior than the frequency of drinking. The meta-analysis by Woolf-King et al. 

(2013) found that individuals whose drinking was suggestive of an alcohol-use disorder had almost twice 

the odds of being HIV-positive compared with non-drinkers. The present analysis of alcohol use and unsafe 

sex found that the variable measuring general alcohol consumption was only significant in the adjusted 

regression for men in Zambia. The frequency of alcohol consumption, as a predictor, was also only 

significant among Zambian men. More specific questions on alcohol consumption in a short-term time 

frame that includes frequency and quantity might improve the analytical value of indicators of drinking 

(Stockwell et al. 2004). 
34 

For this analysis, the use of alcohol-related questions is limited to the questions available in DHS surveys. 

Because the validity of the questions has not been studied, interpretations about the meaning of the results 

should be made with caution. It is unclear whether the questions measure what the analysis hopes they 

measure: a complete picture of alcohol consumption. For example, a response to a question about everdrinking does not necessarily warrant classification of a respondent as a drinker or non-drinker. A person 

may have consumed alcohol in the past but not drink currently. Similarly, asking if a person is a current 

drinker does not provide information about whether the person is a heavy, heavy episodic, moderate or light 

drinker. Perhaps due to the vagueness of the general alcohol questions, the analysis conducted in this report 

has shown no significant global associations between ever-drinking and unsafe sex (just two countries) and 

only one survey (out of two) found a significant association between current drinking and unsafe sex. 

Further, questions concerning drunkenness are subjective and open to differences of interpretation 

(Greenfield and Kerr 2008). Finally, standard drink sizes were only defined in a few surveys, which leads 

to potential differences in interpretation across cultures and countries in measuring quantity of alcohol 

consumed. The problem of measurement standardization is a challenge for screening alcohol use, 

particularly in areas where alcohol is brewed at home or locally; alcohol concentration is not regulated and 

drinks can vary substantially in terms of size and alcohol content (Hahn, Woolf-King, and Muyindike 

2011). Even in areas where alcohol is regulated and mass-distributed, descriptions of typical drink size and 

alcohol content vary from person to person and across regions (Greenfield and Kerr 2008). Therefore, 

lacking validation and standardization of the questions on alcohol consumption, conclusions cannot be 

stated with certainty, particularly in multi-country comparisons. 

Under-reporting is common in the collection of survey data on alcohol consumption, along with other 

sensitive topics such as risky sexual behaviors (Hahn et al. 2010; Minnis et al. 2009; Stockwell et al. 2004; 

Woolf-King and Maisto 2011). There are several reasons for under-reporting of alcohol consumption in 

population studies. First, heavy drinkers, because of their lifestyle, may not be present for, or may be unfit 

to participate in, a household survey (Stockwell et al. 2004). Perception of stigma or social desirability bias 

may cause respondents to under-report alcohol use in order to present themselves more favorably to the 

interviewer (Bowling 2005; Greenfield and Kerr 2008; Hahn et al. 2010; Hawkins et al. 2007). Hahn et al. 

(2010) used biomarker testing and, based on the test results and sensitivity of the test, determined that an 

estimated 15 percent of self-reported abstainers actually tested positive for consuming at least 3.5-6 drinks 

daily, or almost daily, for at least the past 14 days. Under-reporting may be particularly pertinent regarding 

women’s self-reported data on behavior related to sexual risk taking and alcohol use. A randomized control 

trial by Minnis et al. (2009) found that among HIV-negative women in Zimbabwe, who were surveyed 

using both self-administered questionnaires and face-to-face interviews, there was a discrepancy in the 

measures of semen exposure and self-reports of unprotected sex. The study found that tests of almost half 

of the women who reported no recent sexual intercourse, or reported using a condom at recent sex, indicated 

biological evidence of semen exposure (Minnis et al. 2009). These results and similar findings from other 

studies indicate potential social desirability bias in reports of unsafe sex (Gallo et al. 2006; Gallo et al. 

2007). Finally, respondents may unintentionally misreport their behavior, particularly alcohol intake. The 

problem may be due in part to respondents’ difficulty recalling accurately the exact amount of alcohol 

consumed, particularly when survey questions ask about consumption over periods longer than a week. 

This type of misreporting typically results in under-reporting and often occurs when reporting socially 

unacceptable behaviors such as heavy drinking (Greenfield and Kerr 2008; Leigh and Stall 1993; Stockwell 

et al. 2004). 

A limitation of global association studies in which alcohol consumption in general is used to predict unsafe 

sex is that one does not know if the alcohol consumption and the unsafe sex occurred on the same occasion. 

Event-level analyses using alcohol consumption at last sex are also required (Leigh and Stall 1993). Another 

limitation of the present analysis is the inability to conduct a within-person analysis for the association of 

alcohol with unsafe sex. A within-person analysis can inform us whether a certain individual will exhibit 

the same behavior sober that they exhibit under the influence of alcohol. This type of analysis can control 
35 

for any third-variable explanations (Cooper 2002, 2006) such as changes in personality, the situation, or the 

relationship context, according to Cooper (2010). Finally, since DHS studies are cross-sectional, it is not 

possible to establish causality. In fact, it is often unclear whether alcohol consumption is a cause or a result 

of unsafe sex. 

4.3. Considerations for Future Research 

Given the interest in studying the nuances of alcohol consumption—as evidenced by the variety of questions 

included in DHS surveys—the authors suggest the inclusion (in a DHS optional module) of a standardized 

set of questions on this topic that draw from a validated scale. These questions can be used to explore other 

associations in DHS data with outcomes of interest. The use of validated scales such as AUDIT-C in similar 

studies has been supported by experts in the field (Chersich and Rees 2010; Weiser et al. 2006; Woolf-King 

et al. 2013). Alcohol screening methods attempt to identify different aspects of alcohol consumption that 

can directly affect health: past versus current, hazardous, harmful, or dependent drinking2

 (Saunders et al. 

1993). The Alcohol Use Disorders Identification Test (AUDIT) was developed to identify heavy drinking, 

alcohol abuse, and alcoholism (Babor et al. 2001; Saunders et al. 1993). Although subjects tend to 

underestimate alcohol consumption when responding to the questions in AUDIT, it is still a valuable proxy 

for assessing heavy drinkers (Bradley et al. 1998). The authors of AUDIT incorporated categorical response 

options in an attempt to minimize under-reporting (Saunders et al. 1993). While evidence from this and 

previously mentioned studies demonstrates that event-level research on alcohol use produces stronger 

associations with recent risky sexual behavior, standardized, general alcohol-related questions could be 

used to examine other less-studied outcomes associated with alcohol-use in LMICs. For example, alcoholuse could be studied in relation to DHS data on reproductive health or maternal and child health outcomes. 

AUDIT-C has been validated in a number of developed countries in Europe, the Americas, and Asia 

(Reinert and Allen 2007). Only the full 10-item version has been validated in developing countries, but an 

abbreviated three-question version has been shown to maintain high levels of sensitivity and specificity for 

identifying heavy drinking across ethnic groups (Bush et al. 1998; Reinert and Allen 2007). AUDIT-C 

poses questions on frequency of drinking in the past year, how much is typically consumed, and how often 

the respondent has had six or more drinks on one occasion. Table 12 presents the questions, responses, and 

scoring information for AUDIT-C. Points are assigned based on responses to each question and are summed 

to obtain a total score. The range of possible scores is zero to twelve. Hazardous drinkers are identified by 

a score of four or more for women and five or more for men (Bradley et al. 1998; Rumpf et al. 2002). While 

this may prove to be difficult in certain settings, the authors of AUDIT recommended clarifying the 

definition of a standard drink, which they note is approximately 10 grams of pure ethanol, or one 330 ml 

bottle of beer, 140 ml of wine, or 40 ml of liquor (Babor et al. 2001). The use of AUDIT-C questions could 

produce a more accurate description of alcohol consumption compared with the current alcohol questions 

used in DHS surveys. It would also create a standardized measure that could be used to compare alcohol 

consumption and its effects across countries. 

 

 

2

 This paper uses WHO’s previous definitions of alcohol use. Hazardous drinking is defined as alcohol use that carries 

the risk of harm whereas harmful use is defined as the presence of existing complications. Dependence is defined as 

“a cluster of cognitive, behavioral and physiologic symptoms that indicate a person has impaired control of 

psychoactive substance use and continues use of the substance despite adverse consequences” (Babor et al. 1994). 
36 

Table 12. AUDIT-C Questionnaire and Scoring* 

Q1: How often did you have a drink containing alcohol in the past year? 

Answer Points 

Never 0 

Monthly or less 1 

Two to four times a month 2 

Two to three times a week 3 

Four or more times a week 4 

Q2: How many drinks did you have on a typical day when you were drinking in the past 

year? 

Answer Points 

None, I do not drink 0 

1 or 2 0 

3 or 4 1 

5 or 6 2 

7 to 9 3 

10 or more 4 

Q3: How often did you have six or more drinks on one occasion in the past year? 

Answer Points 

Never 0 

Less than monthly 1 

Monthly 2 

Weekly 3 

Daily or almost daily 4 

*

Points from each question are summarized to create a score with a range from 0 to 12. Typical cut 

points for hazardous drinkers are 4 or more for women and 5 or more for men. 

Screening instruments are less reliable for the general population compared with clinical settings because 

they are intended to identify individuals with a potential alcohol-use problem, who are then referred for 

additional testing (Rumpf et al. 2002). When such instruments are used in a population study, results should 

still be interpreted carefully and with cultural context in mind. For example, in countries where abstention 

is common, as in Muslim countries, low levels of alcohol consumption could be perceived as socially 

unacceptable. In countries where drinking is more common, the same low levels of alcohol consumption 

may be perceived as socially acceptable. The boundary between acceptable drinking and heavy drinking 

may be more rigid in countries with low drinking prevalence, resulting in a lower threshold for heavy or 

harmful drinking. Thus, population studies should consider the overall prevalence of drinking when 

interpreting scores, particularly in countries with low drinking prevalence. 

Depending on interest in DHS countries, a survey question on alcohol consumption at last sexual 

intercourse would be useful for the continued study of unsafe sex. The question could lead to better eventlevel data for describing a potential link between alcohol consumption and unsafe sex. 
37 

5. Conclusion 

Heavy use of alcohol can harm individual health, cause public health problems, and have negative social 

and economic consequences. It can cause immediate harm not only to the individual and associated persons 

in his/her social context, but also can contribute to non-communicable and infectious diseases such as 

cancer, HIV, and tuberculosis. Thus, knowledge of the magnitude of abstainers versus drinkers in a 

population, and the extent of alcohol consumption among those who drink, is important information for 

decision-makers at the national level. It is possible to at least estimate the proportion of heavy drinkers in 

a population based on the prevalence of abstention and drinking, and on per capita consumption data. 

Among those who do drink, WHO found that 16 percent are heavy episodic drinkers, indicating harmful 

drinking (WHO 2014). However, without further information of drinking patterns, per-capita estimates of 

consumption, particularly estimates based solely on abstention rates, will underestimate the amount 

consumed among those who drink and mask the true prevalence of heavy drinkers (Peltzer and Ramlagan 

2009; WHO 2014). The large variation in ever-drinking found in this report encourages a deeper 

investigation of drinking patterns and the characteristics of those who consume alcohol. 

The analysis of alcohol as a predictor of unsafe sex revealed that questions on global alcohol consumption, 

as currently asked in DHS surveys, were not significant predictors of unsafe sex in all the countries included 

in the analysis. This situation is perhaps due in part to the lack of a comprehensive picture of alcohol use at 

the individual level. Currently, no set of questions in any DHS survey fully gauges harmful drinking--which 

includes frequency, quantity, and objective measures of heavy drinking--in the way validated scales do. In 

this analysis, however, an important predictor of unsafe sex was alcohol consumption at last sex because, 

in some countries and among some groups of men or women, the consumption of alcohol at last sex was 

linked to unsafe sex. 

This paper presents examples of how questions related to alcohol use in DHS surveys can be analyzed. It 

also shows how validated questions on alcohol use can be used to examine alcohol use as a risk factor for 

other demographic and health issues covered in DHS surveys such as household wealth, employment, 

reproductive health, maternal health, child health, domestic and sexual violence, and non-communicable 

diseases. Understanding the commonalities among those who drink alcohol can inform interventions 

capable of arresting or ameliorating the negative consequences of drinking. Several studies have examined 

the characteristics of people who are susceptible to alcohol over-use and found many varying and 

intertwined characteristics. These include societal variables such as cultural context, economic 

development, legal policies or availability of mass or locally produced alcohol, as well as individual 

variables, such as socioeconomic status (Babor 2010). Currently, as reported in this and other studies, more 

women than men abstain from drinking, although alcohol use among women is on the rise because of 

changes in women’s economic situation and social equality (Martinez et al. 2011; Rehm, Mathers, et al. 

2009; WHO 2014; Wilsnack, Wilsnack, and Kantor 2014). With the wide range of acknowledged 

consequences of alcohol abuse (including unsafe sex) and with use of alcohol on the rise in developing 

countries, there is a global responsibility to monitor alcohol consumption for harmful use. Adopting a 

standardized set of questions, such as a brief validated scale like AUDIT-C, would allow researchers to 

monitor alcohol consumption and make multi-country comparisons that inform policy decisions and focus 

interventions where most needed. 

 

39 

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