Prevalence and correlates of alcohol consumption during pregnancy in Georgia: Evidence from a national survey

Abstract

Background: While alcohol consumption is pervasive in the country of Georgia, the extent of alcohol consumption among pregnant women is yet to be examined. The goal of this study is to examine prevalence and correlates of alcohol consumption during pregnancy in Georgia. Methods: Using data from the World Health Organization’s Stepwise approach to noncommunicable disease risk factor surveillance in Georgia, this study examined prevalence and sociodemographic correlates of alcohol use among pregnant women in Georgia. The study sample of reproductive age (18-45) women was drawn from the STEPS, which is a large and nationally representative survey of adults with a 95% participation rate. Frequencies, multivariate analyses and related statistics were computed to describe and study associations among the target population and the odds of alcohol consumption during pregnancy. Results: Only 66 individuals in the sample were pregnant. About 13% of pregnant women consumed alcohol in the past 30 days and nearly 70% of them engaged in binge drinking on at least one occasion. Pregnant women who were young, married, homemakers, living in two-member households and in the lowest bracket of monthly income had the highest likelihood of consuming alcohol and binge drinking. The study results were statistically significant (p< .05). Conclusions: This study reveals the magnitude of alcohol consumption and binge drinking among reproductive age women in Georgia. This study also shows prevalence and correlates of alcohol consumption during pregnancy in Georgia. The results identify characteristics of women who are most likely to use alcohol during pregnancy. Given that, alcohol use is a modifiable behavioral risk factor, the findings in this study provide the foundation for evidence-based prevention strategies that target pregnant and reproductive age women.

Full text

The Worst Drug Epidemic in US History
Representative Matt Baker, Chairman, Health Committee, Pennsylvania House of
Representatives
Since 2000, 500,000 deaths in the U.S. have occurred due to drug abuse; one person
approximately every 20 minutes. According to new data released by the Centers for Disease
Control (CDC) there were 52,404 total deaths in 2015, or 144 drug overdose deaths per day. This
number is up 11.4 percent in just one year—from 129 a day in 2014.
In 2015 in Pennsylvania, per the Pennsylvania Coroner’s Report, there were 3,505 overdose
deaths. The number of overdose deaths exceeds those caused by car accidents and guns
combined. Thus, the greatest public health threat in Pennsylvania is drug addiction and related
overdose deaths.
The number of deaths in 2015 is a 30 percent increase over 2014, which represents the largest
increase in a decade. On average, in Pennsylvania, 10 people die every day from drug poisoning
and that number is probably low given the gaps in reporting. Eighty-one percent of those deaths
involved opiates, and the vast majority of those who died had more than one drug in
their system.

Growth in hospitalizations for heroin overdoses between 2000 and 2014 showed a 509 percent
increase per the Pennsylvania Heath Care Cost Containment Council. The rural 10-county, north-
central region has the state’s largest percentage increase.
History of the opioid problem
Opioid addiction cuts across all age groups, economic sectors and racial demographics. The use,
overuse, and abuse costs the Commonwealth more than $12.2 million in hospitalization costs
annually as of 2012, per the Pennsylvania Health Care Cost Containment Council. According to
the U.S. Surgeon General, the economic impact of drug and alcohol misuse and addiction across
the nation amounts to $442 billion each year – topping diabetes at $245 billion. One in seven
individuals in the United States will face substance addiction, while only 10 percent of those
addicted receive treatment.
In the last 20 years the dramatic rise in use of opioids can be traced to the inclusion of pain as a
vital sign. Unlike other vital signs which can be externally monitored by medical devices pain is
subjective, and it relies on patient’s self-reporting on a 1 to 10 pain scale.
The use of prescription painkillers has exploded. The U.S. consumes 80 percent of all opioids
globally, despite only having 5 percent of the world population. 1
More than 250 million prescriptions for painkillers were written in 20122 and prescriptions for
opioids have quadrupled from 1999 to 2010.3 Pennsylvania ranks 21st in the U.S. on the number
of prescriptions written for opioids with 88.2 prescriptions per 100 persons.4 Twenty to 30

percent of those opioids prescribed for pain are being misused, including providing them to
others.5 Fifty-three percent of persons 12 and older have received a prescription opioid from a
friend or family member for free for nonmedical purposes.6
Heroin-related overdose deaths in Pennsylvania
Based on Pennsylvania Corners Association (PCA) reports in 43 counties, heroin and heroin-
related deaths have been on the rise for the past five years (PCA, 2013). Between 2009 and 2013,
there were 2,929 heroin-related overdose deaths identified by county coroners. Of these, 490 (17
percent) were heroin only, while 2,439 (83 percent) involved multiple drugs.
Other drugs commonly found along with heroin overdose include other opiates such as
methadone, oxycodone, fentanyl, morphine, codeine, tramadol; other Illegal drugs such as
marijuana, cocaine; other sedating drugs such as alcohol and benzodiazapines; and
antidepressant medications such as Prozac, Celexa, Remeron, trazadone and Zoloft.
The number of deaths where an opioid prescription is solely responsible is difficult to determine.
There routinely is confusion or they are reported with heroin overdoses. The CDC reports the
number of opioid and heroin overdoses combined caused over 27,000 deaths in 2014.
Pennsylvania now leads the nation in drug overdoses among men aged 12 to 25 and is ninth in
the country for overdose deaths across the general population. Deaths due to an opioid overdose
are most likely to impact middle-class white males, ages 25 and 54.

Drug Related Overdose Deaths in Pennsylvania

Drug Related Overdose Deaths in Pennsylvania
[DEA, 2016]

Fifty-six percent of overdoses are among men.7 In 2015, Pennsylvania men represented two-
thirds of overdose deaths. Deaths in adults aged 55 to 64 have increased seven-fold from 1999 to
2013.8 Deaths in women have increased 400 percent since 1999.9 Of the overdose
hospitalizations in Pennsylvania, 28 percent are within the 50 to 59 age group.10 Annual costs of
prescription opioid abuse for the country are estimated at $55 billion.12
The link between opioids and heroin
Opioids and heroin are from same derivative product. The U.S. has seen a dramatic increase in
heroin use that statistically parallels the use of opioids. Nearly half of young people who inject
heroin reported abusing prescription opioids before starting heroin. Some individuals reported
taking up heroin because it’s cheaper and easier to obtain than prescription opioids.13
States that have enacted a prescription drug monitoring data base, such as our ABC-MAP, have
seen dramatic increases in heroin use immediately after implementation of the monitoring
program due to a decrease in access to opioids.
The U.S. has experienced a 63 percent increase in the use of heroin from 2002 to 2013,14 a 26
percent increase in heroin overdoses from 2013 to 2014,15 with more than 800 people dying in
Pennsylvania due to a heroin overdose in 2014.16

Pennsylvania’s strategy
There have been four areas of focus in Pennsylvania’s strategy to battle these drug issues.
Address the growing problem without eliminating access to legitimate users by 1) using
system innovations such as patient review and restriction programs, treatment options, including
medication assisted treatment, and a rapid response project; 2) including technology advances
including abuse-deterrent technologies for medications, the incorporation of ABC-MAP and
electronic health records, and interstate data sharing on ABC-MAP data; 3) practicing
innovations related to rethinking treating pain with methadone, insurance and MA coverage for
alternative pain management, and continuing education for providers, both in detection of
addiction and appropriate pain treatment; and 4) enhancing public education regarding the
appropriate use of opioids and parental detection of abuse of opioids.
Legislative initiatives have revolved around the PA Heroin, Opioid Prevention and Education
(PA-HOPE) Caucus, a bipartisan group of legislators working to address the growing opioid
epidemic, and the House Policy Committee holding public hearings across the state to gain facts.
The Pennsylvania House of Representatives formed a House Task Force and Advisory
Committee and proposed a series of bills designed to proactively address the growing opioid
epidemic during the 2015-16 session.
Five bills were introduced and successfully signed into law before the end of the 2015-16 session
that set a seven-day limit on the discharge prescription of opioids in emergency departments;

provide for the proper disposal of unused prescriptions and over-the-counter medications; require
prescribers and dispensers to obtain education in pain management, identification of addiction
and the use of opioids; prohibit prescribing an opioid to a minor, with certain limitations, for
more than seven days; and require the state boards of Dentistry, Medicine, Nursing, Optometry,
Osteopathic Medicine and Podiatry to create a safe opioid prescribing curriculum to be offered in
medical schools across Pennsylvania by August 2017, and direct the Department of Health to
establish a form for a patient to complete which will opt the patient out of being offered opioids.
Furthermore, Act 191 of 2014 (known as the Achieving Better Care by Monitoring All
Prescriptions Program-- (ABC-MAP) Act) is a prescription drug monitoring program intended to
increase the quality of patient care; give prescribers/dispensers access to patient's prescription
medication history; provide an electronic system that will alert medical professionals to potential
dangers for purposes of making treatment determinations; give patients an easily obtainable
record of their prescriptions so they can make educated and thoughtful health care decisions; and
aid regulatory and law enforcement agencies in the detection and prevention of fraud, drug abuse
and the criminal diversion of controlled substances. It became functional August 25, 2016.
Act 37 of 2016 was also enacted to prevent further spread of substance abuse through precursor
drugs. It amends the Controlled Substance, Drug, Device and Cosmetic Act and provides the
Pennsylvania Department of Health with authority to control the schedules and regulations of
controlled substances, liquefied ammonia gas, precursors and chemicals. It also allows the
Secretary of Health to temporarily reschedule controlled substances to a higher schedule, works
to prevent widespread use of substances potentially harmful/fatal to the public and allows

quicker prosecution of those engaged in manufacture, distribution and sale of designer
illegal drugs.
As government leaders, we also must expand our understanding of drug abuse to include new
hybrids, many of which when mixed with opioids, and are resistant to the lifesaving medication
Naloxone. They can cause death at even microscopic doses. For instance W-18 and Carfentanil
are 10,000 times more powerful than morphine and 100 times more powerful than Fentanyl. Law
now allows the Secretary of Health to protect the public by having the authority to temporarily
declare a “designer drug” an illegal drug, make changes and notify the public 30 days before
the rescheduling takes effect. The rescheduling remains in effect for one year and the Secretary
can work with the attorney general and the regulatory process to get the substance
permanently scheduled.
We still have much work to do in order to address this growing epidemic; however, I
am encouraged we will continue to make great strides in the fight due to the dedicated
cooperation of the governor, state and local elected leaders, and both the law enforcement and
medical communities.

References
1. Joint State Government Commission Report of the Task Force and Advisory Committee
on Opioid Prescription. Drug Proliferation, June 2015. (Herein referenced as the JSGC
Report.)
2. National Conference of State Legislatures (NCSL), American Epidemic: Overdosed on
Opioids, April 1, 2016.
3. Who is Responsible for the Pain-Pill Epidemic?. Celine Gounder, The New Yorker,
November 3, 2013.
4. JSGC Report
5. JSGC Report
6. JSGC Report
7. JSGC Report
8. JSGC Report
9. JSGC Report
10. PHC4 Research Brief “Hospitalization of Overdose of Pain Medication and Heroin”
2016.
11. PHC4 Research Brief.
12. NCSL, American Epidemic: Overdosed on Opioids, April 1, 2016.
13. National Institute of Health, National Institute on Drug Abuse, Drug Facts: Heroin,
October 2014.
14. NCSL, American Epidemic: Overdosed on Opioids, April 1, 2016.
15. NCSL, American Epidemic: Overdosed on Opioids, April 1, 2016.
16. Pennsylvania State Coroners Association, Report on Overdose Death Statistics 2015.

About the Author
Matt Baker is currently serving his 13th term in the Pennsylvania House of Representatives,
representing all of Tioga County and parts of Bradford and Potter counties. He has more than 35
years of knowledge and experience of public service and state government with him as a
state representative.
In the House, Baker serves as majority chairman of the House Health Committee and is a
member of the Rules Committee. Representative Baker has been recognized by many
organizations for his many accomplishments during his tenure including legislation to combat
the spread of substance abuse.
Conflict of Interest
I declare that I have no proprietary, financial, professional or other personal interest of any
nature or kind in any product, service and/or company that could be construed as influencing the
position presented in, or the review of, the manuscript entitled The Worst Drug Epidemic in
US History.

1
Prevalence and Correlates of Alcohol Consumption During Pregnancy in
Georgia: Evidence from a National Survey
By Manouchehr Mokhtari, Ph.D.; Anthony Kondracki, MD, MPH; Lasha Kavtaradze, Ph.D.;
Jacqueline Wallen, MSW, Ph.D.; Mamak Ashtari, MBA; Gvantsa Piralishvili, MD, Ph.D.;
Marina Topuridze, MD; Khatuna Todadze, MD; Lasha Kiladze, MD; Nino Gachechiladze, MS.
Abstract
Background: While alcohol consumption is pervasive in the country of Georgia, the extent of
alcohol consumption among pregnant women is yet to be examined. The goal of this study is to
examine prevalence and correlates of alcohol consumption during pregnancy in Georgia.
Methods: Using data from the World Health Organization’s Stepwise approach to
noncommunicable disease risk factor surveillance in Georgia, this study examined prevalence and
sociodemographic correlates of alcohol use among pregnant women in Georgia. The study sample
of reproductive age (18-45) women was drawn from the STEPS, which is a large and nationally
representative survey of adults with a 95% participation rate. Frequencies, multivariate analyses
and related statistics were computed to describe and study associations among the target
population and the odds of alcohol consumption during pregnancy.

2
Results: Only 66 individuals in the sample were pregnant. About 13% of pregnant women
consumed alcohol in the past 30 days and nearly 70% of them engaged in binge drinking on at
least one occasion. Pregnant women who were young, married, homemakers, living in two-
member households and in the lowest bracket of monthly income had the highest likelihood of
consuming alcohol and binge drinking. The study results were statistically significant (p< .05).
Conclusions: This study reveals the magnitude of alcohol consumption and binge drinking among
reproductive age women in Georgia. This study also shows prevalence and correlates of alcohol
consumption during pregnancy in Georgia. The results identify characteristics of women who are
most likely to use alcohol during pregnancy. Given that, alcohol use is a modifiable behavioral risk
factor, the findings in this study provide the foundation for evidence-based prevention strategies
that target pregnant and reproductive age women.
Keywords: alcohol consumption; pregnancy; women; risk factors; Georgia.
Introduction
Alcohol consumption during pregnancy has been widely proclaimed as a significant public health
problem in many countries (Bhuvaneswar et al., 2007). However, despite its recognition as the
oldest wine country in the world, there is scant evidence on alcohol consumption during pregnancy
in the country of Georgia (Mokhtari et al, 2016). In other words, alcohol use by pregnant women
in Georgia is yet to be characterized and/or assessed in a systematic study. Thus, there is no
evidence-based analysis that may inform policy makers targeting alcohol use by pregnant women
in Georgia. Nonetheless, recent evidence on adults aged 18-65 indicates an escalation in
prevalence of drinking from 11% in 2003 to 30% in 2010 (Mokhtari et al., 2016). Using 2010 data
from the World Health Organization’s (WHO’s) Stepwise approach to noncommunicable disease

3
risk factor surveillance in Georgia (STEPS, 2010), this study aims to investigate prevalence and
correlates of alcohol consumption during pregnancy in Georgia.
Alcohol use in pregnancy may lead to miscarriage, stillbirth and fetal alcohol spectrum (FAS)
disorders in children manifested by lifelong physical, behavioral and intellectual disabilities
(Naimi et al., 2003; Patra et al., 2011). In addition to pre- and postnatal adverse health effects,
alcohol intake in pregnancy significantly contributes to a rising rate of the noncommunicable
diseases worldwide and high economic costs (Bouchery et al., 2011; CDC, 2014; Flak et al., 2014;
Green et al., 2016; Lim et al., 2012; Rehm et al., 2010; Tan et al., 2015; USDHHS, 2005; WHO,
2014). Fetal in utero exposure to maternal alcohol increases risk of developing a congenital
disorder known as fetal alcohol syndrome marked with facial anomalies, poor growth and
cognitive and behavioral problems in children, which is the most debilitating form of fetal alcohol
spectrum disorders (Balachova et al., 2012; Flak et al., 2014; Green et al., 2016). While there are
no estimates for Georgia, evidence shows that prevalence of FAS and Fetal Alcohol Spectrum
Disorders (FASD) in the United States is 6 to 9 cases and 24 to 48 cases per 1000 children,
respectively (May et al., 2014).
Binge drinking, particularly in early pregnancy, is found to be associated with hyperactivity and
attention disorders in children (Sayal et al., 2014). Research has not reached consensus on a
minimal harmful dose of maternal alcohol on developing fetus in a dose-response relationship.
Abstinence from all types of alcohol, including wine and beer, is currently deemed essential in
pregnancy. In 2014, the Centers for Disease Control and Prevention (CDC) and the National
Center on Birth Defects and Developmental Disabilities reaffirmed that there is no safe time to
drink and no safe amount of alcohol intake during pregnancy (CDC, 2014). Alcohol use and binge
drinking in pre-pregnancy is a strong predictor of continued drinking during pregnancy

4
(Skagerstrom et al., 2011), and preconception counselling has been recommended for all
childbearing age women in the United States (Floyd et al., 1999). Unfortunately, no data on the
women use of alcohol prevention or treatment services exist for Georgia at this point. This
provides further impetus for the goal of this study, which is providing baseline evidence on
prevalence and correlates of alcohol consumption during pregnancy in Georgia.
Alcohol consumption in Georgia exceeds global per capita intake by 24%. Georgia’s alcohol
consumption is 45% higher than that of Armenia and 335% higher than that of Azerbaijan, its two
neighboring countries (WHO, 2014). In Georgia, wine is a preferred alcoholic beverage by both
males and females. About 5% of Georgian women believe that alcohol is advantageous for health
(Pomerleau et al., 2008). While cultural factors have always played a significant role in Georgia,
the complexity of contextual social factors and political and economic turmoil linked to the post-
soviet era transformation may contribute to the overall sustained psychological stress and changing
drinking habits among women (Hinote et al., 2009; Jukkala et al., 2008; Peele & Brodsky, 1996).
One could argue that demands of women, related to the traditional gender role as housewives and
guardians of children, have been changing and drinking and binge drinking is used as means of
gaining identity and stress reduction. Overtime, society’s drinking culture may be becoming more
tolerant to women who drink. It is hypothesized that increasing prevalence of drinking and binge
drinking among women in Georgia will predict a similar pattern of drinking during pregnancy that
will include homemakers and married women.
For the most part, in spite of an existing problem, alcohol use by pregnant women in Georgia has
not been adequately assessed in systematic studies. Unlike in developed countries where health
monitoring and national health surveys are routinely conducted, the paucity of statistical data in
Georgia hinders investigation of critical effects of excessive alcohol use in different groups of

5
population. The recent World Health Organization project called WHO STEPwise Approach
(STEPS) has offered assistance and opportunity to raise database and develop national health
surveillance system in countries like Georgia to be used for international comparisons of
noncommunicable disease risk factors (STEPS, 2012; STEPS Manual, 2015; Ustun et al., 2003).
The large WHO STEPS Georgia Survey was piloted in 2010 and has initiated a nationwide
collection of data on essential sociodemographic, economic information and health indicators such
as frequency and quantities of alcohol use in adult population (STEPS, 2012). The objective of this
study is to investigate prevalence and correlates of alcohol consumption during pregnancy
in Georgia.
Methods
Study Data
The source of a sample used in this study was the World Health Organization’s Stepwise (WHO
STEPS) approach to noncommunicable disease risk factor surveillance in Georgia. The WHO
STEPS provides the framework, instruments, and guidelines for collecting comparable health
related data in various countries. By focusing on the noncommunicable disease (NCD) risk factors,
the WHO STEPS’ Instrument covers three different levels or 'steps' of risk factor assessment and
several optional modules: Step 1 (questionnaire), Step 2 (physical measurements) and Step 3
(biochemical measurements) are the basic components of the WHO STEPS’ approach in this
respect. There are also optional modules that cover: mental health/suicide, oral health, sexual
health, tobacco policy, and violence and injury. The questionnaire in each case includes guidelines
and background information on the intent of each question and/or measures to be collected by
implementing the instrument. This allows interviewers to supply relevant information and/or
response to the participant’s requests for clarification about any particular issue.

6
The WHO STEPS Georgia Survey (STEPS, 2010) focused on survey of chronic disease risk
factors in Georgia was carried out from August to December 2010. The WHO STEPS Georgia
survey consists of a multi-stage, clustered sample design that yielded representative data for adults
aged 18-64 in Georgia. A total of 6,497 adults participated in the Georgia STEPS survey. Georgian
data is comparable to other survey data that are collected according to international best practice.
With a participation rate of 95%, the WHO STEPS Georgia Survey or sample represents a total of
more than two million (2,166,687) adults aged 18-65 years old, including 1,090,231 males and
1,076,456 females. Among females, there were 693,910 (64.46%) observations on childbearing
age women (18-45 years old) and 29,862 (4.30%) pregnant women respondents. A series of
questions related to alcohol use captured the main observations on the variables of interest in this
study. For example, the instrument included the following standard questions about alcohol use by
the adults who participated in survey:
Have you ever consumed alcohol?
Consumed alcohol in the past 12 months?
Frequency of one standard during the past 12 months?
Have you consumed any alcohol within the past 30 days?
During the past 30 days, on how many occasions did you have at least one standard
alcoholic drink?

7
A multistage clustered STEPS 2010 Georgia Survey methodology ensured that observations within
the same cluster of population were correlated and valid (STEPS, 2012; STEPS Manual, 2015).
Detailed information related to the primary survey sampling, face-to-face interviews and data
collection can be found elsewhere (STEPS, 2012; STEPS Manual, 2015). Our study sample
comprised data on 2,971 reproductive age women and 66 pregnant women. The range of
sociodemographic variables and covariates on quantities (standard drinks) of alcohol consumed
during lifetime, in the past 12 months and the past 30 days, as well as the number of binge drinking
episodes in the past 30 days were available. In our analysis we included sociodemographic
variables found in previous studies shown to be associated with drinking and drinking-related
outcomes in women (CDC, 2014; Mokhtari et al., 2016; Pomerleau et al., 2008; Skagerstrom
et al., 2011).
Measures
A standard drink is defined by the National Institute on Alcohol Abuse and Alcoholism (NIAAA)
as an equivalent to 14 grams of pure alcohol found in 12 ounces of regular beer, 5 ounces of wine,
and in 1.5 ounces of distilled spirits (NIAAA, 2004). Binge drinking in women refers to an intake
of four or more standard drinks on one occasion or within a two-hour period, and may bring blood
alcohol concentration (BAC) level up to 0.08 grams percent or above (NIAAA, 2004).
Statistical Analysis
Data analyses were carried out using specialized survey command (Surveyfreq Procedure) in the
SAS software version 9.4 (SAS Institute Inc. Cary, NC). The cross-sectional survey analysis was
chosen as a preferred method in the study. The sample was broken down by age, ethnicity,
household size, education, marital status, employment, and monthly household income. The
weighted estimators of alcohol consumption and accompanied weighted standard deviation (SD)

8
were used for unbiased assessments of covariates. Sociodemographic correlates were examined
with logistic regression in the total sample (to predict prevalence) and in subsamples of non-
pregnant and pregnant respondents with lifetime, 12-months and 30-days prevalence of drinking.
Binge drinking was assessed by one, two or four episodes. For inference, we used standard errors,
chi-square and the p-values (<.05) for each of the estimated coefficients, which were confirmed to
be statistically significant for gestational alcohol consumption during the past 30 days among
Georgian women.
Results
Descriptive Analysis
The WHO STEPS Survey of Georgians includes 4,610 women aged 18-65 whose characteristics
are provided in Table 1a. The data sample, however, consisted of 2,971 reproductive age women
(aged 18-45), out which 66 self-identified as being pregnant (Table 1b). Given a 95% participation
rate in the survey and taking the sampling design into account, this implied that sixty six pregnant
women (n = 66) between ages 18 – 45 represented almost thirty thousand (N = 29,862) pregnant
women in Georgia.
Sociodemographic Correlates
Alcohol Consumption
Table 1b and Figure 1 show that the highest weighted relative frequency distribution in the sample
was among 20-year-old pregnant women (17%), 99% constituted pregnant women 38 years old or
younger, and 43% of pregnant women were 18-23 years old.
Table 2 illustrates that 67.51% of non-pregnant and 64.76% of pregnant women of childbearing
age (< 46 years old) consumed alcohol (beer, wine, and spirits) during their lifetime. Also, half of

9
the non-pregnant women (51.89%) used alcohol in the past 12 months, and just over a one-fourth
(27.41%) used it in the previous 30 days. In contrast, more than half (56.85%) of pregnant women
used alcohol in the past 12 months, and over one-third (34.76%) used alcohol in the prior 30 days.
This indicates that almost 10% of non-pregnant women (9.60% = 67.51% x 56.85% x 27.41%) and
13% of pregnant women (12.79% = 64.76% x 51.89% x 34.76%) used alcohol in the past 30 days.
In Table 3 we can see that in Georgia nearly 25% of women (24.45%) also engaged in binge
drinking as defined above. This implies that 70% of pregnant women (70% = 24.45% / 34.76%)
engaged in binge drinking during the past 30 days, half of them (51.51%) had at least four
episodes, 14.51 % had two episodes and 4.31% had one episode of binge drinking.
Ethnicity, Household Size, and Age
In the sample, the majority of pregnant women self-identified themselves as Georgian (89.09%),
and remaining were Azerbaijanis, Russians, Ossetians and Abkhazians women (Table 3). About
one third of Georgian pregnant women (34.76%) reported drinking alcohol in the past 30 days.
More than half of pregnant women (45.88%) lived in two-member households, 25.13% lived in a
three-member, and or 22.83% in a four-member households. The rate of drinking was the highest
(16.54%) among pregnant women who lived in two-member households followed by four-member
households (13.38%). The rates of pregnancy (62.42%) and alcohol use (25.47%) were the highest
among 18-25 years old women. Among 26-35 years old women the pregnancy prevalence was
28.14% and alcohol use was 6.62% and a much lower among women 36-45 years old women.
Marital Status and Education
Pregnant women (92.46%) in the study who were married or cohabitating had a higher rate of
alcohol use (27.23%) than never married or divorced. More than half (57.72%) of pregnant women
completed high school, about 25% (26.30%) completed college, and a smaller fraction (15.99%)

10
had completed secondary school or less. Pregnant women who completed high school or college
had similar rates of alcohol use (15.38% vs.14.34%) compared to women with secondary school
education (5.05%).
Occupation and Income
The majority of pregnant women were homemakers (66.28%), followed by self-employed
(13.06%) and government employees (10.92%). The rate of alcohol use among pregnant
homemakers during the past 30 days was 20.43% and twice as high as among self-employed
women (9.10%) and four times higher than among non-government employees (5.24%). Pregnant
women in other occupations (government, student and unemployed) abstained from drinking
during the previous 30 days. The highest rate of pregnancy (55.70%) and alcohol use in the past 30
days (33.5%) was among women in the lowest reported household income bracket of less than 200
GEL/month (equal to $110 in October, 2010). It appears that a higher income was not associated
with drinking during pregnancy as women in a higher income bracket of 200-400 GEL/month
(8.98%) had lower pregnancy rate and very low rate of alcohol use (1.27%), and reported no
alcohol consumption during the past 30 days.
Logistic Regression Analysis
Table 4a and Table 4b present the results from the multivariate logistic regression analysis with
correlates on alcohol consumption among women aged 18-65 and pregnant women (aged 18-45)
during the past 30 days. First, all of the available covariates were included in the regression model
(Table 4a); thus, avoiding a stepwise approach that would have opened the analysis to potential
spurious correlation or inference. However, limited number of observations on pregnant women (n
= 66) did not allow for the full inclusion of all potential covariates (Table 4b). Based on the
literature, the sociodemographic variables were controlled to avoid confounding. Given a rather

11
modest number of pregnant women in the sample (n = 66) and highly collinear sociodemographic
characteristics, only a limited number of potential regressors were allowed in the final logit model
to make inference about a large population (Table 4b). The proposed model fit (Table 4b) was
overall fairly good, as reflected in the concordant of 75.40%, tied 9.2%, and discordant of 15.4%.
The variations in the likelihood (odds) of drinking and binge in the past 30 days in a sample were
well explained by the sociodemographic characteristics of pregnant women. The measures of
standard error, chi-square tests, and p-values confirmed that a small household size (one-or two-
member), occupation (self-employed) and income (<200 GEL/month) were all statistically
significant (p< .05) for alcohol consumption during the past 30 days among pregnant
Georgian women.
Pregnant women who lived alone (5.68, SD 1.64) were more likely to drink than those who lived
in larger households (two-, three-, four- or five- or more-member). Likewise, pregnant women who
lived in the two-member households (2.17, SD 0.86) were more likely to have consumed alcohol
in the past month than those living in larger households. Self-employed pregnant women (5.11, SD
1.75) and women in low monthly income category (5.06, SD 2.15) had a substantially higher
likelihood of drinking alcohol during the past 30 days. Table 4b shows that the results of adjusted
odds ratios, after controlling for other factors. This provides certain (albeit limited) insight into the
likelihood of drinking during pregnancy in Georgia.
Discussion
Using data from the World Health Organization’s Stepwise approach to noncommunicable disease
risk factor surveillance in Georgia (STEPS, 2010), this study examined prevalence and
sociodemographic correlates of alcohol use among pregnant women in Georgia. The study sample
of reproductive age (18-45) women was drawn from the STEPS, which is a large and nationally

12
representative survey of adults with a 95% participation rate. Frequencies, multivariate analyses
and related statistics were computed to describe and study associations among the target
population and the odds of alcohol consumption during pregnancy. In particular, we examined
sociodemographic correlates in association with alcohol consumption among non-pregnant and
pregnant women in Georgia. Comparisons are made across age groups, ethnicity, marital and
employment status, household size and monthly income to capture alcohol use to determine the
prevalence of lifetime, 12-months and 30-days drinking and binge drinking episodes.
In Georgia, about 67.51% of non-pregnant and 64.76% of pregnant women aged less than 46 years
old consumed alcohol (beer, wine, and spirits) during their lifetime. The pregnancy rates in
association with alcohol use were the highest among 18-25-year-old women. Almost 13% of
pregnant women used alcohol in the past 30 days. This is 5.4 percentage points higher than that of
7.6% found in the United States (5.4% = 13% - 7.6%) (Marchetta et al., 2012.), but it is within the
range of 20% to 80% that has been reported in Ireland, Australia, New Zealand and the United
Kingdom (O’Keeffe et al., 2015).
Recent research suggests that drinking patterns with heavy drinking in binges may indicate a
stronger independent risk factor for adverse alcohol-related health outcomes (Rehm et al., 2001;
Tan et al., 2015). Among those women who drank during their pregnancy in Georgia, nearly 70%
drank alcohol in binges during the past 30 days, on more than one occasion. This pattern of
drinking among pregnant women in Georgia may be a serious risk factor to their health and the
health of offspring. Analysis of the data supports the hypothesis that pregnant women who were
married, homemakers, from small household size (two-member), and with the lowest monthly
income have a higher likelihood of alcohol use and binge drinking than others. In contrast,

13
unmarried, older (35–44 years old) and employed women living in the US were more likely
alcohol drinkers while pregnant (Marchetta et al., 2012).
Alcohol use in pregnancy may vary across studies depending on the methods of data collection
(interviewer-administered vs self-report questionnaires) (Rogers et al., 1998). Nonetheless,
abstention and alcohol cessation are the best ways to achieve a healthy pregnancy. Despite the
limitations imposed by the cross-sectional nature of the data, this study offers evidence that inform
policies and initiatives that are designed to reduce harmful impact of alcohol use during pregnancy
in Georgia. The findings in this study strengthen public health preventive strategies on abstinence
that target reproductive age and pregnant women in the country of Georgia.
Contributions to Understanding Alcohol Use and Policy
As the oldest producer of wine in the world, Georgian culture has evolved to define alcohol
consumption as an essential element for interpersonal relationships and behavioral norms and
expectations. This cultural view hinders an understanding that alcohol use, in general, endangers
public health and, in particular, the health of pregnant women. Thus, by quantifying the extent of
the problem of alcohol use during pregnancy in Georgia this study challenges the existing cultural
norms and informs policy makers of an existing problem that deserves their attention. Moreover,
by reporting on the correlates of alcohol use during pregnancy, this study provides Georgian policy
makers with evidence for targeting sub-groups that may be more susceptible to alcohol abuse
during pregnancy than others.
Our quantitative assessment of the extent of alcohol use during pregnancy in Georgia contributes
to those policies and initiatives that aim at reducing alcohol use among pregnant women. First, our
study provides a base-line for assessing the evolution of alcohol use among pregnant women.

14
Second, our quantitative analysis informs policy makers in their efforts to target particular sub-
groups among pregnant women who consume alcohol. Third, by providing an evidence-informed
perspective, our study can be used as an initial model for monitoring and evaluation, where policy
makers can measure and demonstrate whether interventions have positive effects in reducing
alcohol use among pregnant women. By quantifying the problem of alcohol consumption during
pregnancy and related sub-groups, our study improves policy makers understanding of these
critical issues and provides a better quantitative target for initiatives and action, as well as a
foundation for gauging future activities that may aim at prevention, reduction and abstinence from
alcohol use by women.
Strengths and Limitations
The main strength of this study is availability of a national survey-based sample representative of
the population in Georgia, where cultural and social environment approves of alcohol consumption
in women. The resources provided by WHO STEPS project offered opportunity to begin health
data gathering and to initiate national health surveillance system in Georgia (STEPS, 2012; STEPS
Manual, 2015; Ustun et al., 2003). A second strength of this study is a high local interest and
cooperation in survey with a 95% respondent participation rate. The survey includes data on
alcohol drinking habits and binge drinking episodes among pregnant women during their lifetime,
in the past 12 months and the past 30 days.
This study also has some limitations and weaknesses. The cross-sectional nature of the survey
prevents us from ascribing causality between the variables of interest. Not having access to a
longitudinal dataset is an important limitation in any study of alcohol use. The cross-sectional
nature of the data used in this study limits ability to infer causal associations. Validity of measures,
self-reports, recall bias and underreporting is a problem in most surveys of alcohol consumption

15
and are considered a limitation (Embree & Whitehead, 1998; Stockwell et al., 2004). There may
also be a substantial underreporting of alcohol use by women before and during pregnancy that
have heavily drinking partners (Balachova et al., 2012). No data were collected on drinking habits
among underage youth as the national survey was restricted to adults aged 18-65 years old.
Measure of the longer-term drinking pattern, quitting and resuming of drinking in subsequent
pregnancies could complement research data. Therefore, systematic observations and regular
alcohol screening in women and their partners can enrich data available to research that focuses on
reproductive age women, particularly in the preconception period and during pregnancy.
Conclusion
Based on a national survey data, this study has identified a number of sociodemographic
characteristics which are associated with high prevalence of alcohol use and binge drinking among
pregnant women in the country of Georgia. Maternal use of alcohol during early pregnancy
exposes the fetus to a range of adverse outcomes. Abstention and alcohol cessation ensure
improved pregnancy outcomes and fetal growth and development. Evidence on the alcohol use by
pregnant women in Georgia informs public health preventive strategies that target both
reproductive age and pregnant women in the country of Georgia. For preventing alcohol-exposed
pregnancies research must focus on studying and devising interventions that are effective at earlier
ages. Future research based on continued systematic screening and surveillance at early age might
shed light on women who remain at the highest risk for alcohol exposure before pregnancy
is recognized.
Role of Funding Source
No Funding source was used for supporting this research. No honorarium, grant, or other form of
payment was given to any author or any other individual to produce the manuscript.

16
Contributors
M. Mokhtari designed and coordinated the study and undertook the statistical analysis. All authors
contributed to drafting of the manuscript. All authors approved the final manuscript.
References
1. Balachova T, Bonner B, Chaffin M, et al. (2012). Women’s alcohol consumption and risk
for alcohol-exposed pregnancies in Russia. Addiction. 107(1):109–117.
2. Bhuvaneswar, C. G., Chang, G., Epstein, L. A., & Stern, T. A. (2007). Alcohol Use During
Pregnancy: Prevalence and Impact. Primary Care Companion to The Journal of Clinical
Psychiatry, 9(6), 455–460.
3. Bouchery EE, Harwood HJ, Sacks JJ, Simon CJ, Brewer RD. (2011). Economic costs of
excessive alcohol consumption in the U.S., 2006. Am J Prev Med. 41(5):516–24.
4. CDC. (2014). Centers for Disease Control and Prevention. Fact Sheet-Binge Drinking.
Atlanta, GA. Retrieved from: www.cdc.gov/alcohol/fact-sheets/binge-drinking.htm.
5. Embree B G, Whitehead P C. (1998) Validity and reliability of self-reported drinking
behaviour: dealing with the problem of reporting bias, Journal of Studies on Alcohol, 54,
334- 344.
6. Flak AL, Su S, Bertrand J, Denny CH, Kesmodel US, Cogswell ME. (2014). The
Association of Mild, Moderate, and Binge Prenatal Alcohol Exposure and Child
Neuropsychological Outcomes: A Meta-Analysis. Alc Clin Exp Res. 38(1):214–26.
7. Floyd RL, Ebrahim SH, Boyle CA. (1999). Observations from the CDC. Preventing
alcohol-exposed pregnancies among women of childbearing age: the necessity of a
preconceptional approach. Journal of Women's Health & Gender-Based Medicine 8:733–
736.
8. Green PP, McKnight-Eily LR, Tan CH, Mejia R, Denny CH. (2016). Vital Signs: Alcohol-
Exposed Pregnancies - United States, 2011–2013. Morb Mortal Wkly Rep 65:91–97.
9. Hinote BP, Cockerham WC, Abbott P. (2009). The specter of post-communism: women
and alcohol in eight post-Soviet states. Soc Sci Med 68:1254–1262.
10. Javakhishvili DJ, Sturua L, Otiashvili D, Kirtadze I, Zabransky T. (2011). Overview of the
drug situation in Georgia. Adictologie. 11(1): 42–51.

17
11. Jukkala T, Mäkinen IH, Kislitsyna O et al. (2008). Economic strain, social relations,
gender, and binge drinking in Moscow. Soc Sci Med 66:663–674.
12. Marchetta CM, Denny CH, Floyd RL, Cheal NE, Sniezek JE. (2012). Alcohol use and
binge drinking among women of childbearing age-United States, 2006–2010. Morb Mortal
Wkly Rep 61(28):534-538.
13. May PA, Baete A, Russo J, et al. (2014). Prevalence and characteristics of fetal alcohol
spectrum disorders. Pediatrics 134(5):855–866.
14. Mokhtari M, Kondracki A, Wallen J, Kavtaradze L, Ashtari M, Topuridze M, Sturua L,
Piralishvili G, Todadze K, Kiladze L, Gachechiladze N. (2016). Binge Drinking in the
Oldest Wine Country: Evidence from the Noncommunicable Disease Risk Factor
Surveillance. Journal of Global Drug Policy and Practice, 10 (3).
15. Naimi TS, Lipscomb LE, Brewer RD, Gilbert BC. (2003). Binge drinking in the
preconception period and the risk of unintended pregnancy: implications for women and
their children. Pediatrics.111:1136–41.
16. O’Keeffe LM, Kearney PM, McCarthy FP, et al. (2015). Prevalence and predictors of
alcohol use during pregnancy: findings from international multicentre cohort studies. BMJ
5: e006323.
17. Oxford Companion to Wine, 4th edition. (2015). Robinson J and Harding J Editors. Oxford
University Press. Oxford, UK.
18. Patra J, Bakker R, Irving H, Jaddoe VWV, Malini S, Rehm J. (2011). Dose-response
relationship between alcohol consumption before and during pregnancy and the risks of
low birthweight, preterm birth and small for gestational age (SGA)-a systematic review and
meta-analyses. BJOG. 118:1411–1421.
19. Peele S, Brodsky A. (1996). Alcohol and Society. How Culture Influences the Way People
Drink. Pamphlet prepared for The Wine Institute, San Francisco: CA. Retrieved from:
http://www.peele.net/lib/sociocul.html.
20. Pomerleau J, McKee M, Rose R, Haerpfer CW, Rotman D, Tumanov S.(2008). Hazardous
alcohol drinking in the former Soviet Union: a cross-sectional study of eight countries.
Alcohol and Alcoholism. 43 (3): 351–359.
21. Rehm J, Gmel G, Room R, Frick U. (2001). Average volume of alcohol consumption,
drinking patterns and related burden of mortality in young people in established market
economies of Europe. Eur Addict Res 7:148-151.
22. Rogers SM, Miller HG, Turner CF. (1998). Effects of interview mode on bias in survey
measurements of drug use: Do respondent characteristics make a difference? Subst Use
Misuse 33:2179–2200.

18
23. Sayal K, Heron J, Draper E, Alati R, Lewis SJ, Fraser R, Barrow M, Golding J, Emond A,
Davey Smith G, Gray R. (2014). Prenatal exposure to binge pattern of alcohol
consumption: mental health and learning outcomes at age 11. Eur Child Adolesc Psychiatry
23(10):891-9.
24. Skagerstrom J, Chang G, Nilsen P. (2011). Predictors of drinking during pregnancy: a
systematic review. J Women’s Health. 20(6):901–13.
25. STEPS Manual. (2015). World Health Organization, Geneva, Switzerland. Retrieved from:
http://www.who.int/chp/steps/manual/en/index7.html.
26. STEPS. (2012). Georgia STEPS Survey 2010. World Health Organization, Geneva,
Switzerland. Retrieved from:
http://www.who.int/chp/steps/2012_GeorgiaSTEPS_Report.pdf?ua=1.
27. Stockwell T, Donath S, Cooper-Stanbury M, Chikritzhs T, Catalano P, Mateo C. (2004).
Under-reporting of alcohol consumption in household surveys: a comparison of quantity-
frequency, graduated-frequency and recent recall. Addiction 99:1024–33.
28. Tan CH, Denny CH, Cheal NE, Sniezek JE, Kanny D. (2015). Alcohol Use and Binge
Drinking Among Women of Childbearing Age -United States, 2011–2013. Morb Mortal
Wkly Rep 64(37):1042-1046.
29. USDHHS. (2005). US Department of Health and Human Services. US Surgeon General
releases advisory on alcohol use in pregnancy. Washington, DC: US Department of Health
and Human Services. Retrieved from:
http://www.surgeongeneral.gov/pressreleases/sg02222005.htm.
30. Ustun TB, Chatterji S, Mechbal A, Murray, CJL. (2003). World Health Surveys. In:
Murray CJL, Evans DB. 2003. Health systems performance assessment: debates, methods
and empiricism. Retrieved from: www.who.int/healthinfo/survey/hspa58.pdf.
31. Whitmore SK, Kann L, Prejean J, Koenig LJ et al. (2012). Vital Signs: HIV Infection,
Testing, and Risk Behaviors Among Youths - United States. Morb Mortal Wkly Rep
61(47): 971-976.
32. WHO. (2014). World Health Organization. Global status report on alcohol and health,
2014. Geneva, Switzerland, p.44. Retrieved from:
//apps.who.int/iris/bitstream/10665/112736/1/9789240692763_eng.pdf.
About the Authors
Manouchehr Mokhtari, Ph.D., is an Associate Professor at the School of Public Health at the
University of Maryland, College Park. He is also an Affiliate Faculty of the Horowitz Center for
Health Literacy, and holds a Faculty Associate position with the Maryland Population Research

19
Center (MPRC). He received his MA and Ph.D. from the University of Houston, Texas. He has
served as a faculty at Princeton University, University of Houston, NES (Russia), and the Eurasian
University (Kazakhstan). He has also served as the senior adviser to the governments of
twelve countries in Central Asia, Caucasus, Middle East, and Eastern Europe. His primary research
interests are health policy analysis, the assessment and treatment of alcohol use, fertility and
obesity. Dr. Mokhtari is on the editorial boards of more than ten journals and has served as the
editor for a number of special issues on health systems strengthening and health policy analysis.
Anthony Kondracki, MD, MPH, CPH, is a fourth-year doctoral candidate in Maternal and Child
Health at the School of Public Health at the University of Maryland, College Park. He received his
MD from the Jagiellonian University College of Medicine in Krakow (Poland) and his MPH from
Tulane University. Dr. Kondracki's primary interests are in maternal factors leading to short and
long-term effects of preterm birth and low birthweight.
Lasha Kavtaradze, Ph.D., is an Assistant Professor at the International Black Sea University, an
invited lecturer at the University of Georgia and Ilia State University, and an economist at Galt &
Taggart. Formerly, he was the Head of Macroeconomic Analysis and Tax Policy Unit at the
Parliamentary Budget Office of Georgia. He received his Ph.D. in Public Economics from the
Catholic University of Milan, Italy. Dr. Kavtaradze’s research interests are public policy analysis,
macroeconomics, econometrics, forecasting, monetary and fiscal policies.
Jacqueline Wallen, Ph.D., MSW, is an Associate Professor Emerita in the Department of Family
Science, School of Public Health, University of Maryland, College Park. She earned her Ph.D.
from the University of Chicago and her MSW from Catholic University. Her primary research

20
interests are health and mental health services research, health care disparities, and women’s
health care issues.
Mamak Ashtari, MBA, is an international consultant who provides technical assistance for
promoting evidence-based policy analysis in Central Asia, Caucasus, Middle East, and Eastern
Europe. Ms. Ashtari’s research interests are health policy analysis, and anti-corruption in health
industry and public finance.
Gvantsa Piralishvili, Ph.D., MD, is a Deputy Chair of Council of Science Experts at the Center
for Mental Health and Prevention of Addiction, Tbilisi, Georgia. She received her MD and Ph.D.
from Tbilisi State Medical University and Tbilisi State Medical Academy. She is an alumna
NIDA/CTN/INVEST Fellow at the University of Pennsylvania and the Delaware Valley Node of
the Clinical Trial Network. Her primary research interests are the assessment and treatment of drug
and alcohol abuse.
Marina Topuridze MD, MS, is a chief Specialist at Health Promotion Division, Non-
communicable Disease Department, National Center for Disease Control and Public Health
(NCDC), Tbilisi, Georgia. She received her MD from Tbilisi State Medical University and her MS
in Epidemiology from SUNY Albany, New York. Dr. Topuridze’s primary research interest is
non-communicable disease risk behaviors, health policy, promotion and education.
Khatuna Todadze, Ph.D., MD, is the Head of Department of Narcology and the Vice-Rector of
Tbilisi State Medical University. She also works as a Deputy Director General of the Center for
Mental health and Prevention of Addiction. She received her MD and Ph.D. from Tbilisi State

21
Medical University. She is the founder of opioid substitution treatment (OST) and the Coordinator
of Methadone Maintenance Programs in Georgia and its prison.
Lasha Kiladze, MD, is the Director-General at the Center for Mental Health and Prevention of
Addiction in Tbilisi, Georgia. He also serves a psychiatrist at the Military Hospital. After receiving
his MD and psychiatry degree from Tbilisi State Medical University, Dr. Kiladze completed a
course on Medical Projects Managements at the Institute of Development Studies - Oxford Policy
Management. His areas of research interests include management of healthcare and harm reduction
projects, addictology, alcohol-induced psychotic and behavioral disorders, and suicidology.
Nino Gachechiladze, MSc, is a Senior Researcher at the Analysis and Consulting Team (ACT).
She is also a board member at the Institute of Social Researches (ISR). She received her MSc
degree in Social Research from the University of Edinburgh, United Kingdom. Ms.
Gachechiladze’s research has focused on gender studies, GBV, and women’s health.
Conflict of Interest
All authors declare no conflict of interest. All authors declare that they have no proprietary,
financial, professional or other personal interest of any nature or kind in any product, service
and/or company that could be construed as influencing the position presented in, or the review of,
the manuscript entitled Prevalence and Correlates of Alcohol Consumption During Pregnancy in
Georgia: Evidence from a National Survey.

22
Table 1a. Sociodemographic Characteristics of Georgian Women Aged 18 – 65
Female (n = 4610)
Raw Freq % SD Chi-
Square
Ethnicity
Georgian
4,049
87.80
1.81
188.01
Ossetian
43
0.71
0.21
1,247.21
Azerbaijani
164
6.01
1.71
161.61
Armenian
259
4.41
0.91
399.61
Russian
54
0.81
0.21
3,722.91
Household Size
One
858
7.41
0.50
1,908.90
Two
1,473
25.71
1.00
432.20
Three
1,177
29.81
1.00
340.30
Four
670
20.31
1.00
629.70
Five or more
391
16.50
1.10
478.40
Age
18 – 25
550
21.20
1.20
397.00
26 – 35
674
22.50
0.90
641.90
36 – 45
827
20.80
0.80
855.10
46 – 55
1,221
23.10
0.80
812.10
56 – 65
1,342
12.40
0.60
1,924.00
Marital Status
Never married
614
18.90
1.00
609.20
Separated
136
1.50
0.20
4,794.20

23
Divorced
187
3.20
0.30
2,820.30
Widowed
725
7.80
0.40
2,687.20
Married
2,907
68.20
1.00
262.70
Maternal Status
Pregnant
66
2.80
0.40
1,643.70
Smoker
Smoker
201
4.80
0.50
1,298.60
Education
Secondary school
372
9.11
1.21
1,363.61
High School
2,711
57.81
1.41
413.21
College
1,486
32.80
1.20
185.70
Occupation
Government
1,859
15.70
0.90
823.60
Non-government
823
5.50
0.60
1,332.20
Self-employed
207
6.70
0.50
1,619.70
Non-paid
314
0.30
0.10
2,168.20
Student
10
6.80
0.70
1,116.40
Homemaker
140
42.50
1.30
35.20
Retired
567
5.30
0.40
2,805.90
Unemployed
588
15.80
0.90
738.10
Unable to work
61
0.10
0.20
1,815.10
Monthly Income (GEL)
=< 200
2,766
53.40
1.80
3.90
> 200 to <=400
1,013
23.50
1.10
460.00

24
> 400 to <=800
615
16.50
1.10
510.70
> 800 to <=1600
193
5.70
0.60
1,110.50
More than 1600
27
0.80
0.20
2,099.40
Data: WHO’s STEPwise Approach to Noncommunicable Disease Risk Factor Surveillance
SD: Standard Deviation; Chi-square: Rao-Scott Chi-Squared statistics.
Raw Freq: Raw Frequencies
Software: SAS (Surveyfreq Procedure)
Table 1b. Pregnancy Distributions by Age, Georgia 2010
Age
Raw
Frequency
Weighted
Relative
Frequency
(%)
Weighted
SD
(%)
19
1
0.77
0.77
20
9
16.52
5.57
21
1
1.91
1.93
22
6
11.27
4.41
23
7
12.26
4.45
24
5
6.20
2.93
25
5
5.08
2.41
26
3
5.79
1.55
27
1
0.55
0.55
28
4
5.65
3.32
29
3
5.25
3.13
30
3
4.30
2.53
31
1
0.66
0.67
32
4
7.39
4.11
33
1
2.28
2.26

25
34
3
6.56
3.28
35
2
1.27
0.92
36
1
1.02
1.03
37
2
1.63
1.20
38
3
2.45
1.44
45
1
1.19
1.19
SD: Standard Deviation
Figure 1. Pregnancy Distributions by Age in the Country of Georgia, 2010
0%
2%
4%
6%
8%
10%
12%
14%
16%
18%
19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 45
% Pregnant
Age

26
Table 2. Prevalence of Drinking among Non-Pregnant and Pregnant Women, Georgia 2010
Raw
Frequency
Weighted
Relative
Frequency
(%)
Weighted
SD
(%)
Alcohol Consumption by Non-Pregnant Women (Age < 46)
Ever Consumed Alcohol (X = % of non-pregnant women)
1,245
67.51
2.36
Consume Alcohol in past 12 Months (Y = % of X)
952
51.89
2.34
Consumed Alcohol in past 30 Days (Z = % of Y)
500
27.41
1.78
Alcohol Consumption by Pregnant Women (Age < 46)
Ever Consumed Alcohol ( X = % 0f pregnant women)
46
64.76
7.06
Consume Alcohol in past 12 Months (Y = % of X)
31
56.85
7.13
Consumed Alcohol in past 30 Days (Z = % of Y)
9
34.76
8.80
Binge drinking by Pregnant Women in the Past 30 Days (Z = A1 + A2)
Binged on Alcohol (A1= Z – A2)
5
24.45
8.07
Consumed Alcohol without Binging (A2 = Z – A1)
4
10.31
5.53
Frequency of Drinking Alcohol in the Past 30 Days
(100% = B1 + B2 + B3 + B4)
Drank Alcohol without Binging (B1 = % of Z)
4
29.65
13.18
Binge Drinking Once (B2 = % of Z)
1
4.31
0.70
Binge Drinking Twice (B3 = % of Z)
1
14.51
14.24
Binge Drinking More Than Four Times (B4 = % of Z)
3
51.51
7.88
SD: Standard Deviation

27
Table 3. Prevalence of Drinking Patterns among Pregnant Women in Georgia, 2010.
%SD %SD %SD Chi-Square p-value
Georgian 89.09 4.40 34.77 8.81 90.22 6.75 37.12 0.01
Russian 2.35 1.81 . . 2.73 0.15 19.67 0.01
Ossetian 0.91 0.89 . .
Armenian 0.98 0.98 . .
Azerbaijani 6.69 3.85 . .
One 3.57 3.66 3.57 3.66
Two 45.88 7.00 16.54 5.65 44.98 3.26 2.46 0.11
Three 25.13 6.61 1.27 0.09 36.57 8.13 2.84 0.09
Four 22.83 8.97 13.38 8.87 14.48 7.51 23.42 0.01
Five or more 2.58 0.19 . . 3.95 0.21 49,673.02 0.01
Age
18 - 25 62.42 8.58 25.47 8.51 56.64 9.91 0.47 0.49
26 - 35 28.14 7.89 6.52 0.48 33.14 10.41 2.74 0.09
36 - 45 9.44 5.02 2.78 2.85 10.21 3.85 111.57 0.01
Marital Status
Never married
5.24 0.39 5.24 0.39 . . . .
Divorced
2.31 2.32 2.31 2.32 . . . .
Married/Cohabiting
92.46 2.42 27.23 8.71 . .
. .
Secondary school
15.99 6.39 5.05 4.97 16.77 7.44 20.88 0.01
High school
57.72 9.23 15.38 6.88 18.32 4.98 42.23 0.01
College or Higher
26.31 8.26 14.34 8.28 16.74 3.82 79.16 0.01
Government
10.92 2.61 . . 16.74 3.82 79.16 0.01
Non-government
5.24 0.39 5.24 0.39 . . .
Self-employed
13.06 9.22 9.11 8.57 6.06 5.88 58.32 0.01
Student
2.09 0.16 . . 3.21 0.17 78,294.93 0.01
Homemaker
66.28 8.24 20.43 7.64 70.28 5.41 14.76 0.01
Unemployed
2.41 1.69 . . 3.69 2.61 331.96 0.01
=< 200
55.71 7.27 33.51 8.84 34.03 2.01 66.62 0.01
> 200 to <=400
8.98 4.21 1.27 0.09 11.81 4.36 80.01 0.01
> 400 to <=800
22.74 5.02 . . 34.86 6.06 6.51 0.01
> 800 to <=1600
12.58 4.48 . . 19.27 6.41 24.01 0.01
Chi-square Test: chi-squared test for independence
.
Ful l Sample
Consumed
Did Not Consume
"Have you consumed any alcohol within the past 30 days?"
Chi-square Test
Household Size
Education
Occupation
Ethnicity
Monthly Income (GEL)

28
Table 4a. Results of Multiple Logistic Regression Analysis with Correlates of Alcohol
Consumption during the Past 30 Days among Women Aged 18 – 65 in Georgia
% Concordant
Effe ct Odds p-values
Ethnicity
Ossetian 0.49 0.10 2.50 0.39
Azerbaijani 0.08 0.02 0.29 <0.01
Armenian 0.52 0.14 1.91 0.32
Russian 0.92 0.23 3.70 0.90
Household Size
Two 0.67 0.43 1.03 0.07
Three 0.79 0.51 1.24 0.31
Four 0.93 0.54 1.60 0.80
Five or more 1.00 0.58 1.72 0.99
Age
26 - 35 0.84 0.48 1.48 0.55
36 - 45 0.79 0.47 1.35 0.40
46 - 55 0.56 0.33 0.96 0.04
56 - 65 0.46 0.25 0.86 0.01
Marital Status
Never married
1.09 0.67 1.79 0.73
Separated
0.75 0.25 2.24 0.60
Divorced
0.47 0.21 1.04 0.06
Widowed
0.45 0.26 0.78 <0.01
Maternal Status
Pregnant 0.62 0.23 1.68 0.35
Smoking
Smoker 3.00 1.84 4.89 <0.01
Education
Secondary School 2.00 1.09 3.67 0.02
College or higher 1.43 0.99 2.05 0.06
Occupation
Government
1.05 0.64 1.72 0.84
Non-government
0.83 0.40 1.70 0.61
Self-employed
1.30 0.73 2.30 0.38
Non-paid
1.29 0.12 13.59 0.83
Student
1.31 0.66 2.63 0.44
Retired
0.48 0.25 0.92 0.03
Unemployed
0.61 0.39 0.98 0.04
Unable to work
0.72 0.13 3.86 0.70
Monthly Income (GEL)
> 200 to <=400
0.49 0.33 0.72 <0.01
> 400 to <=800
0.52 0.33 0.82 0.01
> 800 to <=1600
0.75 0.39 1.45 0.39
More than 1600
1.06 0.29 3.91 0.93
95% CL
Female (n = 4610)
0.66

29
Covariates
(control groups)
Coefficient
Beta
Estimate
Standard
Error
Chi-
Square
p-value
Odds
Ratio
Estimates
Intercept -7.85 2.45 10.24 <0.01
Age (18-35)
36 – 45 1.22 2.27 0.29 0.59 3.37 0.04 287.52
One 5.68 1.64 12.03 <0.01 293.91 11.85 >999.99
Two 2.17 0.86 6.41 0.01 8.72 1.63 46.65
Marital Status (Married)
Divorced 1.72 1.08 2.53 0.11 5.58 0.67 46.56
Education (High School or lower)
College or Higher -0.13 0.89 0.02 0.89 0.88 0.16 5.00
Occupation (Homemaker, Government, or unemployed)
Self-employed 5.11 1.75 8.55 <0.01 166.13 5.39 >999.99
Monthly Income ( > 200 GEL)
=< 200 5.06 2.15 5.53 0.02 157.37 2.32 >999.99
% Concordant: 75.4
% Discordant 15.4
% Tied: 9.2
95% CL
Table 4b. Multivariate Logistic Regression Analysis with Correlates of Alcohol Consumption
among Pregnant Women during the Past 30 Days.
Household Size (Three or more)

Social Determinants and Substance Use: A perspective beyond the policy
‘silo’ pragmatics
By Shane Varcoe, National Training & Partnerships Officer, Dalgarno Institute, and
Derek Steenholdt, Research Officer, Dalgarno Institute
Editor’s note: Due to the length of this paper, we are featuring only the abstract and provide
the link to the full paper at the end.
Abstract
The factors which have influenced the uptake of illicit drug use in advanced and developing
countries can be traced back to shifts away from traditional moral principles and changes in
ethical attitudes relating to personal versus government responsibilities through significant
changes in government policies as much as a century ago. (Etzioni 1996). These changes
towards amoral approaches to social issues and greater government responsibility for
personal health issues have influenced the language we use to describe the influence of illicit
drugs on human behaviour, preferring to explain the harms resulting from drug abuse as
essentially “health” issues. (Dalrymple, 2007)
This paper explores how these factors and other social determinants have influenced the
uptake and increased consumption of illicit drugs by the general population in developed
countries and gives due consideration to the substantial and ever increasing social, economic
and health costs to societies world-wide. (Australian Institute of Family Studies 2008;

National Drug Strategy Household Survey 2013; Stutman, 2013; W.H.O. Commission on
Social Determinants of Health, 2008) International policy development and national attempts
to implement effective illicit drug related policies are discussed in light of data which has
been collated through national and international studies. (W.H.O. 2013).
The authors posit that there is a need to address underlying issues and principles relating to
personal responsibility; and at a national level, a need to present a unified approach across
government departments in preventing harm from illicit drugs, which have in the past been
seen as adopting a narrow “silo” approach (Carey & Crammond, 2014). It is proposed that
much can be achieved through implementing an effective model for addressing social
determinants which impact on communities and contribute to the increasing incidence of
drug and alcohol abuse and associated negative impacts being reported in developed
countries. (UN Commission on Narcotic Drugs, 2016)
Only clear and unambiguous policy frameworks, along with policy implementation which
ensures Demand Reduction and Prevention – along with effective drug exiting Recovery
Programs – will see the health, community and familial outcomes that societies focused on
reducing drug use can achieve.
To view the full paper, please click here.
About the Authors
Shane W. Varcoe
Shane Varcoe is currently the National Partnerships & Training Officer for the Dalgarno
Institute, a community-based, not-for-profit, public interest coalition of alcohol and drug
educators in Australia, deploying Train the Trainer Drug Education model nationally.

Previously as Executive Director of the Dalgarno Institute, he designed, implemented and led
numerous prevention programs and campaigns, such as the ‘No Brainer’ alcohol and other
drug education project. As Director of Education Services for Concern Australia, he led the
Values 4 Life schools program. He also has authored a number of papers, studies and books.
He is a registered Chaplain with a Diploma of Ministry, A.C.R.A.C.S. (Advanced Certificate
Residential & Community Services) qualifications, and has over 30 years of
youth/community work, education and facilitation experience.
Derek Steenholdt, Master Educator, Emeritus
Derek currently serves in an unpaid staff role as a Research Officer for Dalgarno Institute in
Australia. His qualifications are: MEdSt; Bed (Prim); BEd; BSc (Hons); Certificate III in
Quality Management for Business Excellence, AQC, 2001; Certificate IV in Workplace
Training and Assessment, ISIS RTO, 1999; Workplace Assessor, West Melbourne Institute
of TAFE, 1998; Master of Educational Studies, Monash, 1991; Bachelor of Education
(Primary), Deakin, 1993; Bachelor of Education, Monash, 1978; Bachelor of Science
(Honours), Monash, 1971.
Conflict of Interest
I declare that I have no proprietary, financial, professional or other personal interest of any
nature or kind in any product, service and/or company that could be construed as influencing
the position presented in, or the review of, the manuscript entitled, Social Determinants and
Substance Use: A perspective beyond the policy ‘silo’ pragmatics, except for the following:
Shane Varcoe is the National Training & Partnerships Officer of the Dalgarno Institute and
Derek Steenholdt is an unpaid Research Officer of the Dalgarno Institute.