Abstract
Background
In response to COVID-19, government-mandated health directives including widespread lockdowns were implemented. Changes in alcohol purchasing were reported, with growing concern that alcohol may be consumed as a way to cope with pandemic-associated stressors. Hitherto, there have been limited studies examining alcohol-related harms, including acute harms requiring an ambulance, and their relationship to government announcements or policies related to COVID-19.
Methods
Analyses were conducted between January and September 2020, with matched months in 2019, using Victorian data from the National Ambulance Surveillance System in Australia. Interrupted time series (ITS) models with odds ratios (OR) were used to map alcohol-related harms as a function of government policies for both metropolitan and regional areas.
Findings
A total of 43,003 alcohol intoxication-related ambulance attendances occurred between January 2019 and September 2020. Attendances in the home increased in 2020 by 9% compared to matched 2019 months. The most socioeconomically advantaged cases showed the highest percentage change. ITS models showed decreased odds of alcohol-related attendances at the beginning of each COVID-19 wave in metropolitan (OR:0•77; 95%CI: 0•71-0•83; p<0•001) and regional Victoria (OR: 0•72; 95%CI: 0•67-0•79, p<0•001) separately, and increased odds following the introduction of harsher restrictions in metropolitan Melbourne (OR:1•07; 95%CI:1•01-1•11, p=0•005). A 19% increase in odds of alcohol-related harms was observed at the end of the second wave lockdown period in regional Victoria (OR:1•19; 95%CI: 1•01-1•41, p=0•004).
Interpretation
Alcohol-related attendances during COVID-19 restrictions showed a displacement to home settings. Changes in patterns of harms were evident in specific sociodemographic groups, and geographic regions when mapped to government health directives. This study is one of the first to investigate alcohol-related harms at the population level in response to a global pandemic.
Funding
Commonwealth Department of Health and Victorian Department of Health.
Keywords: Alcohol, alcohol harms, intoxication, COVID-19, paramedicine, ambulance, government policy
Research in context.
Evidence before this study
We examined the literature for publications examining alcohol consumption, alcohol intoxication, and alcohol harms throughout the COVID-19 pandemic, in addition to previous natural disasters and financial crises. Many studies identified the detrimental mental health impacts of these events and raised concerns regarding increased alcohol use as a coping mechanism to deal with increased feelings of stress, anxiety, loss, isolation and economic uncertainty. Despite a number of previous studies investigating changes in community alcohol consumption pre- and post-COVID 19, research assessing changes in alcohol-related harms were scarce.
Added value of this study
The National Ambulance Surveillance System (NASS) offers an internationally unique opportunity to capture and surveil alcohol and other drug-related harms through the use of ambulance attendance records. We examined Victorian NASS data given the strict restrictions placed on citizens in this state, and conducted one of the first studies investigating the impact of COVID-19 restrictions on acute alcohol-related harms by gender, age, location (e.g., in the home versus public venues) and socioeconomic status, in both metropolitan and regional Victoria.
Implications of all available evidence
This comprehensive analysis of alcohol-related ambulance attendances throughout the 2020 COVID-19 period when compared to the same months in 2019, offers unique insight into alcohol harms experienced during a period of increased stress, anxiety, feelings of isolation and economic uncertainty. We found demographic and location differences, including a displacement of harms into home settings, and changes in relation to government announcements. Our findings emphasise the need for more campaigns that encourage safer alcohol consumption during times of psychological and financial stress that accompany changes in government public health policies including lockdowns.
Alt-text: Unlabelled box
1. Introduction
The COVID-19 pandemic is a worldwide public health emergency. It has resulted in substantial negative impacts on the health and wellbeing of both individuals and economies [1]. Governments around the world have implemented policies aimed at containing the spread of the virus. Measures have included social distancing (e.g., people sitting at least 1.5 metres apart in workplaces and on public transport) and lockdowns (e.g., limiting reasons for leaving home to only four reasons: shopping for food and supplies, authorised work and study, caregiving, and exercise) which have had detrimental effects on people's mental health [2]. This has led to concerns of increased alcohol and other drug use in order to cope with stress, anxiety, feelings of isolation, and economic uncertainty [3,4], which have been documented following exposure to previous natural disasters and financial crises [5,6].
1.1. Alcohol use during COVID-19
Changes in alcohol purchasing patterns have been reported in many parts of the world, with online alcohol sales in the US increasing by 243% compared with the same time the previous year, and an analysis of online credit and debit card transactions showing increases in alcohol sales in Australia [7]. Some increases have been attributed to the ‘panic-buying’ of alcohol, and others reflect changes in the regulatory environment. For example, in response to strict social distancing guidelines, most jurisdictions in Australia relaxed liquor licencing regulations to enable any licenced premises (e.g., restaurants and cafes, small bars) that do not normally sell off-premise alcohol to sell alcohol via take-away or home delivery schemes [7,8]. These changes in alcohol availability and purchasing behaviour have led to concerns for vulnerable groups, including those with alcohol use and/or mental health disorders. While evidence on outcomes is only beginning to emerge, a recent national cross-sectional study of emergency department (ED) presentations in the US reported varied patterns of help-seeking; mental health presentations decreased initially following the declaration of a national emergency, but this decrease was to a lesser extent than total ED presentations, suggesting that acute mental health cases reflected a significant public health concern [4]. Drug overdoses presenting to ED also increased during this time, suggesting an increased burden of drug-related harms to emergency services [4].
There has been growing concern that increased alcohol consumption in the general community may be seen as an acceptable strategy to deal with the stress, anxiety, and financial hardships associated with the COVID-19 pandemic [9,10]. An analysis comparing alcohol consumption between April-May 2020 with the same months in 2019 reported that although population per capita consumption did not change, some sub-populations did report modifying their alcohol consumption [11] with 15% of the population drinking at levels in 2020 that placed them in a higher risk category for alcohol-related harm according to national guidelines. This finding supports previous research that reported no change in weekly alcohol consumption and/or frequency of intoxication between 6 to 24 months post-tsunami in Norway, but that 18•3% of respondents had increased their alcohol consumption [12]. Such findings highlight the need to examine alcohol use beyond simple per capita figures when assessing alcohol-related changes post-disaster. Such analyses leave a gap in our understanding of which sections of the population are increasing their consumption in response to these stressors, and whether they also experience an increase in alcohol-related harms.
Recent data have suggested that changes in alcohol consumption are influenced by sociodemographic factors (e.g., age, gender, social disadvantage). An Australian study reported that young men were drinking more at home given a lack of access to public licenced venues [11], and another reported that increased alcohol consumption was associated with pre-existing mental health issues including depression, lack of social connection and income loss during the first month of COVID-19 restrictions implemented in Canada [9]. Despite this, the focus of these studies has been limited to assessing changes in alcohol consumption in the community compared with their drinking levels pre-pandemic. Research assessing changes in alcohol-related harms are sparse, and have not assessed whether these purported changes in consumption, or location (e.g., home-based drinking) have resulted in increased alcohol-related harms. This lack of focus on alcohol harms is of concern given that alcohol is a causal or component risk factor in more than 200 disease and illness categories [13], and is a leading risk factor for premature death and disability in young people [14].
Additionally, of the studies that have addressed alcohol-related harms, survey designs have been most frequently used. A significant limitation with surveys assessing COVID-19 impacts on health and behaviour is the use of self-report measures of alcohol use, and the potential for recall bias and social desirability effects. Such designs are also unable to extrapolate changes in alcohol consumption to changing policy and social environments, which have occurred frequently during COVID-19 [15]. Furthermore, surveys administered during COVID-19 have typically used short sampling frames (e.g., one-week) that make it difficult to assess any impact of rapidly evolving policy changes on behaviour [16]. Given previous research has reported associations between changes in economic policies during recession times and daily suicides in England and Wales [17], there is a need to utilise surveillance systems that are more effectively able to track harms in relation to COVID-19 policies as they evolve.
Ambulance services are part of the frontline health response to acute crises, including alcohol harms, and are frequently the first contact a person has with health services [18,19]. In Victoria (Australia), ambulance services provide universal coverage in both metropolitation and regional areas, and therefore, utilising the surveillance, monitoring, and reporting capacity of ambulance data provides a unique opportunity to examine, and compare alcohol-related harms at the population level [18,20]. This paper aimed to: (i) investigate changes in alcohol-intoxication-related ambulance attendances from January to September 2020 compared with the same months in 2019 to determine whether there had been increases in alcohol-related harms experienced in the home matching the displacement of reported consumption following closure of licenced venues; (ii) determine whether there were sociodemographic differences in alcohol-related ambulance attendances based on age, gender and social disadvantage with expected increases in young adults (<40 years), and (iii) map alcohol-related harms as a function of government policies in response to COVID-19 that enforced social distancing measures and ‘lockdowns’ on citizens.
2. Methods
2.1. The National Ambulance Surveillance System (NASS)
We used data from the Victorian arm of NASS. Victoria is Australia's second most populous state with approximately 6 million residents. NASS is an ongoing surveillance system that receives a filtered dataset consisting of attendances from the electronic Victorian Ambulance Clinical Information Service (VACIS®) where alcohol or another drug play a significant and contributing factor. These data are coded by researchers following import to a customised database. NASS methodology is described in detail in methodological papers [18,20] but relevant inclusion criteria for the present study are described below. The overall project and surveillance methodology was approved by the Eastern Health Research Ethics Committee.
2.2. Inclusion of alcohol intoxication ambulance attendances
Alcohol intoxication-related ambulance attendances between 1 January 2020 and 30 September 2020 plus matched dates for 2019 were included.
Inclusion criteria for alcohol intoxication coding of cases was assessed using the following criterion: ‘Is it reasonable to attribute the immediate or recent (the past 24-hours) over or inappropriate alcohol use as a contributing reason for the ambulance attendance?’ [20]. This information was drawn from paramedic clinical notes and assessment, patient self-report, information from third parties (e.g., family, friends or bystanders), and evidence at the scene (e.g., alcohol-related products). Importantly, while alcohol consumption must be a contributor to the ambulance attendance, it may not be the primary reason for the ambulance attendance [20]. Ambulance attendances for alcohol-intoxication are a marker of alcohol 'harms' in a broad sense, and no further break down of other 'harms' experienced, or various sub-categories was undertaken in this analysis. Indeed, calling for, and requiring an ambulance for intoxication is taken as a significant harm.
2.3. Location and social disadvantage
As a proxy for alcohol intoxication in the home, patient postcode (residential address) and scene postcode (place of ambulance attendance) were compared. Where these two postcodes matched, alcohol consumption was considered to be in the home setting. We present data separately for metropolitan Melbourne and regional Victoria given differences in restrictions imposed by government (see Supplementary file 1). Socioeconomic status was determined based on the Australian Bureau of Statistics (ABS) Socioeconomic Index for Areas (SEIFA) index of relative socioeconomic disadvantage.
2.4. Key events and government policy announcements
Policy measures enacted in Victoria during 2020 included social distancing (e.g., people required to sit at least 1•5 metres apart in workplaces and on public transport) and lockdowns (e.g., people only allowed to leave the home for four reasons: shopping for food and supplies, authorised work and study, caregiving, exercise, and being limited to travel within a 5km zone). The identification of key events and policies related to COVID-19 were logged on a daily basis and considered relevant if: (i) the event or policy was a public announcement linked directly to COVID-19, and (ii) the announcement was made by key members of government (e.g., Victorian State Premier or the Prime Minister of Australia) (see Supplementary file 1 for key policies or events mapped to key dates). Events were also considered when multiple media sources (online newspapers, television news) were reporting on a story of significance (for example, new clusters or peaks in COVID-19 related cases).
2.5. Data analyses
All descriptive and statistical analyses were performed using Stata v13•1. Frequencies, percentages and percentage change figures describe overarching socio-demographic and location of consumption patterns. Rates are calculated per 100,000 population using data provided by the Australian Bureau of Statistics [21]. For the interrupted time series, we proposed a priori a change in level and slope as our impact model. Linear splines were used to create the intervention periods for metropolitan Melbourne and Mitchell Shire (a local government area, 40 km north of Melbourne that was placed under the same restrictions as Melbourne, see Supplementary file), and the remainder of regional Victoria, corresponding to Victorian State Government public health directives. The interrupted time series were modelled using logistic regression with a negative binomial probability distribution, log-link function and Newey-West standard errors. Autocorrelation and partial autocorrelation were assessed using the Cumby-Huizinga test and correlograms and corrected using linear splines (Supplementary file 2). Stationarity of the time series was assessed using the Portmanteau test.
2.6. Role of funding source
Funders had no role in the study design, conduct, analysis, or interpretation.
3. Results
During the months of January to September 2019 and 2020, there were a total of 43,003 (2019 n=22,056; 2020 n=20,947) alcohol intoxication-related attendances in Victoria, with a monthly average of 2,389 attendances. Of these, 81% (2019: 78.7%, 2020: 82.6%) were transported to hospital for ongoing care. In metropolitan Melbourne, the total rate of attendances was 629•7 per 100,000 population compared to 722•1 per 100,000 population in regional areas of Victoria.
3.1. Alcohol attendance in the home and sociodemographic modifiers
Table 1 shows that overall, the number of monthly alcohol intoxication-related attendances in the home increased during 2020 compared with 2019. This pattern was consistent across age groups and among males and females, but particularly those aged 30 to 39 years.
Table 1.
Frequencies and percentage changes in alcohol intoxication-related ambulances attendances in the home, 2019-2020, by month, age group and gender (values >or <5% are bolded)
| Jan | Feb | Mar | April | May | June | July | Aug | Sept | Total | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Age group: males | |||||||||||
| 10 to 19 | 2019 (n) | 69 | 38 | 48 | 43 | 25 | 49 | 42 | 47 | 53 | 414 |
| 2020 (n) | 51 | 60 | 62 | 25 | 49 | 48 | 34 | 48 | 54 | 431 | |
| % change | -26•1 | 57•9 | 29•2 | -41•9 | 96•0 | -2•0 | -19•0 | 2•1 | 1•9 | 4.1 | |
| 20 to 29 | 2019 (n) | 169 | 132 | 139 | 119 | 111 | 110 | 129 | 117 | 151 | 1177 |
| 2020 (n) | 142 | 132 | 127 | 93 | 139 | 163 | 149 | 155 | 149 | 1249** | |
| % change | -16•0 | 0•0 | -8•6 | -21•8 | 25•2 | 48•2 | 15•5 | 32•5 | -1•3 | 6.1 | |
| 30 to 39 | 2019 (n) | 148 | 146 | 157 | 132 | 139 | 143 | 126 | 155 | 157 | 1303 |
| 2020 (n) | 188 | 172 | 164 | 156 | 173 | 171 | 137 | 186 | 180 | 1527 | |
| % change | 27•0 | 17•8 | 4•5 | 18•2 | 24•5 | 19•6 | 8•7 | 20•0 | 14•6 | 17.2 | |
| 40 to 49 | 2019 (n) | 188 | 156 | 168 | 151 | 171 | 218 | 185 | 190 | 209 | 1636 |
| 2020 (n) | 182 | 176 | 206 | 190 | 191 | 172 | 210 | 235 | 236 | 1798 | |
| % change | -3•2 | 12•8 | 22•6 | 25•8 | 11•7 | -21•1 | 13•5 | 23•7 | 12•9 | 9.9 | |
| 50 to 59 | 2019 (n) | 197 | 141 | 197 | 183 | 182 | 155 | 183 | 200 | 180 | 1618 |
| 2020 (n) | 197 | 208 | 195 | 180 | 174 | 179 | 199 | 211 | 210 | 1753* | |
| % change | 0•0 | 47•5 | -1•0 | -1•6 | -4•4 | 15•5 | 8•7 | 5•5 | 16•7 | 8.4 | |
| 60 + | 2019 (n) | 225 | 182 | 216 | 209 | 175 | 180 | 216 | 209 | 210 | 1822 |
| 2020(n) | 277 | 246 | 205 | 169 | 205 | 226 | 206 | 203 | 197 | 1934 | |
| % change | 23.1 | 35.2 | -5.1 | -19.1 | 17.1 | 25.6 | -4.6 | -2.9 | -6.2 | 6.1 | |
| Age group: females | |||||||||||
| 10 to 19 | 2019 (n) | 38 | 38 | 52 | 44 | 36 | 47 | 40 | 54 | 53 | 402 |
| 2020 (n) | 66 | 54 | 51 | 19 | 41 | 56 | 43 | 41 | 47 | 418* | |
| % change | 73•7 | 42•1 | -1•9 | -56•8 | 13•9 | 19•1 | 7•5 | -24•1 | -11•3 | 4.0 | |
| 20 to 29 | 2019 (n) | 103 | 97 | 102 | 89 | 92 | 102 | 90 | 89 | 86 | 850 |
| 2020 (n) | 98 | 98 | 103 | 87 | 100 | 120 | 104 | 119 | 159 | 988 | |
| % change | -4•9 | 1•0 | 1•0 | -2•2 | 8•7 | 17•6 | 15•6 | 33•7 | 84•9 | 16.2 | |
| 30 to 39 | 2019 (n) | 115 | 103 | 109 | 110 | 96 | 97 | 88 | 108 | 122 | 948 |
| 2020 (n) | 136 | 111 | 115 | 107 | 140 | 129 | 111 | 157 | 126 | 1132 | |
| % change | 18•3 | 7•8 | 5•5 | -2•7 | 45•8 | 33•0 | 26•1 | 45•4 | 3•3 | 19.4 | |
| 40 to 49 | 2019 (n) | 161 | 105 | 144 | 123 | 164 | 120 | 162 | 163 | 145 | 1287 |
| 2020 (n) | 130 | 153 | 154 | 138 | 129 | 137 | 147 | 133 | 149 | 1270 | |
| % change | -19•3 | 45•7 | 6•9 | 12•2 | -21•3 | 14•2 | -9•3 | -18•4 | 2•8 | -1.3 | |
| 50 to 59 | 2019 (n) | 139 | 99 | 108 | 118 | 107 | 109 | 113 | 105 | 120 | 1018 |
| 2020 (n) | 137 | 125 | 122 | 115 | 126 | 131 | 114 | 147 | 134 | 1151 | |
| % change | -1•4 | 26•3 | 13•0 | -2•5 | 17•8 | 20•2 | 0•9 | 40•0 | 11•7 | 13.1 | |
| 60 + | 2019 (n) | 100 | 96 | 111 | 85 | 93 | 96 | 101 | 104 | 76 | 862 |
| 2020 (n) | 109 | 90 | 120 | 81 | 106 | 109 | 82 | 74 | 104 | 875 | |
| % change | 9.0 | -6.3 | 8.1 | -4.7 | 14•0 | 13.5 | -18.8 | -28.8 | 36.8 | 1.5 | |
| Total (all) | 2019 (n) | 1675 | 1351 | 1584 | 1431 | 1417 | 1447 | 1506 | 1561 | 1582 | 13554 |
| 2020 (n) | 1725 | 1649 | 1657 | 1386 | 1592 | 1660 | 1561 | 1725 | 1762 | 14717** | |
| % change | 3.0 | 22.1 | 4.6 | -3.1 | 12.4 | 14.7 | 3.7 | 10.5 | 11.4 | 8.6 |
*p <0.05, ** p=0.000
Figure 1 and Table 2 show data based on drinking location and Socioeconomic Index for Areas (SEIFA) status.
Figure 1.
Proportion (%) of alcohol intoxication-related ambulance attendances by location, Victoria.
Table 2.
Frequencies and percentage changes in alcohol intoxication-related ambulances attendances in the home, 2019-2020, by month and socio economic status (SEIFA)
| SEIFA | Jan | Feb | Mar | April | May | June | July | Aug | Sept | Total | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0-20% | 2019 (n) | 452 | 346 | 442 | 407 | 376 | 406 | 406 | 401 | 461 | 3697 |
| (most disadvantaged) | 2020 (n) | 443 | 424 | 456 | 372 | 408 | 441 | 405 | 455 | 486 | 3890** |
| % change | -2•0 | 22•5 | 3•2 | -8•6 | 8•5 | 8•6 | -0•2 | 13•5 | 5•4 | 5.2 | |
| 21-40% | 2019 (n) | 291 | 260 | 285 | 271 | 271 | 244 | 254 | 294 | 277 | 2447 |
| 2020 (n) | 304 | 293 | 290 | 244 | 300 | 296 | 305 | 311 | 349 | 2692* | |
| % change | 4•5 | 12•7 | 1•8 | -10•0 | 10•7 | 21•3 | 20•1 | 5•8 | 26•0 | 10.0 | |
| 41-60% | 2019 (n) | 306 | 246 | 277 | 231 | 260 | 238 | 295 | 282 | 246 | 2381 |
| 2020 (n) | 333 | 319 | 286 | 248 | 288 | 302 | 296 | 293 | 276 | 2641 | |
| % change | 8•8 | 29•7 | 3•2 | 7•4 | 10•8 | 26•9 | 0•3 | 3•9 | 12•2 | 10.9 | |
| 61-80% | 2019 (n) | 349 | 277 | 294 | 277 | 256 | 295 | 280 | 254 | 324 | 2606 |
| 2020 (n) | 321 | 310 | 328 | 280 | 306 | 304 | 274 | 344 | 313 | 2780* | |
| % change | -8•0 | 11•9 | 11•6 | 1•1 | 19•5 | 3•1 | -2•1 | 35•4 | -3•4 | 6.7 | |
| 81-100% | 2019 (n) | 275 | 222 | 283 | 244 | 251 | 263 | 271 | 328 | 274 | 2411 |
| (least disadvantaged) | 2020 (n) | 323 | 300 | 293 | 239 | 289 | 316 | 279 | 321 | 338 | 2698 |
| % change | 17•5 | 35•1 | 3•5 | -2•0 | 15•1 | 20•2 | 3•0 | -2•1 | 23•4 | 11.9 | |
| Total | 2019 (n) | 1673 | 1351 | 1581 | 1430 | 1414 | 1446 | 1506 | 1559 | 1582 | 13542 |
| 2020 (n) | 1724 | 1646 | 1653 | 1383 | 1591 | 1659 | 1559 | 1724 | 1762 | 14701** | |
| % change | 3.0 | 21.8 | 4.6 | -3.3 | 12.5 | 14.7 | 3.5 | 10.6 | 11.4 | 8.6 |
Note: 28 missing cases, *p <0.05, ** p=0.000
Figure 1 shows that the proportion of alcohol intoxication-related attendances in a home setting increased during 2020, from 60% in January to 81% in September. In contrast, during 2019, these figures remained stable throughout the year. On average, there was a 9% monthly increase in alcohol intoxication-related attendances occurring in the home during 2020 when compared with 2019. Table 2 shows that those in the most disadvantaged group (0-20%) had the highest number of alcohol-related ambulance attendances in the home in both 2019 and 2020, however, the group showed the least amount of change across many months examined when comparing the two years. On average, those in the most advantaged (81-100%) group had the highest percentage change in alcohol attendances in the home between the corresponding months in 2019 and 2020.
3.2. Interrupted time series
Tables 3 and 4 display the results of the interupted time series assessing the effect of government announcements related to COVID-19 on alcohol-related attendances in metropolitan Melbourne (Table 3) and regional Victoria (Table 4). Table 3 shows that there was an initial 23% decrease in the odds of alcohol-related ambulance attendance (OR:0•77; 95%CI: 0•71-0•83, p<0•001) after the implementation of first wave Stage 3 COVID-19 restrictions, followed by an increase in odds of attendance by 15% at the end of first wave restrictions (OR: 1•15; 95%CI: 1•02-1•30, p=0•02). At the beginning of wave two Stage 3 lockdown restrictions, a statistically significant decrease in the odds of alcohol-related ambulance attendance by 10% (OR:0•90; 95%CI:0•86-0•95; p<0•001) was observed, followed by an increase in odds of attendance by 5% at the introduction of Stage 4 lockdown restrictions (OR:1•07; 95%CI:1•01-1•11, p=0•005). A significant decrease in odds of alcohol-related ambulance attendance was observed at the end of the second wave lockdown period (OR: 0•84; 95%CI: 0•78-0•91, p<0•001), to a similar magnitude to the decrease observed after the first wave of lockdown. There were minimal slope changes following each intervention period. The Portmanteau test reported moderate evidence for stationarity (q=56•1; p=0•05)
Table 3.
Logistic regression model assessing the effect of the Victorian Department of Health and Human Services (DHHS) COVID-19 public health response on alcohol-related harms resulting in ambulance attendance in Metropolitan Melbourne and Mitchell Shire
| Parameter | Description | Odds Ratio (OR) | 95% CI | p-value |
|---|---|---|---|---|
| Pre-intervention time slope | Pre-COVID period* | 1•00 | 1•00 | 0•08 |
| Change in time slope at first intervention | Wave 1: Stages 1-3 lockdown** | 1•00 | 0•97-1•01 | 0•44 |
| Change in level after first intervention | 0•77 | 0•71-0•83 | <0•001 | |
| Change in time slope at second intervention | End of Wave 1: Easing of lockdown⁎⁎⁎ | 1•00 | 0•98-1•02 | 0•75 |
| Change in level after second intervention | 1•15 | 1•02-1•30 | 0•02 | |
| Change in time slope at third intervention | Wave 2: Stage 3 lockdownα | 1•00 | 0•98-1•01 | 0•35 |
| Change in level after third intervention | 0•90 | 0•86-0•95 | <0•001 | |
| Change in time slope at fourth intervention | Wave 2: Stage 4 lockdownβ | 1•02 | 1•00-1•03 | 0•031 |
| Change in level after fourth intervention | 1•07 | 1•02-1•11 | 0•005 | |
| Change in time slope at fifth intervention | End of Wave 2: Easing of lockdownπ | 1•06 | 1•04-1•07 | <0•001 |
| Change in level after fifth intervention | 0•84 | 0•78-0•91 | <0•001 |
Refer to greyed out cells in Supplementary 1 File
Table 4.
Logistic regression model assessing the effect of the Victorian Department of Health and Human Services (DHHS) COVID-19 public health response on alcohol-related harms resulting in ambulance attendance in Regional Victoria
| Parameter | Description | Odds Ratio (OR) | 95% CI | p-value |
|---|---|---|---|---|
| Pre-intervention time slope | Pre-COVID period* | 1•00 | 1•00 | 0•14 |
| Change in time slope at first intervention | Wave 1: Stages 1-3 lockdown⁎⁎ | 1•00 | 1.00-1.02 | 0.04 |
| Change in level after first intervention | 0.72 | 0.67-0.79 | <0.001 | |
| Change in time slope at second intervention | End of Wave 1: Easing of lockdown† | 1•00 | 0•98-1•01 | 0•28 |
| Change in level after second intervention | 1•11 | 1•04-1•18 | 0•001 | |
| Change in time slope at third intervention | Wave 2: Stage 3 lockdown§ | 1•00 | 0•98-1•04 | 0•66 |
| Change in level after third intervention | 0•85 | 0•76-0•96 | 0•005 | |
| Change in time slope at fourth intervention | End of Wave 2: Easing of lockdownΩ | 1•00 | 0•96-1•03 | 0•69 |
| Change in level after fourth intervention | 1•19 | 1•01-1•41 | 0•04 |
Refer to greyed out cells in Supplementary 1 File
Table 4 shows that alcohol-related ambulance attendances in regional Victoria varied throughout the COVID-19 lockdown periods. An initial 28% decrease in the odds of alcohol-related ambulance attendance (OR: 0•72; 95%CI: 0•67-0•79, p<0•001) was observed after the implementation of first wave Stage 3 COVID-19 restrictions, followed by an increase in odds of attendance by 11% at the end of the first wave (OR: 1•11; 95%CI: 1•04-1•18, p<0•001). At the beginning of wave two Stage 3 lockdown restrictions, there was a 15% decrease in the odds of alcohol-related ambulance attendance (OR:0•85; 95%CI:0•76-0•96; p=0•005), followed by a 19% increase in the odds of alcohol-related ambulance attendance at the end of the second wave lockdown period (OR:1•19; 95%CI: 1•01-1•41, p=0•004). There was no change in slope following each of the intervention periods. The Portmanteau test reported strong evidence for stationarity (q= 33•9; p=0•7).
4. Discussion
We utilised novel surveillance data to examine changes in alcohol intoxication-related ambulance attendances during 2020 months associated with significant COVID-19 restrictions in Victoria compared with matched months in 2019. Similar to a New Zealand based study [19], we found that overall alcohol-intoxication related attendances were comparable to, or declined, during early 2020 in response to government announcements. However, alcohol-intoxication attendances did increase as the lockdown progressed, and may represent people using greater amounts of alcohol to cope with extended periods of lockdown. In our study, there were differences in alcohol-intoxication attendances based on time relative to government announcements, sociodemographic factors, economic disadvantage, and location; each having important public policy implications.
Broadly, alcohol-related ambulance attendances decreased at the beginning of each wave of restrictions in both metropolitan and regional Victoria. Subsequent increases in these harms were seen in both geographic areas towards the end of the first wave, a pattern that was replicated following a second wave of restrictions. These changes could reflect either a rebound effect representing greater opportunities to drink with, and socialise with small groups as the easing of restrictions were approached, or alternatively may represent alcohol-related harms increasing over time as the pandemic progressed, potentially as a result of increasing anxiety or stress related to the impact of isolation and financial instability. Similar patterns in help-seeking in EDs have been observed following pandemic onset in Europe and the US [4,12] in studies examining ED-related attendances. There have been concerns that the stress associated with isolation may serve as a significant trigger for increased alcohol use [22], particularly amongst vulnerable groups (e.g., those with a mental health disorder or who had a relationship with someone who fell ill due to COVID-19) and certain sociodemographics including older adults, and essential workers [23]. A recent review of alcohol consumption and harms noted that health organisations around the world developed recommendations on coping with social distancing and/or isolation, with advice on avoiding the use of alcohol as a coping strategy [22]. In contrast, the alcohol industry increased their advertising to encourage and normalise alcohol consumption as a means to deal with the isolation and boredom of lockdown [24]. The present study suggests that any public health messaging or advice around alcohol must counter advertising from the alcohol industry and timed towards the end of restrictions (when acute alcohol harms increased), and may best be targeted at specific demographic groups.
COVID-19 has seen changes in alcohol consumption. In addition to initial panic buying in response to mandated stay-at-home orders, surveys have reported changes in drinking at home in specific demographic groups including young males [11], and adults with young children [9]. Some of these changes in consumption have been interpreted as displaced drinking due to restricted access to on-premise venues such as pubs and clubs [11]. To date, however, any data assessing alcohol-related harms has been limited. We found that changes in sociodemographic factors such as age and gender may be particularly important. Indeed, 30-39 year old male and female groups showed increases between 18% and 45% in these harms during the middle of the year compared with the same months in 2019. Conversely, there were decreases in younger age groups, with 20-29 year old males having fewer alcohol-related harms early during restrictions (to the magnitude of between 8% and 21%), however these were not sustained with subsequent months showing rebounds of 25% and 48% in ambulance attendances for alcohol intoxication. While there has been relatively stable per-capita alcohol consumption and decreases in drinking among young adults in many Western countries including Australia, the proportion of heavy alcohol consumers has also increased [25], and this group is likely responsible for the higher rates of harm seen in this study. Targeting heavy drinkers and/or those with alcohol dependence is vital given this population may have poorer outcomes if infected by COVID-19 due to comprised respiratory or immune systems [3,26].
Socio-economic disadvantage was an important driver of acute alcohol harms reported on in this study. Although the most disadvantaged groups (determined using SEIFA scores) experienced the most alcohol-related ambulance attendances in both 2019 and 2020, the greatest change occurred in the least disadvantaged groups, placed in the top 20% of the community. This was also compounded by age, with older cohorts more likely to call an ambulance for an alcohol-related concern. The increase in harms seen in more advantaged groups over time in our dataset may reflect a larger disposable income as a result of travel/socialising restrictions, and job security. This is concerning given the increases in alcohol purchases reported in many jurisdictions during COVID-197, and suggests that increased alcohol availability resulting from easing of licencing restrictions allowed greater access to alcohol in the community, and this policy change should be reviewed based on accumulating harm data. Equally, re-iterating safe drinking guidelines is important at the community level, but also in older adults given that excess alcohol consumption has been associated with an increased incidence in falls [27]. Although the present study did not assess increasing incidence of any illness or injury type, the overall acute nature of the response, and severity in requiring an ambulance suggests that the harm experienced was not trivial. The nature of these cases may also impact upon paramedics themselves, and future studies should examine the impact of these cases on emergency personnel, and whether any extra support or training is needed.
4.1. Limitations and Future directions
While representing a novel and rich data source, ambulance records likely present an under-representation of all alcohol-related harms, as they only include cases that were serious enough to require an ambulance attendance, thus excluding cases where people sought assistance via their local doctor or directly through the hospital system, noting that in 2020 access to these services may have been reduced during lockdown restrictions. Additionally, this dataset is primarily morbidity-focussed, and therefore fatal events (including suicide) are under-represented, as ambulances do not attend all deaths. A further limitation is that data are collected for operational rather than research purposes with paramedics only recording information they deem clinically relevant to patient care and/or stablisation en route to hospital, with only one-year of comparison data included in this study. Our Victorian dataset is filtered to capture attendances associated with acute alcohol, other drug, suicide, self-harm and mental health related attendances, and does not include all primary diagnoses, and is therefore likely to be an under-estimation of total alcohol-attributable harms. Future analyses could also examine the types of harms experienced (e.g., related to falls, mental health crises or loss of conciousness) in order to determine the sub-types of harm experienced in these attendances.
Additionally, the monthly changes, when broken by age group should be treated with caution given that the numbers of incidents in certain cell sizes are low. Despite these limitations, the dataset is derived from electronic patient care records written, on scene, by paramedics. These records document observations relevant to patient care, and can include information like the presence of empty bottles or drug paraphrenalia, suicide notes, other persons on scene and their demeanour or role in the incident. This detailed information complements existing population health metrics (e.g., hospital and ED presentations), particularly given their state-wide coverage. A further strength of the data source is that all information is collected in a manner that is not intrusive, nor does it place further demands of additional data collection by, or interactions with, already burdened health services. This data source provides a novel, and unique way to map population alcohol-related harms over time, providing more robust evidence than studies reliant on small windows of data collection. Other jurisdictions should be encouraged to utilise ambulance data as part of a public health approach to monitor alcohol-related harms, although may face challenges when faced with (i) incomplete population coverage, (ii) lack of common electronic records or, (iii) financial barriers to access [20].
It should also be noted that the key policy announcements and events are not exhaustive, and the policy and community environments were dynamic during this time, with changes announced at daily intervals during the peak lockdown period (see Supplementary file 1). Therefore, causation between policy announcements/key events and alcohol-related attendances cannot be determined from this study alone, given that dates for different schemes and/or restrictions don't always align with the beginning of a month and implementation of those schemes may not have coincided exactly with their announcement.
5. Conclusion
This study examined changes in alcohol-related harms during months in 2020 associated with significant COVID-19 restrictions compared with matched months in 2019, and demonstrated displacement of alcohol harms to home settings compared with public venues, and changes in alcohol-related harms in specific sociodemographic groups. Changes were also evident at both the population and sub-population levels with respect to key government announcements that restricted citizen's movement. Importantly, this is one of the first studies to measure alcohol-related harms at the population level in response to a public health pandemic.
Figure 2.1.
Change in odds of alcohol-related ambulance attendances in metropolitan Melbourne and Mitchell Shire after each COVID intervention period.
Figure 2.2.
Change in odds of alcohol-related ambulance attendances in regional Victoria after each COVID intervention period.
Author Contributions
Conceptualisation: Ogeil, Scott, Manning, Lubman
Data curation: Wilson, Smith
Formal analysis: Faulkner, Beard
Funding acquisition: Ogeil, Scott, Lubman
Investigation: Ogeil, Scott, Faulkner
Methodology: Ogeil, Scott, Faulkner, Wilson, Beard, Smith, Manning, Lubman
Project administration: Ogeil, Scott
Resources: Lubman
Supervision: Manning, Lubman
Validation: Faulkner, Beard
Writing – original draft: Ogeil
Writing – review & editing: Scott, Faulkner, Wilson, Beard, Smith, Manning, Lubman
Authors Ogeil, Scott, Faulkner and Beard have access to all of the data and take responsibility for integrity of the data reported and the accuracy of the data analysis.
Funding Statement
The NASS project is funded by the Commonwealth Department of Health, and Department of Health and Human Services, Victoria. DIL is the recipient of an NHMRC (Australia) Investigator Grant.
Declaration of Competing Interest
DIL has received speaking honoraria from AstraZeneca, Camurus, Janssen, Servier and Lundbeck, and has provided consultancy advice to Lundbeck and Indivior. All other authors report no conflicts.
Acknowledgements
The authors thank Dr Paul Sanfilippo for his advice and comments on a previous draft of this manuscript.
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.lanwpc.2021.100222.
Appendix. Supplementary materials
References
- 1.Pfefferbaum B, North CS. Mental Health and the Covid-19 Pandemic. N Engl J Med. 2020;383(6):510–512. doi: 10.1056/NEJMp2008017. [DOI] [PubMed] [Google Scholar]
- 2.McGinty EE, Presskreischer R, Han H, Barry CL. Psychological Distress and Loneliness Reported by US Adults in 2018 and April 2020. JAMA. 2020;324(1):93. doi: 10.1001/jama.2020.9740. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Clay JM, Parker MO. Alcohol use and misuse during the COVID-19 pandemic: a potential public health crisis? Lancet Public Health. 2020;5(5):e259. doi: 10.1016/S2468-2667(20)30088-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Holland KM, Jones C, Vivolo-Kantor AM. Trends in US Emergency Department Visits for Mental Health, Overdose, and Violence Outcomes Before and During the COVID-19 Pandemic. JAMA Psychiat. 2021 doi: 10.1001/jamapsychiatry.2020.4402. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Vetter S, Rossegger A, Rossler W, Bisson JI, Endrass J. Exposure to the tsunami disaster, PTSD symptoms and increased substance use – an Internet based survey of male and female residents of Switzerland. BMC Public Health. 2008;8(1):92. doi: 10.1186/1471-2458-8-92. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Brooks SK, Webster RK, Smith LE. The psychological impact of quarantine and how to reduce it: rapid review of the evidence. Lancet. 2020;395(10227):912–920. doi: 10.1016/S0140-6736(20)30460-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Colbert S, Wilkinson C, Thornton L, Richmond R. COVID-19 and alcohol in Australia: Industry changes and public health impacts. Drug Alcohol Rev. 2020;39(5):435–440. doi: 10.1111/dar.13092. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Victorian Commission for Gambling and Liquor Regulation. Coronavirus (COVID-19) information for liscensees. 2020. https://www.vcglr.vic.gov.au/covid-192021.
- 9.Wardell JD, Kempe T, Rapinda KK. Drinking to Cope During COVID-19 Pandemic: The Role of External and Internal Factors in Coping Motive Pathways to Alcohol Use, Solitary Drinking, and Alcohol Problems. Alcohol Clinl Exp Res. 2020;44(10):2073–2083. doi: 10.1111/acer.14425. [DOI] [PubMed] [Google Scholar]
- 10.Avery AR, Tsang S, Seto EYW, Duncan GE. Stress, Anxiety, and Change in Alcohol Use During the COVID-19 Pandemic: Findings Among Adult Twin Pairs. Front Psychiatry. 2020;11 doi: 10.3389/fpsyt.2020.571084. 571084- [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Callinan S, Mojica-Perez Y, Wright CJC. Purchasing, consumption, demographic and socioeconomic variables associated with shifts in alcohol consumption during the COVID-19 pandemic. Drug Alcohol Rev. 2021;40(2):183–191. doi: 10.1111/dar.13200. [DOI] [PubMed] [Google Scholar]
- 12.Nordløkken A, Pape H, Heir T. Alcohol consumption in the aftermath of a natural disaster: a longitudinal study. Public Health. 2016;132:33–39. doi: 10.1016/j.puhe.2015.11.007. [DOI] [PubMed] [Google Scholar]
- 13.Griswold MG, Fullman N, Hawley C. Alcohol use and burden for 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet. 2018;392(10152):1015–1035. doi: 10.1016/S0140-6736(18)31310-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.World Health Organization. Global status report on alcohol and health 2018. 2018. https://www.who.int/publications/i/item/97892415656392020.
- 15.Han E, Tan MMJ, Turk E. Lessons learnt from easing COVID-19 restrictions: an analysis of countries and regions in Asia Pacific and Europe. Lancet. 2020;396(10261):1525–1534. doi: 10.1016/S0140-6736(20)32007-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Rodriguez LM, Litt DM, Stewart SH. Drinking to cope with the pandemic: The unique associations of COVID-19-related perceived threat and psychological distress to drinking behaviors in American men and women. Addict Behav. 2020;110 doi: 10.1016/j.addbeh.2020.106532. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Vandoros S, Avendano M, Kawachi I. The association between economic uncertainty and suicide in the short-run. Soc Sci Med. 2019;220:403–410. doi: 10.1016/j.socscimed.2018.11.035. [DOI] [PubMed] [Google Scholar]
- 18.Lubman DI, Heilbronn C, Ogeil RP. National Ambulance Surveillance System: A novel method using coded Australian ambulance clinical records to monitor self-harm and mental health-related morbidity. PLoS One. 2020;15(7) doi: 10.1371/journal.pone.0236344. e0236344-e. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Dicker B, Swain A, Todd VF. Changes in demand for emergency ambulances during a nationwide lockdown that resulted in elimination of COVID-19: an observational study from New Zealand. BMJ Open. 2020;10 doi: 10.1136/bmjopen-2020-044726. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Lubman DI, Matthews S, Heilbronn C. The National Ambulance Surveillance System: A novel method for monitoring acute alcohol, illicit and pharmaceutical drug related-harms using coded Australian ambulance clinical records. PLoS One. 2020;15(1) doi: 10.1371/journal.pone.0228316. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Australian Bureau of Statistics. Quarterly Population Estimates (ERP), by State/Territory, Sex and Age. 2020. https://stat.data.abs.gov.au/Index.aspx?DataSetCode=ERP_QUARTERLY (accessed 9 June 2021 2021).
- 22.Ramalho R. Alcohol consumption and alcohol-related problems during the COVID-19 pandemic: a narrative review. Australas Psychiatry. 2020;28(5):524–526. doi: 10.1177/1039856220943024. [DOI] [PubMed] [Google Scholar]
- 23.Sallie SN, Ritou V, Bowden-Jones H, Voon V. Assessing international alcohol consumption patterns during isolation from the COVID-19 pandemic using an online survey: highlighting negative emotionality mechanisms. BMJ Open. 2020;10(11) doi: 10.1136/bmjopen-2020-044276. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Foundation for Alcohol Research & Education . A snapshot of how the alcohol industry is using a global pandemic as a marketing opportunity. Foundation for Alcohol Research & Education; Australia: 2020. Cancer Council Western Australia. An alcohol ad every 35 seconds. [Google Scholar]
- 25.Ogeil RP, Gao CX, Rehm J, Gmel G, Lloyd B. Temporal changes in alcohol-related mortality and morbidity in Australia. Addiction. 2016;111(4):626–634. doi: 10.1111/add.13213. [DOI] [PubMed] [Google Scholar]
- 26.Volkow ND. Collision of the COVID-19 and Addiction Epidemics. Ann Intern Med. 2020;173(1):61–62. doi: 10.7326/M20-1212. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Chen CM, Yoon Y-H. Usual Alcohol Consumption and Risks for Nonfatal Fall Injuries in the United States: Results From the 2004-2013 National Health Interview Survey. Subst Use Misuse. 2017;52(9):1120–1132. doi: 10.1080/10826084.2017.1293101. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.