Effect of COVID-19 Lockdown on Alcohol and Tobacco Use in Two Chilean Universities: a Difference-in-difference Analysis
Conditions: SARS-CoV-2 Infection, COVID-19
Sponsor: Universidad de La Frontera

 
 
Study protocol - for registration in ClinicalTrials.gov 
 
Effect of COVID-19 lockdown on alcohol and tobacco use in two Chilean universities: 
a difference-in-difference analysis 
 
Sponsor: Universidad de La Frontera 
Organisation’s unique protocol ID: ANID - COVID0282 
Principal investigators:  
Francisca Román, PhD, Universidad de La Frontera, Temuco, Chile 
Paola Haeger, PhD, Universidad Católica del Norte, Coquimbo, Chile 
 
Collaborators: 
Sebastián Peña, MD, PhD, Finnish Institute for Health and Welfare, Helsinki, Finland 
Camila Salazar, PhD, Universidad de La Frontera, Temuco, Chile 
Daniela Palet, MSc, Universidad de La Frontera, Temuco, Chile 
 
Version: 1.0 
Version date: October 5, 2021 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
Effect of COVID-19 lockdown on alcohol use in two Chilean universities: a difference-
in-difference analysis 
 
Background 
The coronavirus disease 2019 (COVID-19) pandemic has led to substantial societal changes 
in most high and middle-income countries. This can translate to changes in the volume and 
patterns of alcohol use, with severe consequences for health and societal wellbeing [1].  
 
The COVID-19 pandemic could potentially affect alcohol and tobacco use in several ways.  
First, governments have introduced policies to reduce viral transmission, including social 
distancing policies to restrict people’s mobility and exposure to SARS-CoV-2. These have 
ranged from stay-at-home advice and remote-work guidance to statutory closures of schools 
and universities, bars and restaurants and restrictions for public gatherings [2, 3]. The most 
restrictive policies have included lockdowns (with various levels of stringency) and curfews. 
Such policies have disrupted routines and reshaped social interactions as well as acting as an 
acute stressful event, which could, in turn, affect alcohol and tobacco use [1, 4-6]. 
 
Second, the pandemic could directly impact alcohol and tobacco use through changes in 
affordability due to the negative economic consequences, reducing people’s disposable 
income and consumption as a result [7]. A SARS-CoV-2 infection could also directly impact 
tobacco or alcohol use, as the majority of infected individuals have experienced fever, 
malaise or cough [8]. An estimated 10% of those who had COVID-19 persist with fatigue, 
dyspnoea, disturbance of smell or taste after 8-24 weeks, which could affect their alcohol use 
[9]. Persistent COVID-19 symptoms have been reported to be as high as 50% among those 
who were hospitalized due to COVID-19 [10]. 
 
Third, governments have adopted policies that directly influence alcohol and tobacco 
availability and affordability. Such policies include total ban of tobacco (South Africa)[11] 
or alcohol sales (e.g. South Africa, India, Thailand, Panama),[12-15] changes in opening 
hours (as in parts of Chile and Mexico) and even raised alcohol taxes in some States in India 
[16].    
 
Lockdowns, especially those that include statutory restrictions for people’s mobility, have 
likely the largest potential effect on alcohol and tobacco use. Previous studies reporting the 
effect of COVID-19 lockdowns on alcohol use have reported a mixed picture, with some 
studies reporting an increase in high-risk drinking (either volume or heavy episodic 
drinking),[17-21] volume of alcohol use [22] and frequency of alcohol use [23], while other 

 
 
studies have reported reductions in alcohol use [24-26]. Mixed changes on tobacco use have 
also been reported, with a relatively equal proportion of respondents describing an increase 
or reduction in their use of tobacco [17, 20, 27-30]. Evidence comes primarily from countries 
in Europe, the United States, Australia, and New Zealand. One common limitation of these 
studies is that they compare a pre-pandemic with a pandemic period and are thus not able to 
disentangle the direct effects of the pandemic with those from lockdown and curfew policies.  
 
In this study, we will advance prior knowledge by providing evidence from a country in Latin 
America, one of the worst-hit regions worldwide. Latin America accounts for 8.4% of the 
global population, but 20.3% of the total SARS-COV2 cases and 30.2% of the COVID-19 
deaths to date [31]. In addition, we will exploit the variation in lockdown policies in two 
regions in Chile to disentangle the effects of the COVID-19 pandemic with those from a 
lockdown.  
 
The aim of the study is to examine the effect of a regional lockdown on alcohol use in two 
university populations in the Araucanía and Coquimbo regions in Chile. We will use a 
difference-in-difference analysis to obtain causal estimates of these COVID-19 policies.  
 
Methods 
 
Study design 
The study is a controlled before-and-after study of COVID-19 policies in two Chilean 
regions. We will report the results in accordance with the Strengthening the Reporting of 
Observational Studies in Epidemiology (STROBE) statement [32].  
 
Participants 
The study population are university communities from two regions in Chile (Coquimbo, 
northern Chile, and Araucanía, southern Chile). These university communities include 
undergraduate and postgraduate students, full-time and part-time academics, leadership 
positions, administrative staff and service personnel. Eligibility criteria include (1) those with 
study rights either at the undergraduate and postgraduate levels by July 27, 2020; or (2) 
workers with a full-time or part-time contract with the University, including academics and 
assistant personnel, (3) with an email registered in the Human Resource Office of each 
university.  
 
 
 

 
 
Intervention 
We will examine the effect of lockdown in the context of the COVID-19 pandemic. During 
the study period, the Chilean Ministry of Health established a five-step process for social 
distancing measures. These ranged from full lockdown (step 1) to almost no restrictions (step 
5). Even under full lockdown, citizens were able to obtain permits for essential activities 
(e.g., buying food or going to the doctor). These permits had a maximum of two per week 
and were obtained in a virtual station of the Chilean Police Force (Carabineros de Chile). 
Table S1 describes the five phases in detail. Table S2 describes the different types of permits 
people were allowed to use. It must be noted that, due to the COVID-19 pandemic, the 
Chilean government issued a night curfew with a total prohibition to leave home between 
22.00 and 05.00 for the whole country from March 22, 2020, to date. Table 1 includes the 
specific policies implemented in both regions at the time of each data collection period.  
 
Comparator 
The comparator is the absence of lockdown at a given time. During most of the study period, 
the whole country had in place restrictions for public gatherings, school closures and advice 
for remote work. Both universities instructed remote work from March 16, 2020, which 
continued during the whole study period.  
 
Covariates 
We will adjust for covariates that are not influenced by the intervention but correlate with 
the outcome to increase the statistical power. These covariates include sex, age, educational 
level, living arrangements, existing medical conditions, and type of relationship with the 
university (i.e., student, academic or service personnel). We will categorise education into 
four categories: complete secondary education, incomplete undergraduate education, 
complete undergraduate education, and postgraduate education degree. We will categorise 
living arrangements into living alone or not. Existing medical conditions will be categorised 
into a dichotomous variable on whether the participants reported any of the following: high 
blood pressure; diabetes; cardiac problems (cardiac insufficiency, myocardial infarction, or 
others; respiratory conditions (asthma, respiratory insufficiency; depression; anxiety; other 
mental health problem; cancer (any malignancy including leukaemia or lymphoma; and 
fibromyalgia). We will categorise the type of relationship into three categories: student, 
service or administration personnel, and academic or leadership position.  
 
 
 
 

 
 
Outcomes 
We will examine three primary outcomes: weekly grams of alcohol use, heavy episodic 
drinking (HED) and number of cigarettes smoked per day. Weekly grams of alcohol use were 
measured at baseline with a question of how many drinks of beer (in portions of 330 cc), 
wine and similar (chicha and pipeño, two types of unfiltered wines, in portions of 140 cc) 
and spirits (pisco, rum, whisky, tequila, vodka, gin or other strong liquors) in a typical week. 
We asked the same questions for a pre-pandemic period and a during-the-pandemic period. 
The follow-up at waves 2 to 6 included a similar question but for each day of the week (“how 
many drinks did you have each day of the week”).  
 
We will convert the number of drinks into grams by multiplying the volume of each beverage 
by the density of alcohol (0.789). We will consider a standard drink of 15.8 grams based on 
the results of the Chilean National Health Survey 2009-2011, which had a standardized 
protocol to assess standard drinks in Chile. This data is available for all waves. Waves 0, 1, 
5 and 6 include separate questions for beer, wine, and spirits. 
 
We will measure HED with a question on how often the respondent drank 5 or more drinks 
on a single occasion (considering a 1-month period). The options were never, once, twice, 3 
to 5 times, 6 to 9 times and 10 or more. We will convert this information into a continuous 
variable. We will convert the options 3-5 and 6-9 times to their arithmetic midpoint (4 and 
7.5, respectively). We will convert the 10 or more option into the lower boundary (i.e., 10). 
This data is available for waves 0, 1, 4, 5 and 6. 
 
We will measure the number of daily cigarettes smoked per day with a question on how many 
cigarettes has the participant smoked on average during the past week. We will convert this 
information into a continuous variable. This data is available for all waves. 
 
Procedures 
We collected the data using an online survey sent by email to all eligible participants. Data 
were collected from July 27 to August 13 (wave 0 and 1), August 15 to August 25 (wave 2), 
September 7 to September 22 (wave 3), October 5 to October 16 (wave 4), November 9 to 
November 20 (wave 5), December 9 to December 21 (wave 6) and April 5 to April 23 (wave 
7). In all waves, we used an online survey tool (QuestionPro) which creates a database 
automatically. We did not allow participants to leave questions blank, but participants could 
stop answering at any moment. We used the following protocol to remind participants to 
answer the questionnaire: After sending the survey, we sent a reminder every three days: 
twice via email, then to those who had provided a mobile phone number, we sent the survey 

 
 
two more times via text messaging. No incentive was provided in exchange for their 
participation in any of the study waves. The first round of data collection included questions 
regarding the period before the COVID-19 pandemic (wave 0) and during the pandemic 
(wave 1).  
 
Sample size calculation 
Prior to the beginning of the study, we calculated a sample size of 1046 participants to detect 
a small effect size (0.2), with a statistical power of 0.95, alpha of 0.05 and a factor of 2 to 
take into account the impact of attrition.  
 
Ethical approval 
The Scientific Ethics Committee from the Universidad de la Frontera and Universidad 
Católica del Norte approved the study in accordance with Law 20.120 (2006). We obtained 
electronic written consent from all participants.  
 
Statistical analysis 
We will exploit the variation in lockdown policies in the two regions to measure the effect 
of lockdown on alcohol use. For this purpose, we will use a difference-in-difference (DiD) 
design to compare the effect of lockdown in multiple treatment periods. DiD is a quasi-
experimental approach that allows using longitudinal data to obtain causal effects in the 
absence of randomization [33]. DiD is a well-established method in public health research 
and was first used by John Snow in his seminal study on the transmission of cholera in 1855 
[34].   
 
The canonical DiD consists of two time periods and two groups. One computes the difference 
in the mean outcomes of the treatment and control group after the treatment and subtract the 
difference that existed before treatment had any effect [35]. 
 
𝛿𝐷𝐷 = (𝑌𝑝𝑜𝑠𝑡𝑡𝑟𝑒𝑎𝑡 −𝑌
𝑝𝑟𝑒𝑡𝑟𝑒𝑎𝑡) −(𝑌𝑝𝑜𝑠𝑡𝑐𝑜𝑛𝑡𝑟𝑜𝑙 −𝑌
𝑝𝑟𝑒𝑐𝑜𝑛𝑡𝑟𝑜𝑙)  
 
The key identifying assumption is that, in the absence of treatment, the average outcomes 
would have followed parallel paths over time [33].  
 
As depicted in Figure 1, our case is more complex, as there are multiple time periods (seven 
in total) and two groups that are both treated and not-treated in different time periods. For 
𝜏periods and a particular time period denoted by 𝑡 where t=1,..., 𝜏, 𝑡0represents the baseline 
measurement captured retrospectively at 𝑡1. In time periods 𝑡1, 𝑡2and 𝑡3, the Coquimbo group 

 
 
is exposed to lockdown while the Araucanía group is exposed to less restrictive social 
distancing policies. At 𝑡4both groups are exposed to step 2 social distancing policies and at 
𝑡5and 𝑡6; this situation reverses, and Araucanía is exposed to lockdown and Coquimbo moves 
to less restrictive social policies. Treatment intensity 𝐷has values ranging from 5 (step 1) to 
1 (step 5) (see Table S2 for details).  
 
Figure 1.  Social distancing policies in Coquimbo and Araucanía for the study period 
 
 
 
In this setting, we will use a generalized difference-in-difference that allows for multiple 
treatment periods and several treatment intensities [36, 37]. The regression of a DiD model 
can be expressed in more general terms as  
 
(1) 
 
𝑌𝑖𝑠𝑡 =  𝛼 + 𝛿𝐷𝐷𝑇𝑅𝐸𝐴𝑇𝑠𝑡  + 𝜃𝑋𝑖𝑠𝑡 +
𝛽𝑖 + 𝛾𝑡 + 𝑒𝑖𝑠𝑡 
 
where 𝑌𝑖𝑠𝑡is the outcome for an individual 𝑠 at time 𝑡 and 𝑖is the region (Coquimbo or 
Araucanía), 𝛿𝐷𝐷 is the coefficient of interest of a treatment intensity variable, 𝑋𝑖𝑠𝑡 is a vector 
of control variables (e.g. age, sex), 𝛽𝑖 is a region fixed effect, and 𝛾𝑡 is a set of time fixed 
effects. The identifying assumption, in this case, relies on a common trend assumption that 
both treatment groups would develop equally over time under at least one of the treatments. 
It assumes effect homogeneity conditional on observables 𝑋𝑖𝑠𝑡. 
 
An alternative to adjustment by control variables would be to use propensity score matching 
(PSM). Recent analyses Daw and Hartfield (2018) suggest that using PSM could increase 
bias due to regression to the mean when treatment assignment occurs at the population level. 
In this context, the difference between treatment groups is stable and unmatched analysis is 
unbiased. Matching on the preperiod level introduces regression to the mean bias [38]. For 
this reason, we chose to adjust for control variables and not to use PSM.  
 

 
 
There is an ongoing debate about DiD when groups of units receive treatment at different 
times or different treatment intensities.[39, 40] Researchers are concerned this fixed effect 
regression provides greater weights to treatments with similar before and after treatment 
periods and uses treated units as controls.[39] This is unlikely to affect our study, as it has 
only two treated groups and thus no variation in treatment timing. Nonetheless, we will use 
the Callaway-Sant’Anna method (CS method) in sensitivity analyses. The method was built 
to handle staggered treatment adoption designs.[40] To accommodate this, we will divide the 
analysis into two sections (𝑡0versus 𝑡1, 𝑡2and 𝑡3) and (𝑡0versus 𝑡5and 𝑡6). 
 
The estimation will be done using linear mixed effects models. These models take into 
account the correlated nature of the data (repeated measures of the same individuals) and 
provide mathematically equivalent estimates than fixed effects linear regression. However, 
an additional advantage of linear mixed effects models is that they allow to vary the number 
of observations within each participant, handling missing data more efficiently than other 
analytical approaches [41].  
 
Statistical Software  
We will use R (current version 3.6.3) for all analyses. We will use the lme4 function to run 
the DiD model and the did package for the Callaway-Sant’Anna method. 
 
 
 
 
 
 
 
 

 
 
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Supplementary Appendix 
 
Table S1. Components of the step-by-step mobility restrictions for the COVID-19 pandemic in Chile during the study period 
 
Phase Curfew 
(22.00-
05.00) 
Lockdown 
Schools 
Restaurants 
and bars 
Gyms 
Public gatherings 
Cinemas, 
theatres and 
similar 
Closed 
spaces 
Local mobility 
Mobility 
permits 
Older adults 
Step 1 Yes 
Yes 
Remote 
education for 
preschool, 
elementary 
and higher 
schools 
Closed, only 
take away 
allowed 
Closed 
Forbidden 
Closed 
Customer 
service 
restricted to 
no more than 
1 person per 
10 square 
meters 
Passenger cruises 
forbidden. All buses 
must have a list of 
passengers for 
travelling times 
longer than 2 hours. 
Forbids travel to 
second residence.1 
Allowed 
Lockdown for 
residents in elderly 
care. Closure of day 
centers for older 
adults and meetings of 
"Clubes de Adultos 
Mayores" 
Step 2 Yes 
Yes, only 
Saturdays, 
Sundays 
and bank 
holidays 
Remote 
education for 
preschool, 
elementary 
and higher 
schools 
Open at 25% 
of their 
maximum 
capacity, 
maximum 
time two 
hours, only in 
open spaces 
Sports 
activities for 
maximum 10 
people in open 
spaces. Gyms 
closed 
Public events 
allowed for a 
maximum of 10 
people in a closed 
space and 20 people 
in an open space. 
Closed 
Customer 
service 
restricted to 
no more than 
1 person per 
10 square 
meters 
Passenger cruises 
forbidden. All buses 
must have a list of 
passengers for 
travelling times 
longer than 2 hours. 
Forbids travel to 
second residence.1 
Allowed 
Lockdown for 
residents in elderly 
care. Closure of day 
centers for older 
adults and meetings of 
"Clubes de Adultos 
Mayores" 

 
 
Step 3 Yes 
No 
Allowed after 
permission 
from 
Regional 
Secretary of 
Education 
Open at 25% 
of their 
maximum 
capacity, 
maximum 
time two 
hours, only in 
open spaces 
Sports 
activities for 
maximum 25 
people in open 
spaces and 5 
people in 
closed spaces, 
including gyms 
"Oficios, ritos, 
seminarios and 
ceremonias" allowed 
for a maximum of 25 
people in a closed 
space and 50 people 
in an open space. 
Closed 
Customer 
service 
restricted to 
no more than 
1 person per 
10 square 
meters 
Allows travel to 
second place of 
residence 
Allowed 
Lockdown for 
residents in elderly 
care. Closure of day 
centers for older 
adults and meetings of 
"Clubes de Adultos 
Mayores" 
Step 4 Yes 
No 
Allowed after 
permission 
from 
Regional 
Secretary of 
Education 
Open at 50% 
of their 
maximum 
capacity 
Sports 
activities for 
maximum 50 
people in open 
spaces and 10 
people in 
closed spaces, 
including gyms 
"Oficios, ritos, 
seminarios and 
ceremonias" allowed 
for a maximum of 50 
people in a closed 
space and 100 people 
in an open space. 
Open at 50% 
of maximum 
capacity 
Customer 
service 
restricted to 
no more than 
1 person per 
5 square 
meters 
Allows travel to 
second place of 
residence 
Allowed 
Lockdown for 
residents in elderly 
care. Closure of day 
centers for older 
adults and meetings of 
"Clubes de Adultos 
Mayores" 
Step 5 Yes 
No 
Allowed after 
permission 
from 
Regional 
Secretary of 
Education 
Open at 75% 
of maximum 
capacity 
Sports 
activities for 
maximum 100 
people in open 
spaces and 20 
people in 
closed spaces, 
including gyms 
"Oficios, ritos, 
seminarios and 
ceremonias" allowed 
for a maximum of 
100 people in a 
closed space and 200 
people in an open 
space. 
Open at 75% 
of maximum 
capacity 
Customer 
service 
restricted to 
no more than 
1 person per 
5 square 
meters 
Allows travel to 
second place of 
residence 
Allowed 
Visits to elderly care 
centers are allowed. 
Day centers for older 
adults open 
1. Except people older than 65 years old and with chronic conditions. They are allowed to move but must remain in quarantine. 
Data based on Resolución Exenta 591 from the Chilean Ministry of Health, July 23, 2020 

 
 
Table S2. Mobility permits during step 1 (lockdown) in Chile during the study period 
 
 
Permit 
Duration 
Appointment in a health care centre 
3 hours 
Shopping for essential goods (food, medications, etc) 
3 hours 
Going out for a person with autistic spectrum disorder 
or any other cognitive disability 
2 hours, no 
weekly limit 
Walking dogs and other pets, two blocks around the 
place of residence 
30 minutes 
Payment of household expenses or collecting pensions 
or State subsidies 
3 hours 
Attending funerals of direct relatives 
5 hours1 
Collecting textbooks, school food or technological 
devices for school purposes 
5 hours 
Attending a court appointment 
No limit 
Take food or other essential products to older adults 
2 hours 
Take food or other essential products to prison inmates 
3 hours 
Transport children or adolescents between parents or 
caretakers’ residences 
2 hours 
Visits to people with disabilities that are hospitalized 
3 hours 
Weddings or civil unions, including a maximum of 5 
companions 
4 hours 
Donate blood 
4 hours 
Taking care of older adults and people with disabilities 
No limit 
Other important and urgent matters authorized in person 
by the Chilean Police Force 
Depend 
 
1. If the funeral is in the same region, 24 hours if it's in a different region than the one of residence