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. 2024 Mar 16;59(3):agae015. doi: 10.1093/alcalc/agae015

Associations between alcohol taxes and varied health outcomes among women of reproductive age and infants

Meenakshi S Subbaraman 1,✉, Alex Schulte 2, Nancy F Berglas 3, William C Kerr 4, Sue Thomas 5, Ryan Treffers 6, Guodong Liu 7, Sarah C M Roberts 8
Editor: Giancarlo Colombo
PMCID: PMC10945295  PMID: 38497162

Abstract

Objective

No studies have examined whether alcohol taxes may be relevant for reducing harms related to pregnant people’s drinking.

Method

We examined how beverage-specific ad valorem, volume-based, and sales taxes are associated with outcomes across three data sets. Drinking outcomes came from women of reproductive age in the 1990–2020 US National Alcohol Surveys (N = 11 659 women Inline graphic 44 years); treatment admissions data came from the 1992–2019 Treatment Episode Data Set: Admissions (N = 1331 state-years; 582 436 pregnant women admitted to treatment); and infant and maternal outcomes came from the 2005–19 Merative Marketscan® database (1 432 979 birthing person–infant dyads). Adjusted analyses for all data sets included year fixed effects, state-year unemployment and poverty, and accounted for clustering by state.

Results

Models yield no robust significant associations between taxes and drinking. Increased spirits ad valorem taxes were robustly associated with lower rates of treatment admissions [adjusted IRR = 0.95, 95% CI: 0.91, 0.99]. Increased wine and spirits volume-based taxes were both robustly associated with lower odds of infant morbidities [wine aOR = 0.98, 95% CI: 0.96, 0.99; spirits aOR = 0.99, 95% CI: 0.98, 1.00] and lower odds of severe maternal morbidities [wine aOR = 0.91, 95% CI: 0.86, 0.97; spirits aOR = 0.95, 95% CI: 0.92, 0.97]. Having an off-premise spirits sales tax was also robustly related to lower odds of severe maternal morbidities [aOR = 0.78, 95% CI: 0.64, 0.96].

Conclusions

Results show protective associations between increased wine and spirits volume-based and sales taxes with infant and maternal morbidities. Policies that index tax rates to inflation might yield more public health benefits, including for pregnant people and infants.

Keywords: alcohol taxes, women, pregnancy, treatment admissions, infant outcomes, maternal outcomes

Short Summary: Results show protective associations between increased wine and spirits volume-based and sales taxes with infant and maternal morbidities. Policies that index tax rates to inflation might yield more public health benefits, including for pregnant people and infants.

Introduction

Historically, alcohol taxation has been one of the best strategies to reduce drinking and related harms in the general population (Giesbrecht and Greenfield 2003; Wagenaar et al. 2009; Babor et al. 2023). However, impacts of alcohol taxes often vary across subgroups because of income, beverage preference, and/or preferred place of drinking (Mulia and Jones-Webb 2017). For example, a study examining US state-level alcohol policy impacts across gender and race/ethnicity found higher beer taxes were particularly protective for Black and White women and higher spirits taxes were particularly protective for Hispanics (Subbaraman et al. 2020). Other epidemiologic (Meier et al. 2010), econometric (Ayyagari et al. 2009), and review (Nelson 2014) studies have concluded that women are more sensitive to alcohol prices than men.

General population alcohol policies such as taxes affect everyone who buys alcohol, whereas pregnancy-specific alcohol policies single out pregnant people’s alcohol use. Pregnancy-specific policies vary across US states and include laws like mandatory posting of warning signs about harms of alcohol use during pregnancy and those permitting civil commitment for those using alcohol during pregnancy (Roberts et al. 2017). A growing literature shows that these pregnancy-focused policies are, on the whole, ineffective (Roberts et al. 2019, 2023; Berglas et al. 2023), and in some cases, associated with worse outcomes. For example, policies mandating warning signs relate to increased odds of adverse birth outcomes, infant maltreatment, and severe maternal morbidities (SMM) and decreased prenatal care utilization (Subbaraman and Roberts 2019; Berglas et al. 2023; Roberts et al. 2023).

This pattern of findings is consistent with a 25-year-old critique of policies singling out pregnant people’s alcohol use, which emphasizes that targeting specific individuals (e.g. based on pregnancy) or simply educating individuals about harms of alcohol use during pregnancy (e.g. with mandatory warning signs) “naively assumes that drinking exists in a social and psychological vacuum” (Abel 1998). This critical review of strategies to reduce alcohol-related birth effects concluded that, because heavy drinking is sensitive to alcohol price changes, the most effective public health strategy for reducing alcohol-related birth effects likely involves higher taxes on alcohol (Abel 1998). A few recent studies support the idea that general population alcohol policies are relevant for reducing adverse health effects related to pregnant people’s alcohol use. Specifically, one US study found that stricter general population alcohol policies like restrictions on Sunday sales are associated with less drinking among women of reproductive age (Subbaraman et al. 2018, 2023). Regarding alcohol pricing in particular, a US-based study found that a one-cent increase in beer taxes was associated with a 1–2 percentage point decrease in low-birthweight between 1985 and 2002 (Zhang 2010), whereas a Finland-based study found increased adverse birth outcomes associated with an alcohol price cut in 2002–05 (Luukkonen et al. 2023). Other research in the US reports that higher alcohol taxes are associated with decreased child maltreatment (Markowitz et al. 2010; McLaughlin 2019). However, research on relationships between alcohol pricing and outcomes related to pregnant people’s consumption has tended to focus on policy changes occurring more than 20 years ago and on population-health outcomes with multiple causes rather than outcomes more closely linked to pregnant people’s alcohol use.

Thus, this study examines how alcohol taxes relate to key outcomes relevant to pregnant people’s alcohol consumption: drinking among women of reproductive age; alcohol-related treatment admissions among pregnant people; and infant maltreatment, infant alcohol-related morbidities, and SMM. Examining tax associations with outcomes across three different data sets allows us to draw broader conclusions about how alcohol taxes relate to health outcomes among reproductive-age women and infants.

Materials and Methods

Overview of study design

We examine relationships between nine separate tax variables and eight outcomes across three outcome data sets (detailed below). Each analysis follows the same modeling steps, includes similar sets of covariates and all years of available data, and uses similar principles to align with published models (e.g., Subbaraman et al. 2023), although each data set has a different unit of analysis and distinct outcomes.

Tax data

Data for primary exposures, taxes, came from NIAAA’s Alcohol Policy Information System (APIS), the Pacific Institute for Research and Evaluation, the Wine Institute (Blanchette et al. 2020), and original legal research using online legal research tools Westlaw and HeinOnline. Taxes are specific to three beverages, beer, wine, and spirits. The most prevalent types of alcohol taxes are:

  1. Ad valorem: taxes levied as a percentage (%) of the beverage’s retail price. Different ad valorem tax rates may apply to on- and off-premises sales. Ad valorem tax data are available for 1990–2020.

  2. Volume-based: taxes levied per gallon at wholesale or retail level. This tax can be converted to dollars or cents per drink. Volume-based tax data are available for 1993–2020.

  3. Sales: a tax on goods in general rather than a tax that specifically applies to alcoholic beverages. Not all states have sales taxes, and among those that do, not all apply their sales tax to alcohol. Some states instead have sales tax specific to each beverage type. Sales tax data are available for 1993–2020.

We analyzed beverage-specific (beer, wine, spirits) ad valorem on-premise, volume-based, and sales taxes (nine specific taxes total). We refer to “ad valorem on-premise taxes” as simply “ad valorem taxes” from here on. Ad valorem taxes were measured as a percentage of the retail price, volume-based taxes were measured as cents/drink, and sales taxes were measured using a Yes/No dichotomous indicator of whether the state has a specific sales tax for that beverage. Volume-based taxes were adjusted to the 2020 Consumer Price Index (CPI). APIS does not track wine and spirits ad valorem and volume-based tax data for the 17–18 government monopoly states whose prices are set by the state (the number varies because Washington privatized its system at the end of 2011). For each set of analyses, models first examined each tax separately, then combined models included the ad valorem (%), volume-based (cents/drink), and dichotomous (Y/N) sales tax for each specific beverage in the same model.

Analyses of drinking among women of reproductive age

Data set

Data for drinking among women 18 to ≤44 years came from the 1990–2020 National Alcohol Surveys (NAS), a US representative survey of the US population age 18 and older conducted every 5 years. Sampling methods changed from a multistage cluster design (1990) to random digit dialed (2000–20). An address-based sample (ABS) and nonprobability sample from a pre-recruited web panel were added in 2020. Interviews were conducted in-person (1990–95) via telephone (2000–20), and online (2020) in English or Spanish. Black and Hispanic populations were oversampled for all years except 1990. For the 2020 NAS, the cooperation rate for the combined telephone and ABS samples was 42.2%. Our analyses focus on N = 11 659 adult women of reproductive age, defined as ≤44 years (Denny et al. 2019). For analyses excluding government monopoly states, N = 8689. Following previous analyses of taxes and similar outcomes (e.g. Xuan et al. 2015), taxes are modeled contemporaneously with outcomes. We also expect most tax effects on drinking to occur within 1 year. Thus, tax and NAS data were merged on NAS survey year.

Outcomes

NAS outcomes were past 12 months any drinking, total number of drinks, number of days with ≥5 drinks, and number of days with ≥8 drinks. Any drinking and number of drinks were measured using the graduated frequency series, which assesses frequencies of drinking in a graduated series of quantity intervals (Greenfield et al. 2009). The graduated frequency measures also provide the number of days using 5–7, 8–11, and ≥ 12 drinks; these were used to calculate the number of ≥5 drink days and ≥8 drink days.

Statistical analyses

Logistic regression was used to model any drinking; negative binomial regression was used to account for over-dispersion of count outcomes. Unadjusted models included a fixed effect for year; adjusted models further included respondent-level age, race, marital status, education, employment, and interview month, state-year poverty, unemployment, and state-level consumption patterns (wet, moderate, dry; Kerr 2010). Sensitivity analyses adjusted for these covariates plus state-year per capita alcohol consumption. All models were survey-weighted and adjusted standard errors for clustering at the state level.

Analyses of alcohol-related treatment admissions among pregnant women

Data set

Treatment Episode Data Set: Admissions (TEDS-A) data track annual admissions of individuals ≥12 years at substance use disorder treatment facilities that receive public funds. Since 1992, facilities that receive any public funding are required to report TEDS-A data annually irrespective of whether the facilities are publicly or privately administered. The data set contains more than 50 million admissions and includes demographic and socioeconomic characteristics, including biological sex; pregnancy status at the time of admission; and the primary, secondary, and tertiary substances used at the time of admission. Because data are based on treatment admissions, an individual may be included more than once if they are admitted multiple times during a calendar year. We collapsed TEDS-A data sets for 1992–2019 across 50 states and the District of Columbia to analyze number of treatment admissions by state-year. Some states did not report data in some years (N = 40 state-years), and some states did not report admissions of any pregnant women in some years (N = 57 state-years). The final data set includes 1331 of a possible 1428 state-years (582 436 pregnant women admitted to treatment) and for analyses excluding government monopoly states, N = 873 state-years (438 868 pregnant women). Tax and TEDS-A data were merged on year of treatment of admission because, as with drinking outcomes, we expect most tax effects to occur within one year.

Outcomes

State-year outcome measures for TEDS-A analyses were (i) number of treatment admissions of pregnant women where alcohol was reported as the primary substance related to the treatment episode and (ii) number of admissions of pregnant women where alcohol was reported as any substance (i.e. primary, secondary, or tertiary) related to the treatment episode. To account for differences in population size and fertility across states and years, we examined admissions of pregnant women to treatment relative to the number of pregnancies that resulted in a birth in the state-year. We collected birth data from the National Center for Health Statistics by state-year and corrected multiple births (i.e. twins, triplets, etc.) as included as a single pregnancy that resulted in a birth.

Statistical analyses

Poisson models were fit using an offset variable (specifically, the natural log of number of pregnancies in the state-year) to account for differences in population size and fertility by state and year. The exponentiated Poisson coefficient of the tax variable reports how much the expected rate changes multiplicatively for a unit increase. Unadjusted models included fixed effects for state and year and state-specific quadratic time trends, and clustered standard errors by state. Adjusted models also included state-year poverty and unemployment. Sensitivity analyses additionally adjusted for state-year per capita alcohol consumption.

Analyses of infant maltreatment, infant morbidities, and SMM

Data set

The Merative Marketscan® Commercial Claims and Encounters database is a commercially available health insurance claims database that contains claims for a sample of privately insured people in all 50 US states and the District of Columbia. Claims have been adjudicated for payment and were obtained directly from a convenience sample of health plans and large employers. The study population included all female beneficiaries (aged 12–50) who resided in a US state or Washington, DC, gave birth to a singleton between 2006 and 2019 at least 280 days after a previous birth, and were continuously enrolled 1 year prior to and 1 year after delivery. Individuals in the sample had to be matched under the same household with an infant who had at least one claim within the 1st month after delivery and who was continuously enrolled for 1 year after birth. Birthing people younger than 25 were excluded from the study cohort, as >70% of those younger than 25 could not be matched with an infant on the same insurance plan—likely because the birthing person, but not the infant, was eligible to be covered on a parent’s health insurance plan. The final study cohort included a total of 1 432 979 birthing person–infant dyads. For analyses excluding government monopoly states, N = 1 060 251 birthing person–infant dyads. Additional details on cohort creation can be found here (Roberts et al. 2023).

Outcomes

Primary outcomes were dichotomous variables for infant injuries associated with maltreatment (i.e. injuries that a systematic review identified as having positive predictive values greater than 50% for maltreatment; Syed et al. 2021), infant morbidities related to maternal alcohol consumption (i.e. infant morbidities previous literature has identified as related to maternal alcohol consumption; O’Leary et al. 2013), and SMM (i.e. having one or more de novo SMM within 6 weeks after discharge from the delivery hospital; Chen et al. 2021; Centers for Disease Control and Prevention 2023). Outcome variables were measured from birth to one year and developed using ICD-9 and ICD-10 diagnosis and procedure codes. Specific codes used for each outcome are available in a previously published article (Roberts et al. 2023). Following previous analyses of birth outcomes (Zhang 2010), tax data were merged with outcome data based on the estimated year of conception, accounting for preterm births.

Statistical analyses

Logistic regression was used to analyze Marketscan outcomes. Unadjusted models included fixed effects for state and year and linear and quadratic time trends and standard errors clustered by state of residence. Adjusted models further adjusted for individual-level age (25–29, 30–34, 35–39, and 45+) and health status (categorized as 0, 1, 2, or 3+ comorbidities using the Elixhauser Comorbidity Index18) and state-year poverty and unemployment. Sensitivity analyses first adjusted for state-year per capita alcohol consumption, then additionally included those aged 12–24, for an additional 79 047 infant–birthing person dyads.

Results

Tax descriptives

Table 1 provides descriptive statistics for each tax at 5-year intervals. All beverage-specific ad valorem tax and sales taxes increased significantly (P < .05) on average over time (P-values from models regressing year on each tax, not shown). Conversely, all volume-based beverage-specific taxes (CPI-adjusted cents/drink) decreased significantly from 1990 to 2020. Numbers of states with off-premise beer or wine sales taxes increased significantly over time, whereas numbers of states with on-premise alcohol sales tax or off-premise spirits sales tax did not change significantly.

Table 1.

Beverage-specific taxes, 1990–2020.

Tax 1990 1995 2000 2005 2010 2015 2020
Beer ad valorem 1.1 (3.2); [0–12] 1.2 (3.4); [0–14] 1.2 (3.4); [0–14] 1.2 (3.4); [0–14] 1.0 (3.1); [0–14] 1.0 (3.2); [0–15] 1.4 (3.9); [0–15]
Wine ad valorem 1.6 (4.0); [0–15] 1.7 (4.2); [0–15] 1.7 (4.2); [0–15] 1.7 (4.2); [0–15] 1.5 (4.0); [0–15] 1.5 (4.0); [0–15] 1.9 (4.5); [0–15]
Spirits ad valorem 2.5 (5.1); [0–16] 2.6 (5.2); [0–16] 2.6 (5.2); [0–16] 2.4 (5.1); [0–16] 2.3 (4.9); [0–15] 2.3 (4.9); [0–15] 2.3 (4.9); [0–15]
Beer volume-based 0.04 (0.04); [0.01–0.17] 0.04 (0.03); [0.002–0.15] 0.04 (0.03); [0.002–0.13] 0.03 (0.03); [0.002–0.12] 0.03 (0.03); [0.01–0.13] 0.03 (0.03); [0.002–0.12]
Wine volume-based 0.04 (0.03); [0.01–0.15] 0.04 (0.03); [0.01–0.13] 0.04 (0.03); [0.01–0.13] 0.04 (0.03); [0.01–0.12] 0.04 (0.02); [0.005–0.11] 0.03 (0.02); [0.008–0.10]
Spirits volume-based 0.07 (0.03); [0.03–0.13] 0.07 (0.03); [0.03–0.11] 0.06 (0.03); [0.02–0.20] 0.06 (0.03); [0.02–0.18] 0.06 (0.03); [0.02–0.16] 0.05 (0.03); [0.02–0.15]
# states with off-premise beer sales tax 39 39 40 43 41 41
# states with off-premise wine sales tax 25 25 25 28 26 26
# states with off-premise spirits sales tax 25 25 25 28 25 25
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Ad valorem taxes were measured as a percentage of the retail price, volume-based taxes were measured as cents/drink, and sales taxes were measured using a Yes/No dichotomous indicator of whether the state has a specific sales tax for that beverage. Volume-based taxes were adjusted to the 2020 CPI. The APIS does not track wine and spirits ad valorem and volume-based tax data for the 17–18 government monopoly states whose prices are set by the state (17–18 because Washington switched during study period). Data for ad valorem taxes are available for 1990–2020. Data for volume-based taxes are available for 1993–2020.

Correlations (not shown) between beverage-specific ad valorem tax rates range from 0.6 to 0.8; correlations between beverage-specific volume-based taxes range from 0.5 to 0.7; correlations between ad valorem tax rates and volume-based taxes range from −0.3 to −0.006. These correlations indicate that ad valorem taxes should not be modeled with other ad valorem taxes and that volume-based taxes should not be modeled with other volume-based taxes. Thus, we examined ad valorem, volume-based, and sales taxes separately for each specific beverage.

Drinking among women of reproductive age

Models show no robust associations between taxes and drinking. In adjusted separate tax models (Supplementary Table S1), only wine volume-based taxes are significantly (P < .05) related to more days with ≥5 drinks [adjusted IRR (aIRR) = 1.05, 95% CI: 1.00, 1.10]. Combined tax models (Supplementary Table S2) show similar associations between taxes and drinking in terms of magnitude and significance, though results for beer and wine ad valorem taxes become significant at the P < .05 level for any drinking [adjusted odds ratios = 1.01, 95% CIs: 1.00, 1.02]. Sensitivity analyses (not shown), including state per capita consumption, showed the same pattern and magnitude of results for both single and combined tax models with the only significant associations remaining between beer and wine ad valorem taxes and any drinking.

Alcohol-related treatment admissions among pregnant women

When alcohol was reported as the primary substance related to treatment admission, only increased spirits ad valorem tax was associated with lower rates of admissions in unadjusted and adjusted [aIRR = 0.93, 95% CI: 0.90, 0.95] single-tax models (Table 2) as well as in unadjusted and adjusted [aIRR = 0.95, 95% CI: 0.91, 0.99] combined beverage-specific models (Table 3). Results were similar when examining alcohol reported as the primary, secondary, or tertiary substance related to admission. Sensitivity analyses that included per capita alcohol consumption showed the same pattern and magnitude of results (not shown).

Table 2.

Incidence rate ratios and 95% confidence intervals from separate Poisson regressions of tax associations with admission to substance use disorder treatment; 1992–2019 TEDS-A data (N = 1331 state-years; 582 436 pregnant women admitted to treatment).

Alcohol reported as primary substance at admission Alcohol reported as any substance at admission
Tax Unadjusted IRR aIRR Unadjusted IRR aIRR
Beer ad valorem 0.94 (0.86, 1.02) 0.94 (0.87, 1.02) 0.95 (0.90, 1.01) 0.96 (0.90, 1.02)
Wine ad valorem 0.94 (0.86, 1.02) 0.94 (0.87, 1.02) 0.95 (0.90, 1.01) 0.96 (0.90, 1.02)
Spirits ad valorem 0.92 (0.90, 0.94)*** 0.93 (0.90, 0.95)*** 0.93 (0.91, 0.96)*** 0.94 (0.92, 0.96)***
Beer volume-based 1.00 (0.96, 1.04) 1.00 (0.96, 1.04) 1.02 (0.97, 1.07) 1.02 (0.97, 1.07)
Wine volume-based 1.01 (0.95, 1.08) 1.00 (0.95, 1.06) 1.04 (0.93, 1.16) 1.04 (0.94, 1.15)
Spirits volume-based 1.01 (0.97, 1.06) 1.01 (0.97, 1.05) 1.03 (0.96, 1.10) 1.03 (0.96, 1.10)
Off-premise beer sales tax vs. not 1.31 (0.92, 1.88) 1.31 (0.93, 1.84) 1.22 (0.92, 1.63) 1.22 (0.93, 1.61)
Off-premise wine sales tax vs. not 1.23 (0.85, 1.78) 1.22 (0.85, 1.75) 1.17 (0.90, 1.53) 1.17 (0.90, 1.51)
Off-premise spirits sales tax vs. not 1.34 (0.95, 1.90) 1.34 (0.96, 1.87) 1.23 (0.93, 1.64) 1.23 (0.93, 1.62)
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Ad valorem taxes were measured as a percentage of the retail price, volume-based taxes were measured as cents/drink, and sales taxes were measured using a Yes/No dichotomous indicator of whether the state has a specific sales tax for that beverage. Volume-based taxes were adjusted to the 2020 CPI. Each tax is included in each model separately. Unadjusted models include an offset variable of the number of people giving birth in state-year, fixed effects for year and state, state-specific quadratic time trends, and clustering of standard errors by state. Adjusted models further adjust for state-level poverty and unemployment. Analyses of volume-based and sales taxes are for 1993–2019 (N = 1293 state-years; 565 951 pregnant women admitted to treatment). Analyses for wine and spirits ad valorem and volume-based taxes are missing data for government monopoly states (N = 850 state-years; 427 189 pregnant women for analyses missing data on government monopoly states).

* * * P < .001.

Bold indicates P < .05.

Table 3.

Incidence rate ratios and 95% confidence intervals from beverage-specific Poisson regressions of tax associations with admission to substance use disorder treatment; 1993–2019 TEDS-A data (N = 1293 state-years; 565 951 pregnant women admitted to treatment).

Alcohol reported as primary substance at admission Alcohol reported as any substance at admission
Tax Unadjusted IRR aIRR Unadjusted IRR aIRR
Beer
 Ad valorem 0.97 (0.89, 1.06) 0.98 (0.90, 1.06) 0.97 (0.91, 1.04) 0.97 (0.92, 1.04)
 Volume-based 1.01 (0.95, 1.08) 1.01 (0.95, 1.07) 1.02 (0.93, 1.13) 1.02 (0.93, 1.12)
 Sales tax (Y vs. N) 1.31 (0.90, 1.90) 1.32 (0.92, 1.89) 1.18 (0.91, 1.54) 1.19 (0.92, 1.55)
Wine
 Ad valorem 0.97 (0.88, 1.06) 0.97 (0.89, 1.06) 0.97 (0.91, 1.03) 0.97 (0.91, 1.04)
 Volume-based 1.01 (0.95, 1.08) 1.01 (0.95, 1.06) 1.04 (0.94, 1.16) 1.04 (0.94, 1.15)
 Sales tax (Y vs. N) 1.26 (0.87, 1.81) 1.27 (0.89, 1.80) 1.16 (0.90, 1.50) 1.17 (0.90, 1.50)
Spirits
 Ad valorem 0.94 (0.91, 0.99)** 0.95 (0.91, 0.99)* 0.94 (0.91, 0.97)*** 0.94 (0.91, 0.98)**
 Volume-based 1.01 (0.97, 1.06) 1.01 (0.97, 1.05) 1.03 (0.96, 1.10) 1.03 (0.96, 1.10)
 Sales tax (Y vs. N) 1.23 (0.90, 1.68) 1.23 (0.91, 1.67) 1.12 (0.91, 1.39) 1.13 (0.92, 1.38)
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Ad valorem taxes were measured as a percentage of the retail price, volume-based taxes were measured as cents/drink, and sales taxes were measured using a Yes/No dichotomous indicator of whether the state has a specific sales tax for that beverage. Volume-based taxes were adjusted to the 2020 CPI. Each model includes ad valorem, volume-based, and a sales indicator together for each beverage. Unadjusted models include an offset variable of the number of people giving birth in state-year, fixed effects for year and state, state-specific quadratic time trends, and clustering of standard errors by state. Adjusted models further adjust for state-level poverty and unemployment. Analyses for wine and spirits ad valorem and volume-based taxes are missing data for government monopoly states (N = 850 state-years; 427 189 pregnant women for analyses missing data on government monopoly states).

* P < .05, **P < .01, ***P < .001.

Bold indicates P < .05.

Infant maltreatment, infant morbidities, and SMM

Table 4 shows results from single-tax models for infant and maternal outcomes. Increased wine and spirits volume-based taxes were each associated with significantly lower odds of infant morbidities [wine aOR = 0.98, 95% CI: 0.96, 0.99; spirits aOR = 0.99, 95% CI: 0.98, 1.00] and of SMM [wine aOR = 0.91, 95% CI: 0.86, 0.97; spirits aOR = 0.95, 95% CI: 0.92, 0.97] in both unadjusted and adjusted models. Having an off-premise spirits tax was also significantly related to lower odds of SMM [aOR = 0.78, 95% CI: 0.64, 0.96]. Having an off-premise beer sales tax was associated with significantly higher odds of infant morbidities [aOR = 1.08, 95% CI: 1.02, 1.14] but lower odds of SMM [aOR = 0.79, 95% CI: 0.64, 0.97].

Table 4.

Odds ratios and 95% confidence intervals from separate logistic regressions of tax associations with infant and maternal health outcomes; 2005–19 Merative Marketscan® data (1432979 infant–birthing person pairs).

Infant maltreatment Infant morbidities SMM
Tax Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
Beer ad valorem 1.00 (0.94, 1.07) 1.01 (0.95, 1.08) 0.99 (0.97, 1.00) 0.98 (0.96, 1.00) 1.03 (0.94, 1.12) 1.02 (0.94, 1.12)
Wine ad valorem 1.00 (0.94, 1.07) 1.01 (0.95, 1.08) 0.99 (0.97, 1.00) 0.98 (0.96, 1.00) 1.03 (0.94, 1.12) 1.02 (0.94, 1.12)
Spirits ad valorem 1.07 (0.87, 1.31) 1.11 (0.92, 1.35) 0.97 (0.92, 1.03) 0.96 (0.90, 1.01) 1.10 (0.94, 1.30) 1.11 (0.92, 1.33)
Beer volume-based 0.99 (0.96, 1.01) 0.99 (0.96, 1.01) 1.00 (0.99, 1.01) 1.00 (0.99, 1.01) 1.02 (0.98, 1.06) 1.02 (0.98, 1.06)
Wine volume-based 0.93 (0.82, 1.04) 0.93 (0.84, 1.03) 0.98 (0.96, 1.00)* 0.98 (0.96, 0.99)* 0.91 (0.85, 0.97)** 0.91 (0.86, 0.97)**
Spirits volume-based 0.96 (0.92, 1.00) 0.96 (0.92, 1.00) 0.99 (0.98, 1.00)** 0.99 (0.98, 1.00)** 0.94 (0.92, 0.97)*** 0.95 (0.92, 0.97)***
Off-premise beer sales tax vs. not 1.11 (0.73, 1.69) 1.11 (0.73, 1.68) 1.08 (1.02, 1.14)* 1.08 (1.02, 1.14)* 0.79 (0.64, 0.98)* 0.79 (0.64, 0.97)*
Off-premise wine sales tax vs. not 1.10 (0.79, 1.52) 1.09 (0.79, 1.51) 1.05 (0.99, 1.12) 1.05 (0.99, 1.12) 1.31 (0.73, 2.36) 1.31 (0.72, 2.35)
Off-premise spirits sales tax vs. not 1.10 (0.73, 1.65) 1.10 (0.74, 1.64) 1.05 (0.97, 1.14) 1.05 (0.97, 1.14) 0.79 (0.64, 0.97)* 0.78 (0.64, 0.96)*
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Ad valorem taxes were measured as a percentage of the retail price, volume-based taxes were measured as cents/drink, and sales taxes were measured using a Yes/No dichotomous indicator of whether the state has a specific sales tax for that beverage. Volume-based taxes were adjusted to the 2020 CPI. Each tax is included in each model separately. Unadjusted models include fixed effects for year and state and clustering of standard errors by state. Adjusted models further adjust for individual-level age (categorical) and health status (0, 1, 2, or 3+ Elixhauser comorbidities) and state-year poverty and unemployment. Analyses for wine and spirits ad valorem and volume-based taxes are missing data for government monopoly states (N = 1 060 251 birthing person–infant dyads for analyses missing data on government monopoly states).

* P < .05, **P < .01, ***P < .001.

Bold indicates P < .05.

Table 5 shows results from beverage-specific models combining tax types. Generally, results were similar as those from single-tax models. However, unlike in single-tax models, combined tax models showed that having an off-premise wine sales tax was associated with significantly lower odds of SMM [aOR = 0.77, 95% CI: 0.61, 0.96] and that the relationship between off-premise beer taxes and SMM was no longer statistically significant [aOR = 0.78, 95% CI: 0.60, 1.01]. Results were robust in sensitivity analyses (not shown) including “per capita” alcohol consumption. When including “per capita” alcohol consumption and those <25 years, having an off-premise beer sales tax was no longer significantly related to infant morbidities and the spirits ad valorem taxes became significantly associated with lower odds of infant morbidities in both single and combined tax models [aOR = 0.94, 95% CI: 0.89, 0.99].

Table 5.

Odds ratios and 95% confidence intervals from logistic regressions of tax associations with infant and maternal health outcomes; 2005–19 Merative Marketscan® data (1432979 infant–birthing person pairs).

Infant maltreatment Infant morbidities SMM
Unadjusted Adjusted Unadjusted Adjusted Unadjusted Adjusted
Beer
 Ad valorem 1.01 (0.94, 1.08) 1.01 (0.94, 1.08) 0.99 (0.97, 1.01) 0.98 (0.96, 1.01) 1.01 (0.94, 1.09) 1.01 (0.94, 1.09)
 Volume-based 0.98 (0.96, 1.01) 0.98 (0.96, 1.01) 1.00 (1.00, 1.01) 1.00 (1.00, 1.01) 1.00 (0.98, 1.02) 1.00 (0.98, 1.02)
 Sales tax (Y vs. N) 1.12 (0.74, 1.72) 1.11 (0.73, 1.69) 1.07 (1.01, 1.15)* 1.07 (1.01, 1.15)* 0.79 (0.61, 1.02) 0.78 (0.60, 1.01)
Wine
 Ad valorem 1.01 (0.94, 1.08) 1.01 (0.94, 1.08) 0.99 (0.97, 1.01) 0.98 (0.96, 1.00) 1.01 (0.94, 1.08) 1.01 (0.94, 1.08)
 Volume-based 0.93 (0.83, 1.04) 0.93 (0.84, 1.03) 0.98 (0.96, 1.00)* 0.98 (0.96, 0.99)* 0.91 (0.85, 0.97)** 0.91 (0.86, 0.97)**
 Sales tax (Y vs. N) 1.10 (0.72, 1.68) 1.09 (0.72, 1.66) 1.05 (0.96, 1.15) 1.05 (0.95, 1.15) 0.77 (0.62, 0.97)* 0.77 (0.61, 0.96)*
Spirits
 Ad valorem 1.06 (0.87, 1.29) 1.10 (0.92, 1.31) 0.97 (0.92, 1.02) 0.95 (0.90, 1.01) 1.10 (0.95, 1.29) 1.11 (0.93, 1.33)
 Volume-based 0.96 (0.92, 1.00) 0.96 (0.92, 1.00) 0.99 (0.98, 1.00)** 0.99 (0.98, 1.00)** 0.94 (0.92, 0.97)*** 0.95 (0.92, 0.97)***
 Sales tax (Y vs. N) 1.10 (0.73, 1.66) 1.09 (0.73, 1.63) 1.05 (0.96, 1.14) 1.05 (0.96, 1.15) 0.76 (0.59, 0.97)* 0.75 (0.59, 0.97)*
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Ad valorem taxes were measured as a percentage of the retail price, volume-based taxes were measured as cents/drink, and sales taxes were measured using a Yes/No dichotomous indicator of whether the state has a specific sales tax for that beverage. Volume-based taxes were adjusted to the 2020 CPI. Each model includes ad valorem, volume-based, and a sales indicator together for each beverage. Unadjusted models include fixed effects for year and state and clustering of standard errors by state. Adjusted models further adjust for individual-level age (categorical) and health status (0, 1, 2, or 3+ Elixhauser comorbidities) and state-year poverty and unemployment. Analyses for wine and spirits ad valorem and volume-based taxes are missing data for government monopoly states (N = 1 060 251 birthing person–infant dyads for analyses missing data on government monopoly states).

* P < .05, **P < .01, ***P < .001.

Bold indicates P < 0.05.

Discussion

We assessed how state-level beverage-specific alcohol taxes are associated with alcohol-related health outcomes among women, other pregnant and birthing people, and infants. Overall, we found no robust significant associations between alcohol taxes and drinking outcomes, which is surprising given evidence that women are sensitive to alcohol taxes (Ayyagari et al. 2009; Meier et al. 2010; Subbaraman et al. 2020). Our focus on women ≤44 years might have reduced power to detect significant associations, especially given the very small changes in taxes over the study period. Although alcohol taxes are historically low (Naimi et al. 2018), we did find that inflation-adjusted taxes changed significantly over time, corroborating prior studies (Naimi et al. 2018; Blanchette et al. 2020). This suggests that our tax exposure variables varied enough to meaningfully assess associations with outcomes.

Results show significant associations between beer and wine ad valorem taxes and increased odds of any drinking, though these were not robust across models. This contrasts previous NAS findings, which show that increased beer taxes were related to lower odds of any drinking among White women (Subbaraman et al. 2020), perhaps because previous analyses used a composite measure, did not adjust for sales taxes, examined racial/ethnic subgroups, and did not restrict the population to those of reproductive age. Though public health authorities recommend that pregnant people avoid all alcohol consumption during pregnancy (US Preventive Services Task Force et al. 2018), this recommendation does not apply to women of reproductive age who are not pregnant and thus the implications of this finding for pregnant people in particular are not clear. Future research should explore whether alcohol taxes relate to drinking among pregnant people specifically.

Results also show one consistently significant tax association with treatment, specifically that increased spirits ad valorem taxes are associated with fewer alcohol-related treatment admissions Though we did not see evidence of tax associations with heavy drinking, increased taxes might nudge those who drink heavily (but do not have a use disorder) to drink less, making them less likely to progress to a use disorder and thus less likely to need treatment. Two primary factors could explain the general lack of significant associations between alcohol taxes and drinking and treatment found here. First, alcohol taxes account for a small portion of overall prices, e.g. one study found that excise taxes accounted for ~7% of liquor prices (Siegel et al. 2013). Second, alcohol is currently more affordable than at any time in the past 60 years, largely because of declines in alcohol prices (Kerr et al. 2013). The relatively small contribution of taxes to overall alcohol prices as well as the overall increase in affordability might also explain the lack of significant associations for the drinking and treatment outcomes. Thus, the lack of significant associations could be interpreted as alcohol taxes being too low rather than a true lack of associations between taxes and these outcomes.

We found the greatest number of significant associations between alcohol taxes and infant and maternal outcomes. Specifically, increased wine and spirits volume-based taxes are robustly related to lower odds of both infant and SMM while having an off-premise wine sales tax and having an off-premise spirits sales tax are robustly related to lower odds of SMM, though magnitudes of effect estimates are modest. Given its size, the Marketscan data set likely has the most power to reveal significant associations. Despite our finding that all taxes changed significantly over time, the magnitude of changes amount to one or two cents. Still, our findings of protective associations between volume-based taxes and infant and SMM support previous findings that even small increases in these types of taxes (e.g. one-cent/drink) could yield benefits related to pregnant people’s alcohol use (Zhang 2010). Current findings align with previous studies showing that general population policies are more often associated with better infant and maternal outcomes than pregnancy-specific policies (e.g. Roberts et al. 2023). Although more research is needed, current findings provide additional evidence that general population policies, like alcohol taxes, could benefit infant and maternal outcomes. This starkly contrasts pregnancy-specific policies, for which we find almost no benefits and consistent adverse effects.

Counterintuitively, having an off-premise beer sales tax was associated with higher odds of infant morbidities, though the association did not remain significant in sensitivity analyses. We also found no significant relationships between taxes and infant injuries. These results are unexpected, as prior studies show that higher volume-based alcohol taxes might reduce incidence of child maltreatment (Markowitz et al. 2010; Luukkonen et al. 2023). Future studies could examine composite tax measures (which combine beverage-specific ad valorem and sales taxes), as one study concluded that combined tax measures improve model fit (Xuan et al. 2015). We modeled taxes separately because (1) each tax might have different associations that could be obscured in a combined measure and (2) ad valorem taxes are measured as a percentage of price and require assumptions regarding average price per drink to calculate a combined tax.

Limitations

First, APIS does not provide wine and spirits ad valorem or volume-based tax data for “government monopoly” states whose prices are set by the state, restricting analyses to 32–33 states when examining those taxes and limiting generalizability to those states. Second, despite the NAS being the longest, most detailed repeated US alcohol survey available, sample size might have affected power to detect significant associations (N = 11 659; N = 8689 after exclusion of government monopoly states). Given low tax values and small changes over the study period, larger sample sizes may be needed to detect associations between taxes and drinking outcomes. Though other national repeated surveys that include alcohol questions exist, the NAS has the longest timeframe with commensurate, detailed alcohol use measures, and captures more of the US alcohol consumed than other population-based surveys (Esser et al. 2022). Third, drinking data are from women of reproductive age, not pregnant people nor other people with capacity for pregnancy; future studies should examine pregnant people specifically. Fourth, drinking data are self-report, and could be under-reported.

Fifth, TEDS-A data come from treatment facilities that receive public funding; findings do not generalize to all treatment admissions. Treatment admissions data are missing for some states in some years (137 of 1428 state-years); this could bias results if data are missing for years when a tax change occurs and if the tax effects are concentrated in those years. Sixth, TEDS-A data were aggregated at the state-year level; we could not adjust for individual-level confounders. Seventh, infant and maternal outcome measurements are based on diagnosis and procedure code data in claims data. Although we used codes that others have used to measure these outcomes in claims data (Roberts et al. 2023), each case has not been individually reviewed and compared with clinical measurements. Eighth, because of the inability to match most birthing people younger than 25 with an infant and thus the need to exclude them from these data, findings do not generalize to young people. Finally, Marketscan claims data are from individuals with certain health plans, including employer-sponsored insurance, so the findings may not generalize to people with other type of insurance.

Conclusion

Results provide evidence of protective associations between wine and spirits taxes with both alcohol treatment admissions and infant and SMM. As others have noted (Blanchette et al. 2019, 2020), alcohol taxes in the USA are at a historic low and policies that index tax rates to inflation might yield more public health benefits, including for birthing people and infants. Policies that restrict alcohol availability are related to less drinking in the general population and among women of reproductive age specifically (Subbaraman et al. 2023). Furthermore, stronger alcohol policy environments impact drinking and related health problems more than weaker alcohol policy environments (Naimi et al. 2014). Thus, increasing alcohol taxes while also restricting availability should have the greatest impact on health outcomes.

Supplementary Material

Tax_analyses_new_supplemental_tables_agae015
tax_analyses_new_supplemental_tables_agae015.docx (28.9KB, docx)

Acknowledgements

The authors gratefully acknowledge Doug Leslie and Tammy Corr for their work creating the Marketscan study cohort and supporting the variable creation in the data set, and Jason Blanchette for sharing volume-based tax data.

Contributor Information

Meenakshi S Subbaraman, Behavioral Health and Recovery Studies, Public Health Institute, 555 12th St, Oakland, CA 94607, United States.

Alex Schulte, Advancing New Standards in Reproductive Health, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, S1330 Broadway, Suite 1100, Oakland, CA 94612, United States.

Nancy F Berglas, Advancing New Standards in Reproductive Health, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, S1330 Broadway, Suite 1100, Oakland, CA 94612, United States.

William C Kerr, Alcohol Research Group, Public Health Institute, 6001 Shellmound Ave, Suite 450, Emeryville, CA 94608, United States.

Sue Thomas, National Capital Region Center, Pacific Institute of Research and Evaluation, 4061 Powder Mill Road Suite 350, Beltsville, MD 20705-3113, United States.

Ryan Treffers, National Capital Region Center, Pacific Institute of Research and Evaluation, 4061 Powder Mill Road Suite 350, Beltsville, MD 20705-3113, United States.

Guodong Liu, Center for Applied Studies in Health Economics, Pennsylvania State College of Medicine, 90 Hope Drive, Suite 2200, Hershey, PA 17033, United States.

Sarah C M Roberts, Advancing New Standards in Reproductive Health, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, S1330 Broadway, Suite 1100, Oakland, CA 94612, United States.

Author contributions

Meenakshi S. Subbaraman (Conceptualization [equal], Data curation [equal], Formal analysis [equal], Funding acquisition [supporting], Methodology [lead], Writing—original draft [lead]), Alex Schulte (Formal analysis [equal], Writing—review & editing [equal]), Nancy F. Berglas (Formal analysis [equal], Writing—review & editing [equal]), William C. Kerr (Conceptualization [equal], Funding acquisition [supporting], Methodology [supporting], Writing—review & editing [supporting]), Sue Thomas (Data curation [lead], Writing—review & editing [supporting]), Ryan Treffers (Data curation [lead], Writing—review & editing [supporting]), Guodong Liu (Data curation [lead], Writing—review & editing [supporting]), and Sarah C.M. Roberts (Conceptualization [equal], Funding acquisition [lead], Investigation [equal], Project administration [lead], Supervision [lead], Writing—original draft [supporting], Writing – review & editing [supporting])

 

Conflict of interest: W.C.K. has received support for contracts and/or travel from the National Alcoholic Beverage Control Association. W.C.K. has also been paid as an expert witness regarding cases on alcohol policy issues retained by the Attorney General’s Offices of the US states of Indiana and Illinois under arrangements where half of the cost was paid by organizations representing wine and spirits distributors in those states.

Funding

This work was supported by R01 AA023267 and P5037 AA005595 from the US National Institute on Alcohol Abuse and Alcoholism.

Data availability

Data from the National Alcohol Survey are available on reasonable request to the Alcohol Research Group (https://arg.org/center/national-alcohol-surveys/). Data from the Treatment Episode Data Set: Admissions are publicly available from the Substance Abuse and Mental Health Servies Administration (https://www.samhsa.gov/data/data-we-collect/teds-treatment-episode-data-set). Data from the Merative Marketscan® Commercial Claims and Encounters database are publicly available for a fee (https://www.merative.com). Data on ad valorem and sales taxes will be shared on reasonable request to the corresponding author. The authors do not have permission to share data on volume-based taxes.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Tax_analyses_new_supplemental_tables_agae015
tax_analyses_new_supplemental_tables_agae015.docx (28.9KB, docx)

Data Availability Statement

Data from the National Alcohol Survey are available on reasonable request to the Alcohol Research Group (https://arg.org/center/national-alcohol-surveys/). Data from the Treatment Episode Data Set: Admissions are publicly available from the Substance Abuse and Mental Health Servies Administration (https://www.samhsa.gov/data/data-we-collect/teds-treatment-episode-data-set). Data from the Merative Marketscan® Commercial Claims and Encounters database are publicly available for a fee (https://www.merative.com). Data on ad valorem and sales taxes will be shared on reasonable request to the corresponding author. The authors do not have permission to share data on volume-based taxes.

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