Socioeconomic position, alcohol use and alcohol-attributable emergency department visits

Abstract

Background

Differential vulnerability to alcohol contributes to socioeconomic inequities in alcohol-attributable harm. This study aimed to estimate the sex-/gender-specific joint effects of socioeconomic position (SEP) and heavy episodic drinking or volume of alcohol use on 100% alcohol-attributable emergency department (ED) visits.

Methods

We conducted a cohort study among 36 900 men and 39 700 women current and former alcohol consumers aged 15–64 from population-representative Canadian Community Health Surveys (2003–2008) linked to administrative ED visit data through 2017 in Ontario and Alberta. We estimated sex-/gender-specific associations between SEP (both education and income) and heavy episodic drinking (≥5 standard drinks on one occasion, at least monthly) or volume of alcohol use (standard drinks per week) on incident alcohol-attributable ED visits and assessed additive interactions using the Synergy Index (S).

Results

Lower levels of education (eg, less than high school vs Bachelor’s degree or above: men: adjusted HR (aHR)=3.71, 95% CI 2.47 to 5.58; women: aHR=1.75, 95% CI 1.15 to 2.68) and income (eg, quintile (Q)1 vs Q5, men: aHR=2.07, 95% CI 1.35 to 3.17; women: aHR=1.84, 95% CI 0.91 to 3.71) were associated with increased rates of alcohol-attributable ED visits. Among men and women, superadditive joint effects (ie, greater than the sum of both exposures experienced independently) were observed between low SEP (education and income) and heavy episodic drinking and higher volume of alcohol use on alcohol-attributable ED visits.

Interpretation

Our results indicate that individuals with lower SEP experience increased vulnerability to alcohol use and related harms. These findings highlight the urgent need for population-level interventions that reduce both the high burden and socioeconomic inequities in alcohol-attributable harm.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• The association between low socioeconomic position (SEP) and alcohol-attributable harms cannot fully be explained by heavy episodic drinking or volume of alcohol use.

WHAT THIS STUDY ADDS

• Our study found that low SEP, measured using education and income, was associated with alcohol-attributable emergency department visits, an outcome that includes acute alcohol-attributable harm.

• We add to an emerging literature that individuals with low SEP experience increased vulnerability to alcohol harm compared with their high SEP counterparts.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• Our findings underscore the need for population-level interventions that reduce inequities in the social determinants of alcohol harm, including education and income, which drive the differential vulnerability to alcohol use experienced by individuals with lower SEP.

• Furthermore, population-level alcohol interventions that disproportionately reduce alcohol use and harm in individuals with low SEP, such as pricing policies, are required to mitigate alcohol harm inequities.

Introduction

Alcohol, a leading cause of death and disability in Canada and internationally, is causally associated with over 200 chronic and acute health harms.¹ The societal impact of alcohol use is substantial, with alcohol-attributable healthcare costs in Canada reaching CAD$6.3 billion in 2020.² Systematic reviews and meta-analyses have estimated the risk of alcohol-attributable mortality to be 3.8–5.2 times higher in individuals with low socioeconomic position (SEP) compared with those with high SEP in high-income countries.³

Robust evidence indicates that differential exposure to alcohol alone cannot explain observed socioeconomic inequities in alcohol-attributable harm.^{4 5} Internationally, individuals with lower SEP have been shown to use alcohol at similar or lower levels, yet experience greater alcohol-attributable harm than individuals with high SEP, known as the alcohol harm paradox.^{4 5} Evidence from the most recent systematic review and meta-analysis found that heavy episodic drinking and volume of alcohol use only explained between 15%–30% and 5%–15% of the observed inequities in all-cause mortality.³

Emerging international evidence, including from Canada, suggests low SEP and alcohol use may interact to increase vulnerability to alcohol-attributable hospitalisation and death.6,8 A joint effect would indicate that risks associated with low SEP and high alcohol use together are greater relative to the sum of their independent effects. A joint effect would support the differential vulnerability hypothesis,⁹ where a higher prevalence of negative health exposures accumulates across the life course to disproportionately increase the risk of alcohol-attributable harm for individuals with low compared with high SEP. These vulnerabilities may be amplified by reduced access to opportunities for resilience, prevention and intervention (eg, social support or access to healthcare) that may buffer the negative impacts of alcohol use among individuals with low SEP.⁵

To date, no studies internationally have examined the joint effect of SEP and alcohol use on alcohol-attributable emergency department (ED) visits.⁵ These visits, which include both acute (eg, intoxication) and chronic (eg, alcoholic liver disease) conditions, place a significant burden on the healthcare system.¹⁰ While socioeconomic inequities in acute and chronic alcohol-attributable ED visits exist,¹¹ it remains unclear whether the increased vulnerability to other alcohol-attributable harm also applies to alcohol-attributable ED visits. This study estimated the joint effects between SEP (measured using education and income) and heavy episodic drinking or volumes of alcohol use on 100% alcohol-attributable ED visits between 2003 and 2017 in Canada, examined separately by sex/gender.

Methods

Data and sample

We conducted a retrospective cohort study among respondents living in two Canadian provinces, Ontario and Alberta, pooling three 2-year cross-sectional Canadian Community Health Survey (CCHS) cycles (2003, 2005 and 2007–2008) linked to administrative ED visits.¹² Conducted by Statistics Canada, the CCHS is a cross-sectional survey representative of >96% of the Canadian population,¹² capturing sociodemographic, health status and healthcare utilisation information on individuals aged 12+ living in private dwellings. The CCHS does not include Indigenous peoples living on reserve, Canadian Armed Forces members, people living in institutions or in certain remote areas.¹² Response rates for the 2003–2008 CCHS varied between 76% and 81%. The CCHS (CCHS linked: 2000–2017) was linked to the National Ambulatory Care Reporting System (NACRS: 2002-2017), the Discharge Abstract Database (DAD: 1999–2017), the Ontario Mental Health Reporting System (OMHRS: 2006–2017), the Canadian Vital Statistics-Death Database (CVSD: 2000–2017) and the T1 Family File (T1FF, 2003–2008) by Statistics Canada. Outcome data derived from NACRS includes event-based hospital and community care ED visits across Canada. However, only Ontario (12.2 million residents in 2003) and Alberta (3.2 million residents in 2003) report data from all facilities. ED visits were followed up until 31 December 2017, the most recent linkage available. DAD and OMHRS, which include all Canadian hospital discharges, were used to identify 100% alcohol-attributable hospitalisation prior to the CCHS survey. The CVSD includes all deaths in Canada, which are used to account for all-cause mortality as a competing risk. The T1FF included the annual income estimates derived from tax returns and was the source of income data.

Overall, 85% of CCHS participants agreed to provide their data for linkage.¹² Of these, 96% were successfully linked probabilistically to Statistics Canada’s Social Data Linkage Environment using given and family names, birth date, sex and postal code. Using unique identifiers in health administrative datasets, 95.3% of ED visits were deterministically linked (to this environment).¹² Full details on microdata linkage can be found elsewhere.¹² Our study received ethical clearance from Public Health Ontario’s Research Ethics Board (file number: 2021–034.01).

Cohort creation and study population

We pooled 326 600 respondents from the 2003, 2005 and 2007–2008 CCHS surveys who were linked to ED visits through 2017 (figure 1). We excluded respondents living outside of Ontario and Alberta (n=192 700), in regions that did not include the optional alcohol use module (in 2007/2008, n=9600), who prior to their CCHS interview had a healthcare encounter for a 100% alcohol-attributable condition (n=700) and were aged less than 15 or 65+ (n=28 000). We excluded individuals aged 65+ as their reported alcohol use is often lower and therefore does not align with their lifetime alcohol use patterns.¹³ Additionally, social assistance programmes available to older adults may mitigate socioeconomic inequities in this population. Furthermore, we excluded women who were pregnant or breastfeeding (n=2200), whose alcohol use may not represent normal levels; those with missing covariate data (n=8000) or lifetime alcohol abstainers who could not experience an alcohol-attributable ED visit (n=8900).

Figure 1. Study flow chart. *Note: due to random rounding of the counts to base 100, as per Statistics Canada Protocols, they may not add up to the overall sample in our study. CCHS, Canadian Community Health Survey.

Outcome

We examined incidents of 100% alcohol-attributable ED visits identified using the International Classification of Diseases 10th revision and Diagnostic and Statistical Manual of Mental Disorders-fifth revision diagnostic codes listed as the underlying or contributing cause based on the Canadian Institute for Health Information’s indicator ‘Conditions Entirely Caused by Alcohol’¹⁴(online supplemental eAppendix 1). This definition has been used to examine alcohol-attributable ED visits in Ontario.^{10 15 16} Follow-up time was measured in person-years from the CCHS survey date to incident alcohol-attributable ED visit, death or end of follow-up.

Exposures

We operationalised SEP using two measures. Self-reported educational attainment was categorised as less than high school, high school diploma/some postsecondary, trades or certificates below Bachelor’s degree and Bachelor’s degree or above. For individuals aged 30+, the respondent’s education was used. For those under age 30, the highest household educational attainment was used, as respondents may not yet have had the opportunity to achieve the highest education group.⁶ This approach is consistent with previous Canadian work on educational inequities in alcohol-attributable harm.⁶ We also examined equivalised after-tax household income quintiles (Q1: lowest and Q5: highest), calculated by dividing after-tax income from T1FF by the square root of the number of individuals living in the household.

Two self-reported alcohol use measures were explored. We dichotomised heavy episodic drinking (yes/no), based on whether respondents reported binge drinking, consuming ≥5 standard drinks (13.45 g of ethanol) on a single occasion, at least monthly in the past year.¹⁷ Volume of alcohol use was measured using four risk zones based on the number of standard drinks consumed in the past 7 days based on the continuum of risk described in Canada’s Guidance on Alcohol and Health¹⁸: former consumer (no alcohol use in the past year), low (≤2 drinks/week), medium (3–6 drinks/week), high (7–15 drinks/week) and excess (>15 drinks/week) risk. We selected low risk as the reference due to the heterogeneity of alcohol risk among former consumers, some of whom may have stopped using alcohol due to poor health.

Covariates

We used self-reported measures of biological sex (male/female). We interpret our findings with the recognition that both sex (eg, females experience greater alcohol harm at similar volumes of alcohol use) and gender (eg, socially constructed roles, attitudes and expectations) play a role in generating alcohol harm,¹⁹ factors that are further complicated across SEP. Therefore, we use the terms sex/gender, women and men.

Age (in years), marital status (married/common-law, windowed/separated/divorced, single/never married), immigrant status (immigrant and non-immigrant), province (Ontario and Alberta), rurality (urban/rural defined as population concentration ≥1000 and a population density ≥400 km²) and survey cycle (categorical) were included as confounders.

Statistical analysis

We assessed alcohol-attributable ED visit rates by baseline sociodemographic characteristics by sex/gender. We used Fine and Gray subdistribution hazard models with competing risk (all-cause mortality) to estimate the sex-/gender-specific associations between SEP and incident alcohol-attributable ED visits, including models adjusted for CCHS cycle and all confounders (CCHS cycle, age and age-squared, marital status, immigrant status, province and rurality). We ensured the model’s assumptions were satisfied using a modified version of the log-rank test to test the proportional hazards assumption and Martingale residuals to assess linearity between the log hazard and linear covariates such as age. We investigated a potential joint effect by including an interaction term between SEP and alcohol use. In our joint effect models, we further dichotomised education (low: less than high school or high school diploma/some postsecondary; high: trades/certificate below Bachelor’s, Bachelor’s or above) and income (low: Q1–Q3; high: Q4–Q5) to improve the precision of our estimates. We estimated 95% CIs using bootstrapping (500 repetitions) and applied Statistics Canada linkage survey weights to all models, scaled by a third to account for combining three CCHS cycles, to produce population-representative estimates adjusted for non-response and respondents that were unable or did not consent to link their responses.¹²

We tested the joint effects of SEP and alcohol use on the additive scale using the Synergy Index (S). Identifying additive interactions is crucial for public health, as they highlight subpopulations that could gain the most from targeted interventions.²⁰ S represents the ratio of the joint relative effect of two exposures exceeding 1 to the sum of their independent relative effects exceeding 1. S greater than 1 (superadditive) or less than 1 (subadditive) indicates an interaction between exposures. We use S to estimate additive interactions because it remains consistent across different strata defined by covariates, making it ideal for use in multivariate regression models.²¹ We estimated 95% CIs for S using the Hosmer-Lemeshow delta method²² using the postestimated bootstrapped variances. Statistical analyses were conducted using SAS Enterprise Guide V.8.1.

Results

Our study population included 76 000 respondents (52% women, mean age 41 years) with a mean follow-up of 12.3 years. We identified 1710 alcohol-attributable ED visits, of which 78% were attributable to acute alcohol conditions (online supplemental eAppendix 2). Descriptively, alcohol-attributable ED visit rates appeared to be higher among men than women, and in individuals with lower education and income, heavy episodic drinking, higher volume of alcohol use, were widowed, separated or divorced and lived in urban areas (table 1). Alcohol-attributable ED visit rates appeared to be similar across immigrant status and province.

Table 1. Sex/gender-specific rates of alcohol-attributable emergency department visits by sociodemographic characteristics, Ontario and Alberta, Canada (men=36 900, women=39 700).

	Men				Women
	%	Events	PY	Rate per 10 000 PY	%	Events	PY	Rate per 10 000 PY
Overall	100	1080	448 545	24.1	100	630	487 910	12.9
Educational attainment
Less than high school	11	220	48 215	45.6	10	100	47 495	21.1
High school diploma	24	300	107 075	28.0	25	165	124 340	13.3
Trades/certificate below Bachelor’s	42	415	187 825	22.1	42	265	204 320	13.0
Bachelor’s degree or above	23	115	105 430	14.7	23	105	111 760	9.4
Income
Quintile 1: low	12	250	54570	45.8	16	190	74590	25.5
Quintile 2	12	140	53970	25.9	13	100	64500	15.5
Quintile 3	16	140	75530	18.5	17	80	79270	10.1
Quintile 4	21	180	97580	18.4	23	90	94720	9.5
Quintile 5: high	30	170	121020	14.0	27	90	109670	8.2
Missing	9	190	45870	14.4	6	80	65 160	12.3
Heavy episodic drinking (y/n)
Non-heavy drinker	67	495	303 835	16.3	87	435	424 550	10.2
Heavy drinker	33	585	144 710	40.4	13	195	63 360	30.8
Volume of alcohol use
Former drinker	7	85	33 470	25.4	10	40	50 490	7.9
Low volume	42	310	189 405	16.4	58	275	285 155	9.6
Medium volume	19	155	84 210	18.4	18	125	86 240	14.5
High volume	20	250	91 420	27.3	12	125	54 760	22.8
Excess drinker	11	275	50 040	55.0	2	70	11 270	62.1
Age (mean, SD)	41	(0.01)			41	(0.01)
Canadian Community Health Survey cycle
2003	38	435	193 295	22.5	37	270	210 150	12.8
2005	37	390	163 520	23.9	37	230	177 320	13.0
2007–2008	26	260	91 725	28.3	26	135	100 440	13.4
Marital status
Married/common law	58	395	260 510	15.2	57	260	280 810	9.3
Widowed/separated/divorced	11	230	46 405	49.6	16	140	76 635	18.3
Single	32	450	141 630	31.8	27	225	130 465	17.2
Immigrant status
Immigrant	16	140	71 270	19.6	15	55	72 000	7.6
Non-immigrant	84	940	377 275	24.9	85	580	415 915	13.9
Urban/rural
Urban	79	865	355 915	24.3	79	525	387 330	13.6
Rural	21	220	92 630	23.1	21	105	100 580	10.4
Province
Ontario	82	880	362 085	24.1	83	510	396 235	12.9
Alberta	18	200	86 465	23.1	17	125	91 685	13.6

^*Note: due to random rounding the counts of men and women to base 5, as per Statistics Canada Protocols, they may not add up to the overall sample in our study.

PY, person-years.

Low SEP was associated with alcohol-attributable ED visits (table 2). For example, among men and women with ‘less than high school’ education had 3.71 (95% CI 2.47 to 5.58) and 1.75 (95% CI 1.15 to 2.68) times higher risk of alcohol-attributable ED visit compared with the ‘Bachelor’s degree or above’ groups in confounder-adjusted models. While results were consistent across income levels for men, results were similar among men across income (Q1 vs Q5: adjusted HR (aHR) 2.07, 95% CI 1.35 to 3.17); among women, the inverse gradient observed between income and alcohol-attributable ED visits requires further confirmation due to lack of precision (ie, uncertainty) (eg, Q1 vs Q5: aHR 1.84, 95% CI 0.91 to 3.71).

Table 2. The associations between socioeconomic position and alcohol-attributable emergency department visits.

	Men		Women
	Cycle-adjusted	Confounder-adjusted*	Cycle-adjusted	Confounder-adjusted*
	HR (95% CI)	HR (95% CI)	HR (95% CI)	HR (95% CI)
Educational attainment
Less than high school	3.52 (2.45 to 5.06)	3.71 (2.47 to 5.58)	1.49 (0.99 to 2.24)	1.75 (1.15 to 2.68)
High school graduation	1.82 (1.31 to 2.53)	1.78 (1.28 to 2.46)	1.12 (0.75 to 1.66)	1.18 (0.80 to 1.76)
Trades/certificate below Bachelor’s	1.54 (1.11 to 2.12)	1.51 (1.09 to 2.08)	1.53 (1.05 to 2.24)	1.55 (1.06 to 2.27)
Bachelor’s degree or above	Ref	Ref	Ref	Ref
Income
Quintile 1: low	2.44 (1.60 to 3.72)	2.07 (1.35 to 3.17)	1.93 (1.02 to 3.67)	1.84 (0.91 to 3.71)
Quintile 2	1.67 (1.07 to 2.60)	1.66 (1.06 to 2.59)	1.39 (0.78 to 2.45)	1.43 (0.81 to 2.52)
Quintile 3	1.43 (0.81 to 2.55)	1.49 (0.84 to 2.63)	1.25 (0.66 to 2.37)	1.33 (0.70 to 2.54)
Quintile 4	1.20 (0.80 to 1.79)	1.20 (0.80 to 1.81)	1.16 (0.59 to 2.25)	1.15 (0.60 to 2.25)
Quintile 5: high	Ref	Ref	Ref	Ref

^*Model adjusted for cycle, age (continuous), age2, marital status, immigrant, province and rurality.

S values were greater than 1 in confounder-adjusted models, indicating a superadditive joint effect between individuals with low education (men: S=1.21, 95% CI 1.00 to 1.42; women: S=1.22, 95% CI 0.97 to 1.48) and low income (men: S=1.28, 95% CI 0.65 to 2.53; women: S=2.53, 95% CI 1.03 to 6.21) and heavy episodic drinking on alcohol-attributable ED visits (table 3). The joint effect estimates for income were higher in women compared with men but were similar for education, with low precision surrounding estimates for education in women and income for men.

Table 3. Joint effects of SEP and heavy episodic drinking on alcohol-attributable emergency department visits.

	High education	Low education	Synergy index (95% CI)	High income	Low income	Synergy index (95% CI)
	HR (95% CI)	HR (95% CI)		HR (95% CI)	HR (95% CI)
Men
Heavy episodic drinking
No heavy drinking	Ref	1.95 (1.42 to 2.67)		Ref	1.30 (0.85 to 2.02)
Heavy episodic drinking	2.75 (2.04 to 3.71)	4.27 (3.21 to 5.68)	1.21 (1.00 to 1.42)	1.05 (0.59 to 1.89)	2.27 (1.52, to 3.38)	1.28 (0.65 to 2.53)
Women
Heavy episodic drinking
No heavy drinking	Ref	0.84 (0.61 to 1.17)		Ref	1.34 (0.85 to 2.12)
Heavy episodic drinking	3.33 (2.20 to 5.03)	3.65 (2.44 to 5.47)	1.22 (0.97 to 1.48)	0.71 (0.34 to 1.47)	3.78 (2.00 to 7.19)	2.53 (1.03 to 6.21)

Models adjusted for cycle, age, age2, marital status, immigrant, province and rurality.

Low education was defined as having less than high school or high school graduation/some postsecondary and high education was defined as having trades or certificate below Bachelor’s degree or Bachelor’s degree or above.

Low income included individuals with income in quintiles 1–3 and high income was included individuals with incomes 4 and 5.

Heavy episodic drinking was defined as consuming at least five standard drinks on a single occasion least once a month in the past year (one standard drink=13.45 g or 17.05 mL of pure alcohol).

Synergy index=(HR₁₁–1)/((HR₁₀–1)+(HR₀₁−1)), where HR₁₁ refers to the HR where both low socioeconomic position (SEP: education or income) and heavy episodic drinking are present, HR₁₀ refers the HR where low SEP is present, but where heavy episodic drinking is absent, and HR₀₁ refers to the HR where high SEP and heavy episodic drinking are present.

Among men, we found a joint effect of low education and volume of alcohol use on alcohol-attributable ED visits (table 4). Results were less consistent for women, with a small superadditive effect noted among individuals using alcohol at excess risk volumes only. Among men and women, we observed superadditive joint effects of low income and volume of alcohol use, in particular in the high risk among women (S=2.85, 95% CI 1.59 to 5.12) and excess risk (men: S=2.36, 95% CI 0.76 to 7.36; women: S=5.82, 95% CI 3.25 to 10.42) volume groups, where the estimates were higher in women than in men. Confirmation is required where estimates CIs cross 1.

Table 4. Joint effect of SEP and volume of alcohol use on alcohol-attributable emergency department visits.

	High education	Low education	Synergy index (95% CI)	High income	Low income	Synergy index (95% CI)
	HR (95% CI)	HR (95% CI)		HR (95% CI)	HR (95% CI)
Men
Volume of alcohol use
Low risk	Ref	1.64 (1.11 to 2.44)		Ref	1.35 (0.77 to 2.35)
Former consumer	1.79 (1.06 to 3.02)	3.00 (1.48 to 6.08)	1.40 (0.61 to 2.19)	0.94 (0.30 to 2.95)	1.33 (0.56 to 3.18)	0.32 (0.17 to 0.60)
Medium risk	1.06 (0.71 to 1.59)	2.31 (1.41 to 3.78)	1.87 (0.21 to 3.54)	1.89 (0.85 to 4.21)	0.82 (0.47 to 1.45)	0.26 (0.14 to 0.50)
High risk	2.15 (1.48 to 3.14)	3.23 (1.97 to 5.29)	1.25 (0.78 to 1.72)	0.94 (0.42 to 2.08)	2.28 (1.38 to 3.78)	1.25 (0.32to 4.83)
Excess risk	3.17 (2.14 to 4.68)	5.69 (3.92 to 8.26)	1.70 (1.31 to 2.03)	0.87 (0.38 to 1.95)	3.47 (1.98 to 6.06)	2.36 (0.76 to 7.36)
Women
Volume of alcohol use
Low risk	Ref	1.20 (0.80 to 1.78)		Ref	1.05 (0.63 to 1.73)
Former consumer	1.98 (0.70 to 5.63)	1.17 (0.58 to 2.39)	0.14 (−0.47 to 0.76)	2.69 (0.22 to 3.55)	0.68 (0.12 to 3.73)	−0.35 (−0.66 to 0.19)
Medium risk	2.00 (1.30 to 3.07)	1.84 (1.06 to 3.18)	0.70 (0.13 to 1.27)	1.97 (0.88 to 4.40)	1.32 (0.67 to 2.61)	0.34 (0.20 to 0.56)
High risk	3.90 (2.48 to 6.13)	3.41 (2.13 to 5.47)	0.78 (0.56 to 0.99)	1.22 (0.49 to 3.02)	3.82 (1.86 to 7.85)	2.85 (1.59 to 5.12)
Excess risk	7.61 (4.16 to 13.92)	8.67 (4.30 to 17.48)	1.13 (0.97 to 1.28)	0.54 (0.15 to 1.91)	6.95 (2.44 to 19.82)	5.82 (3.25 to 10.42)

Models adjusted for cycle, age, age2, marital status, immigrant, province and rurality.

Low education was defined as having less than high school or high school graduation/some postsecondary and high education was defined as having trades or certificate below Bachelor’s degree or Bachelor’s degree or above.

Low income included individuals with income in quintiles 1–3 and high income was included individuals with incomes 4 and 5.

Volume of alcohol use was defined as low risk volume (≤2 standard drinks per week), former consumer (no alcohol use in the past 12 months), medium risk volume (3–6 standard drinks per week), high risk volume (7–15 standard drinks per week) and excess risk volume (more than 15 standard drinks per week).

Synergy index=(HR₁₁–1)/((HR₁₀ –1)+(HR₀₁–1)), where HR₁₁ refers to the HR where both low socioeconomic position (SEP: education or income) and the specified volume of alcohol use category are present, HR₁₀ refers the HR where low SEP and low volume of alcohol use are present, and HR₀₁ refers to the HR where high SEP and the specified volume of alcohol use category are present.

SEP, socioeconomic position.

Interpretation

In a large population-representative cohort study from Ontario and Alberta, Canada, we found socioeconomic inequities in alcohol-attributable ED visits, consistent with previous Canadian studies using individual¹¹ and area-level SEP measures.^{10 15} Furthermore, we identified joint effects of low SEP and both heavy episodic drinking and volume of alcohol use on alcohol-attributable ED visits, indicating greater vulnerability at different levels of alcohol use among individuals with low SEP. Our findings underscore the need for population-level interventions that account for both SEP and alcohol use to reduce the high burden and social inequities in alcohol-attributable harm.

Our study adds to the international literature on the joint effects of SEP and alcohol use on alcohol-attributable harm by demonstrating this effect for the first time in alcohol-attributable ED visits. Previous longitudinal studies from Canada,⁶ Denmark,⁷ Finland⁸ and Scotland²³ have found a joint effect of SEP and alcohol use on 100% alcohol-attributable hospitalisations or deaths. Our results extend these findings by demonstrating increased vulnerability from acute alcohol use, which accounted for 78% of alcohol-attributable ED visits. This insight suggests that the mechanisms increasing vulnerability to alcohol among individuals with low SEP affect both acute and chronic outcomes, such as ED visits and hospitalisations/mortality. This highlights the broader influence of cumulative socioeconomic disadvantage and the role of structural determinants of health in shaping alcohol-attributable risks.

We also identified sex/gender differences in the strength of the joint effect of SEP and alcohol use on alcohol-attributable ED visits across SEP indicators. The joint effect was stronger in women with low income for both alcohol use indicators. This may be explained by individuals with fewer resources and lower SEP being less able to shield themselves from the negative consequences of acute alcohol use.²⁴ Furthermore, these effects may interact with sex/gender-related risk, where women experience increased stigma from alcohol use and intoxication²⁴ and have greater biological susceptibility to alcohol’s detrimental effects.¹⁹ Among men, education was a stronger indicator of vulnerability, which may be linked to men with lower education often working in occupations with stronger drinking cultures and higher alcohol use and harm (eg, trades, transport, equipment operations, primary industry and manufacturing).²⁵ Future research is needed to confirm our findings and to explore potential sex/gender differences leading to differential vulnerability to (acute) alcohol-attributable ED visits.

Several potential mechanisms, beyond alcohol use patterns, have been proposed to contribute to the differential vulnerability to alcohol-attributable harm across SEP. For example, greater exposure and vulnerability to lifestyle risk factors (eg, smoking, overweight/obesity, low physical activity and poor diet) partially explain the disproportionate alcohol-attributable harm.^{8 23} Despite Canada’s universal healthcare system, individuals with lower SEP or living in rural communities (where lower SEP is more common)²⁶ have reduced healthcare access²⁷ and may lack extended health benefits that cover substance use-related programmes and prescriptions.²⁸

Our findings highlight the need for population-level interventions that target the social determinants of health, including low income and education, to mitigate alcohol harm inequities.⁵ These policies address the root causes of differential vulnerability to alcohol use experienced by individuals with lower SEP. Furthermore, real-world experimental and modelling studies evaluating population-level alcohol interventions have shown promise for disproportionately reducing alcohol use and harm in individuals with low SEP.29,31 For example, the introduction of minimum alcohol unit pricing in Scotland in 2018 reduced the quantity of alcohol sold overall, with greater reductions in alcohol purchases in households with lower incomes³⁰ and alcohol-attributable hospitalisations/deaths in neighbourhoods with the highest deprivation.³¹ Additional research is needed to understand the unintended, yet potentially disproportionate, health equity impacts of population-level alcohol interventions in contexts where they are eroding. For example, in Ontario, where the ongoing expansion of alcohol sales into convenience and grocery stores is increasing alcohol availability in up to 8500 new outlets,³² there may be disproportionate impacts on low SEP groups.^{33 34}

Limitations

Our study has several limitations. Our results may be conservative, due to the presence of non-response bias (higher among individuals with heavy episodic drinking)³⁵ and selection bias (due to the exclusion of hard-to-reach populations with higher alcohol use)³⁶ inherent in population-representative surveys. The exclusion of individuals with prior alcohol-attributable healthcare encounters, including individuals with alcohol use disorder at baseline, resulted in a healthier study population than the population of alcohol users. As such, the true socioeconomic inequities in alcohol harm are underestimated. However, this exclusion is required to examine incident alcohol-attributable ED visits, minimising reverse causality of alcohol use on SEP. Additionally, self-reported alcohol use is likely underestimated, estimated to account for 30%–60% of per capita alcohol sales.³⁷ However, evidence suggests alcohol use is not differentially reported by sociodemographic factors³⁸ and is an unlikely explanation of the alcohol harm paradox.³⁹ Furthermore, SEP and alcohol use were measured at baseline only, not accounting for lifetime alcohol use and its time-varying relationship with SEP. Given the long follow-up between baseline and alcohol-attributable ED visits in our study, measured alcohol use cannot directly account for these ED visits. We also likely underestimated the true extent of socioeconomic inequities in alcohol-attributable harm, as partially alcohol-attributable harm and non-health harm due to alcohol were accounted for. Finally, our findings may not be generalisable to jurisdictions without universal healthcare.

Our study has several strengths. We take advantage of a large cohort study that includes measures of individual-level SEP, alcohol use and up to 15 years of follow-up for alcohol-attributable ED visits. Our study is among the first to examine the joint effect of education and alcohol use on alcohol-attributable ED visits, a finding that was robust across SEP indicators. This is important as SEP indicators represent distinct yet interrelated pathways that impact alcohol-attributable harm, for example, through knowledge-related assets (ie, education) or material resources (ie, income).

Conclusion

We observed a joint effect of SEP and alcohol use on alcohol-attributable ED visits. Our findings indicate differential vulnerability across SEP, with alcohol use posing disproportionately greater health risks for individuals with low compared with high SEP. As such, population-level interventions that account for both SEP and alcohol use are urgently needed to reduce social inequities in alcohol-attributable harm.

Data availability statement

Data may be obtained from a third party and are not publicly available.