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. 2022 Jun 28;117(12):3004–3023. doi: 10.1111/add.15966

TABLE 2.

Reviews: study characteristics, main findings and limitations

Author, year; review type, research question ‘a priori’ design; search; study selection; data extraction Quality assessment Main findings Limitations/risks of bias

Ornstein, 1980 [29];

‐ Narrative review

Ornstein, Levy, 1983 [30];

‐ Narrative review

‐ Effectiveness of pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: unclear

‐ grey literature: unclear

‐ year of last search: not reported

‐ no. of studies included: 23 (LMIC: 0)

‐ duplicate study selection and data extraction: no

To some extent; the quality of individual studies was generally discussed throughout; some studies dismissed because of quality concerns. No formal quality assessment approach/tool used; useful critical review of econometric techniques used in individual studies, with suggestion to interpret results cautiously.

Total own‐price elasticities:

‐ beer: −0.3 to −0.9, all statistically significant;

‐ wine: wide variation between countries, generally inelastic;

‐ spirits: most studies generally weak; best estimate, unitary elastic;

cross‐price elasticities:

‐ no consistency in findings across studies.

Search strategy not described; criteria for quality assessment could be more explicit; limited generalizability to LMIC.

Leung and Phelps, 1993 [31];

‐ Narrative review

‐ Effectiveness of pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: unclear

‐ grey literature: unclear

‐ year of last search: not reported

‐ no. of studies included: 21 (LMIC: 0)

‐ duplicate study selection and data extraction: no

To some extent; the quality of individual studies was generally discussed throughout. No formal quality assessment approach/tool used; useful critical review of data, study design, and econometric techniques used in individual studies.

Total own‐price elasticities*:

‐ beer: −0.3

‐ wine: −1

‐ spirits: −1.5

*based on studies that used aggregate data; studies that used individual‐level data tended to find higher total own‐price elasticities

Cross‐price elasticities:

‐ no consistency in findings across studies;

Too few studies reported participation and consumption elasticities or elasticities between groups to make any conclusive statements.

Search strategy not described; criteria for quality assessment could be more explicit; limited generalizability to LMIC.

Edwards, Anderson et al., 1994 [32];

‐ Narrative review

‐ Effectiveness of pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: no

‐ grey literature: unclear

‐ year of last search: not reported

‐ no. of studies included: 46 (LMIC: 1)

‐ duplicate study selection and data extraction: no

None

Only broad results presented:

No average results provided; a description of the main results were discussed by countries and range of elasticities were provided:

‐ English‐speaking countries had a demand for beer that was less price elastic than the one for wines and spirits;

‐ Heavy and dependent drinkers were at least as responsive to price as moderate drinkers;

‐ Cross‐price elasticities between beverage type were generally small.

No quality assessment of included studies; no account for differing types of price elasticities (e.g. short‐run, long‐run, participation, consumption); no search strategy or proper discussion of results; results of the review do not support some of the proposed policy recommendations; limited generalizability to LMIC.

Fogarty, 2006 [27];

‐ Narrative review; meta‐regression

‐ Effectiveness of pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: no

‐ grey literature: unclear

‐ year of last search: not reported

‐ no. of studies included: 44 (LMIC: 1)

‐ duplicate study selection and data extraction: no

None

Mean (95% CI); median total own‐price elasticities:

‐ beer: −0.38 (−0.46, −0.30); −0.28

‐ wine: −0.77 (−0.89, −0.65); −0.59

‐ spirits: −0.70 (−0.84, −0.56), −0.59

Mean and median own‐price elasticities appear to be calculated without any distinction between price‐ and tax‐elasticities, between short‐ and long‐run price elasticities and include multiple estimates from the same studies.

Non‐systematic search strategy; study characteristics not presented; no quality assessment of included studies; no account for differing types of price elasticities (e.g. short‐run, long‐run, participation, consumption); limited generalizability to LMIC.

Gallet, 2007 [28];

‐ Narrative review; meta‐regression

‐ Effectiveness of advertising and pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: unclear

‐ grey literature: yes

‐ year of last search: not reported

‐ no. of studies included: unclear (132 studies that examined price, income or advertising elasticities) (LMIC: 1)

‐ duplicate study selection and data extraction: no

No quality assessment approach/tool used. Information collected on several common traits of studies, which covered a broad range of attributes, including the type of elasticity estimate, the beverage to which the elasticity applied, serial correlation, heteroscedasticity, the specification of demand, the nature of the data, estimation techniques used, year of publication and quality of the publication outlet. A criticism for some of these study traits were discussed

Total median own‐price elasticities

‐ all, short‐run: −0.52

‐ all, long‐run: −0.82

‐ beer: −0.36

‐ wine: −0.70

‐ spirits: −0.68

‐ alcohol (composite of beer, wine, spirits): −0.50

No specific distinction made by type of own‐price elasticities, and between subgroups; unable to disentangle policy‐relevant effects. Tax elasticities appear to be treated as own‐price elasticities.

Poorly described search strategy; study characteristics not clearly presented; no formal quality assessment of included studies; limited generalizability to LMIC.

Booth, Brennan, et al., 2008 [33];

‐ Narrative review

‐ Effectiveness of advertising and pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: unclear

‐ grey literature: yes

‐ year of last search: 2008

‐ no. of studies included: 2 reviews [20, 28] + 15 additional individual studies (LMIC: 0 (from additional 15 studies)

‐ duplicate study selection and data extraction: unclear

Quality assessment was discussed but no information was provided as to how it was operationalized. Limitations for each study were provided.

Only broad results presented.

‐ own‐price elasticity estimates highly variable, but consistently negative;

‐ stronger effect for cheaper drinks;

‐ scattered evidence suggests that price policies have a similar or stronger effect for at‐risk groups (young, young adult binge drinkers and heavy drinkers).

Only broad presentation of results (focus on direction of effect); unclear how quality assessment was operationalized; limited generalizability to LMIC.

Wagenaar, Salois, Komro, 2009 [20];

‐ meta‐analysis

‐ Effectiveness of pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: yes

‐ grey literature: yes

‐ year of last search: not reported

‐ no. of studies included: unclear (112 but only 105 references could be identified) (LMIC: 1)

‐ duplicate study selection and data extraction: no

No quality assessment approach/tool used. As a quality inclusion criterion, authors excluded from analysis empirical studies that did not provide sufficient data for calculating some form of numerical estimate of effect and estimate of its standard error. Sensitivity and robustness analyses to evaluate consistency of estimates across study characteristics were conducted.

Pooled standardized effect sizes (95%CI)

− aggregate‐level:

‐ alcohol −0.44 (−0.54, −0.34)

‐ beer: −0.17 (−0.22, −0.12)

‐ wine: −0.30 (−0.36, −0.23)

‐ spirits: −0.29 (−0.34, −0.23)

− individual‐level

‐ alcohol −0.03 (−0.05, −0.02)

‐ beer: −0.12 (−0.22, −0.02)

‐ wine: −0.14 (−0.26, −0.01)

‐ spirits: −0.10 (−0.17, −0.02)

‐ heavy drinking: −0.01 (−0.03, 0.00)

Total simple mean own‐price elasticities:

‐ alcohol −0.51

‐ beer: −0.46

‐ wine: −0.69

‐ spirits: −0.80

‐ heavy drinking: −0.28

Standardized effect sizes at aggregate‐level were calculated from total own‐price elasticities and combined short‐ and long run estimates. Unclear if standardized effect sizes at individual‐level refer to participation or consumption own‐price elasticities, or both; tax elasticities treated as own‐price elasticities.

No quality assessment of included studies; no account for differing types of price elasticities (e.g. short‐run, long‐run, participation, consumption); pooled elasticity estimates not reported; limited generalizability to LMIC.

Elder, Lawrence et al., 2010 [34];

‐ Narrative review

‐ Effectiveness of pricing policies at reducing alcohol use and related harms

‐ ‘a priori’ design: unclear

‐ search comprehensive: yes

‐ grey literature: yes

‐ year of last search: 2005

‐ no. of studies included: 46 (LMIC: 0)

‐ duplicate study selection and data extraction: unclear

Quality of study execution was assessed using a 9‐point scale, reflecting the total number of limitations to internal or external validity (study population and intervention descriptions, sampling, exposure and outcome measurement, data analysis, interpretation of results, and other biases). Studies with 0 or 1 limitation were categorized as having good execution, those with 2 to 4 limitations as fair execution, and those with 5 or more were categorized as having limited execution.

Total own‐price elasticities, median (interquartile interval):

‐ beer: −0.50 (−0.91, −0.36)

‐ wine: −0.64 (−1.03, −0.38)

‐ spirits: −0.79 (−0.90, −0.24)

‐ ethanol: −0.77 (−2.00, −0.50)

Prices/taxes were associated with a lower prevalence of excessive alcohol consumption;

Median estimates presented without any distinction between price‐ and tax‐elasticities, and between short‐ and long‐run price elasticities.

No account for differing types of price elasticities (e.g. short‐run, long‐run); limited generalizability to LMIC.

Fogarty, 2010 [21];

‐ Meta‐analysis; meta‐regression

‐ Effectiveness of pricing policies at reducing alcohol use

‐ ‘a priori’ design: no

‐ search comprehensive: no

‐ grey literature: unclear

‐ year of last search: not reported

‐ no. of studies included: 106 (LMIC: 1)

‐ duplicate study selection and data extraction: no

No quality assessment approach/tool used. As a quality inclusion criterion, author excluded from analysis empirical studies that did not provide sufficient data for calculating some form of numerical estimate of effect and estimate of its standard error. Sensitivity and robustness analyses to evaluate consistency of estimates across study characteristics were conducted.

Pooled total own‐price elasticities

− Fixed effects:

‐ beer: −0.26

‐ wine: −0.83

‐ spirits: −0.38

− Random effects:

‐ beer: −0.36

‐ wine: −0.57

‐ spirits: −0.5

Significance levels not reported; all estimates were statistically significantly different than 0.

Pooled estimates calculated without any distinction between price‐ and tax‐elasticities, and between short‐ and long‐run price elasticities.

Non‐systematic search strategy; no quality assessment of included studies; no account for differing types of price elasticities (e.g. short‐run, long‐run); limited generalizability to LMIC.

Patra, Giesbrecht et al., 2012 [35];

‐ Narrative review

‐ Effectiveness of pricing policies at reducing alcohol use and related harms

‐ ‘a priori’ design: unclear

‐ search comprehensive: yes

‐ grey literature: no

‐ year of last search: 2011

‐ no. of studies included: 26 (LMIC: 0)

‐ duplicate study selection and data extraction: yes

The quality of individual articles was assessed based on 4 domains: comparability of subjects, exposure, outcome measurement, and funding/sponsorship. For some studies, some limitations were reported (albeit extremely briefly) along study characteristics. Only broad results were provided. Changes in price or taxes of alcohol were found to have had an impact on drinking patterns, including high risk drinking. Limited quality assessment of included studies; overly broad presentation of results (focus on direction of effect); limited generalizability to LMIC.

Sornpaisarn, Shield et al., 2013 [24];

‐ Meta‐analysis

‐ Effectiveness of pricing policies at reducing alcohol use and related harms in LMIC

‐ ‘a priori’ design: unclear

‐ search comprehensive: yes

‐ grey literature: no

‐ year of last search: 2011

‐ no. of studies included: 12 (LMIC: 12)

‐ duplicate study selection and data extraction: yes

Minimum quality criteria for inclusion were used: (i) a longitudinal study had to have enough time points to provide a meaningful result; and (ii) the results were not confounded by any other large changes in alcohol control policies that were not taken into account.

‐ minimal and broad data limitation for each study were highlighted;

‐ authors stated that ‘problems with statistical analysis’ were assessed; however, no such assessment was presented.

Pooled total own‐price elasticities (95% CI):

‐ total alcohol: −0.64 (−0.80,−0.48)

‐ beer: −0.50 (−0.78,−0.22)

‐ other alcoholic beverages: −0.79 (−1.09,−0.49)

‐ all studies: −0.66 (−0.82,−0.51)

Pooled estimates calculated without any distinction between price and tax elasticities, between short‐ and long‐run price elasticities and between types of own‐price elasticities (participation, or consumption elasticities).

Relatively small number of studies included; relatively vague quality assessment criteria; non‐English or Thai studies or reports excluded.

van Walbeek, Blecher, 2014 [38];

‐ Narrative review

‐ Effectiveness of pricing policies at reducing alcohol use and related harms in LMIC

‐ ‘a priori’ design: no

‐ search comprehensive: unclear

‐ grey literature: no

‐ year of last search: not reported

‐ no. of studies included: 83 (LMIC: 7)

‐ duplicate study selection and data extraction: no

None

Only broad results presented:

‐ a 10% increase in the price of alcohol reduced alcohol consumption by ~4% to 8% in most low‐ and middle‐income countries.

Non‐systematic search strategy; no quality assessment; only very broad results presented, which limit usefulness of review; despite focus on LMIC small number of studies included, which limits generalizability to LMIC.

Li, Babor et al., 2015 [39];

‐ Narrative review

‐ Effectiveness of pricing policies at reducing alcohol use and related harms in China

‐ ‘a priori’ design: no

‐ search comprehensive: unclear

‐ grey literature: yes

‐ year of last search: not reported

‐ no. of studies included: 1 (LMIC: 0)

‐ duplicate study selection and data extraction: unclear

Study quality was evaluated on a scale of 1–5 according to the Maryland Scale of Scientific Methods.

Equity Checklist for Systematic Reviews to assess equity and gender sensitivity of actions was also used.

One study concluded that an alcohol tax reduction in 2007 and 2008 in Hong Kong was associated with increased alcohol use (as well as decreased binge drinking) Only one study included that examined the impact of prices/taxes on alcohol use; study's conclusion not based on included studies; limited generalizability to LMIC.

Chen, Abler et al., 2016 [26];

‐ Meta‐analysis

‐ Food Demand Elasticities in China

‐ ‘a priori’ design: no

‐ search comprehensive: yes

‐ grey literature: unclear

‐ year of last search: 2012

‐ no. of studies included: 11 (LMIC: 11)

‐ duplicate study selection and data extraction: unclear

None

Total own‐price elasticity:

‐ alcohol, mean: −0.77

‐ alcohol, predicted: −0.65

– Predicted cross‐price elasticities

‐ tobacco: 0.12

‐ rice: 0.13

‐ wheat: 0.26

‐ vegetables: 0.03

Statistical significance not reported.

No quality assessment of studies; unclear if all studies included measured alcohol similarly; statistical significance of pooled results not reported.

Scott, Muirhead et al., 2017 [42];

‐ Narrative review

‐ Effectiveness of marketing (price, promotion, product attributes and place of sale/availability) on key drinking outcomes (initiation, continuation, frequency and intensity) in young people.

‐ ‘a priori’ design: no

‐ search comprehensive: yes

‐ grey literature: yes

‐ year of last search: 2015

‐ no. of studies included: 2 (LMIC: 0)

‐ duplicate study selection and data extraction: yes

The Effective Public Health Practice Project (EPHPP) Quality Assessment Tool was used to assess the quality of individual studies. Quality assessment of individual studies not provided; only broad scores presented (weak, moderate, strong).

‐ Drinking continuation: one study found that alcohol discounts had a significant effect on alcohol consumption among young people ages 14–17 in the Netherlands.

‐ Drinking intensity: one study, using 2 datasets, found that binge drinking among US adolescents (mean age: 15 years) decreased as price increased (data set 1: price elasticity: −0.18 (95% CI, −0.30, −0.06); data set 2: price elasticity: −0.73 (95% CI, −1.51, 0.05).

The reported price elasticities for drinking intensity were past 2‐week binge participation elasticities.

Very small number of studies included limits the usefulness of the review; complete quality assessment not reported.

Boniface, Scannell, Marlow, 2017 [41];

‐ Narrative review

‐ Effectiveness of minimum unit pricing policies at reducing alcohol use and related harms

‐ ‘a priori’ design: yes

‐ search comprehensive: yes

‐ grey literature: unclear

‐ year of last search: 2017

‐ no. of studies included: 35 (LMIC: 3)

‐ duplicate study selection and data extraction: yes

The Effective Public Health Practice Project (EPHPP) Quality Assessment Tool was used to assess the quality of individual quantitative studies. Quality assessment of individual studies not provided; only broad scores presented (weak, moderate, strong).

There was very little evidence that minimum alcohol prices were not associated with consumption or subsequent harms. Results were presented with respect to the Bradford Hill criteria for causality:

‐ Strength of the association: reasonably good support;

‐ Consistency: very strong support;

‐ Specificity: very strong support;

‐ Temporality: very strong support;

‐ Dose–response/biological gradient: strong support, although the relationship is difficult to quantify;

‐ Plausibility: strong support;

‐ Coherence: strong support;

‐ Experiment: tentative support;

‐ Analogy: very strong support.

Limited discussion of effect sizes; complete quality assessment not reported; limited generalizability to LMIC.