TABLE 3.
Author, year; review type, research question | ‘a priori’ design; search; study selection; data extraction | Quality assessment | Main findings | Limitations/risks of bias |
---|---|---|---|---|
Nelson, 2013 ‐ Health Econ Rev [22]; ‐ Meta‐analysis ‐ Price and income elasticities for alcohol beverages (beer, wine, spirits) |
‐ ‘a priori’ design: no ‐ search comprehensive: yes ‐ grey literature: yes ‐ year of last search: 2012 ‐ no. of studies included: 182 (LMIC: 16) ‐ duplicate study selection and data extraction: no |
Some studies excluded because of poor reporting (e.g. missing standard errors), or poor methods ‘linear model or poor data’; quality of included studies not generally assessed (no formal quality assessment approach/tool used); unclear which study was excluded and why. |
Pooled total own‐price elasticities, trimmed samples (95% CI) − fixed effects: ‐ beer: −0.26 (−0.46, −0.06) ‐ wine: −0.34 (−0.54, −0.14) ‐ spirits: −0.49 (−0.69, −0.29) ‐ alcohol: −0.46 (−0.66, −0.26) − random effects ‐ beer: −0.35 (−0.39, −0.31) ‐ wine: −0.58 (−0.64, −0.52) ‐ spirits: −0.64 (−0.70, −0.58) ‐ alcohol: −0.58 (−0.64, −0.52) Total own‐price elasticities, full samples, medians ‐ beer: −0.32 ‐ wine: −0.57 ‐ spirits: −0.67 ‐ alcohol: −0.54 |
Substantial overlap with Nelson, 2013 ‐ Journal of Wine Economics and Nelson, 2014 ‐ J Health Econ [23, 25]. No formal quality assessment conducted; opaque selection of individual studies' estimates; unclear if short‐run and long‐run estimates have been pooled together; heterogeneity not formally assessed; efforts to minimize the potential effect of alcohol prices on alcohol use apparent; data/results do not support all conclusions. |
Nelson, 2013 ‐ J Wine Econ [23]; ‐ Meta‐analysis; meta‐regression ‐ Price and income elasticities for wine and spirits |
‐ ‘a priori’ design: no ‐ search comprehensive: yes ‐ grey literature: yes ‐ year of last search: 2012 ‐ no. of studies included: 125 (LMIC: 6) ‐ duplicate study selection and data extraction: no |
Some studies excluded because of poor reporting (e.g. missing standard errors), or poor methods ‘linear model or poor data’; quality of included studies not generally assessed (no formal quality assessment approach/tool used); unclear which study was excluded and why. |
Pooled total own‐price elasticities, full samples (95% CI) − Fixed effects: ‐ wine: −0.63 (−0.65, −0.61) ‐ spirits: −0.48 (−0.50, −0.46) − Random effects: ‐ wine: −0.62 (−0.74, −0.50) ‐ spirits: −0.65 (−0.73, −0.57) Pooled total own‐price elasticities, trimmed samples ‐ same as Nelson, 2013 (Health Econ Rev) |
Substantial overlap with Nelson, 2013 ‐ Health Econ Rev [22]. No formal quality assessment conducted; opaque selection of individual studies' estimates; unclear if short‐run and long‐run estimates have been pooled together; heterogeneity not formally assessed; efforts to minimize the potential effect of alcohol prices on alcohol use apparent; data/results do not support all conclusions. |
Nelson, 2014 ‐ J Health Econ [25]; ‐ Meta‐analysis; meta‐regression ‐ Price and income elasticities for beer |
‐ ‘a priori’ design: no ‐ search comprehensive: yes ‐ grey literature: yes ‐ year of last search: 2012 ‐ no. of studies included: 114 (LMIC: unclear) ‐ duplicate study selection and data extraction: no |
None |
Pooled total own‐price elasticities (95% CI) − fixed effects: ‐ beer, full sample: −0.23 (−0.24, −0.22) ‐ beer, trimmed sample: −0.20 (−0.39, −0.31) − random effects: ‐ beer, full sample: −0.35 (−0.21, −0.19) ‐ beer, trimmed sample: −0.23 (−0.27, −0.19) |
Substantial overlap with Nelson, 2013 ‐ Health Econ Rev [22]. No formal quality assessment conducted; opaque selection of individual studies' estimates; unclear if short‐run and long‐run estimates have been pooled together; heterogeneity not formally assessed; efforts to minimize the potential effect of alcohol prices on alcohol use apparent; data/results do not support all conclusions. |
Nelson, 2013 ‐ Econ Anal Pol [36]; ‐ Narrative review ‐ Effectiveness of pricing policies at reducing alcohol use and related harms in heavy drinkers |
‐ ‘a priori’ design: no ‐ search comprehensive: yes ‐ grey literature: yes ‐ year of last search: 2012 ‐ no. of studies included: 19 (LMIC: 1) ‐ duplicate study selection and data extraction: no |
Some limitations were generally discussed. No formal quality assessment approach/tool used. |
Only broad results presented. Results generally not clearly synthesized. ‐ heavy drinking unlikely to be associated with prices or taxes (2/19 studies found statistically significant and substantial price/tax response by heavy drinking adults); ‐ prices/taxes likely associated with moderate drinking; ‐ prices/taxes possibly associated with heavy drinking among youth. |
No formal quality assessment conducted; no differentiating between types of elasticities; tax and price interventions not separated; limited generalizability to LMIC. |
Nelson, 2014 ‐ Health Econ [37]; ‐ Narrative review ‐ Effectiveness of pricing policies at reducing alcohol use by sex |
‐ ‘a priori’ design: no ‐ search comprehensive: yes ‐ grey literature: yes ‐ year of last search: 2012 ‐ no. of studies included: 21 (LMIC: 5) ‐ duplicate study selection and data extraction: no |
Some limitations were generally discussed. No formal quality assessment approach/tool used. |
Results not clearly synthesized. Study's conclusion: ‐ adult men had less elastic demands compared with women; ‐ there was little or no price response by heavy‐drinking adults, regardless of sex; ‐ although the sample was small, price might be important for drinking participation for younger adults; ‐ results were mixed but strongly suggested that heavy drinking by young adults, regardless of sex, was not easily dissuaded by higher prices. |
No formal quality assessment conducted; unclear exclusion criteria; data/results do not support all conclusions; limited generalizability to LMIC. |
Nelson, 2015 ‐ Health Econ Rev [43]; ‐ Narrative review ‐ Effectiveness of pricing policies at reducing binge drinking by age |
‐ ‘a priori’ design: no ‐ search comprehensive: yes ‐ grey literature: yes ‐ year of last search: 2012 ‐ no. of studies included: 65 (LMIC: 0) ‐ duplicate study selection and data extraction: no |
Some limitations were generally discussed. No formal quality assessment approach/tool used. |
Effects of prices/taxes on binge drinking, among youth, young adult and adult population varied between studies. Overall, very heterogeneous and mixed evidence: ‐ for youth 3/18 studies found statistically significant protective effects on heavy drinking from price/tax interventions, 10 null results, and others mixed; ‐ for young adults 1/5 studies that pooled men and women found statistically significant protective effects, 2/7 found significant protective effects for men, and 2/4 found significant protective effects for women; ‐ for adults 5/19 studies indicated statistically significant protective effects and 4/19 suggest mixed results. |
No formal quality assessment conducted; unclear exclusion criteria; data/results do not support all conclusions; limited generalizability to LMIC. |
Nelson, McNall, 2017 ‐ Eur J Health Econ [44]; ‐ Narrative review ‐ Evidence from natural experiments on the effectiveness of pricing policies at reducing alcohol use |
‐ ‘a priori’ design: no ‐ search comprehensive: no ‐ grey literature: yes ‐ year of last search: not reported ‐ no. of studies included: 29 (LMIC: 0) ‐ duplicate study selection and data extraction: yes |
Some limitations were generally discussed. No formal quality assessment approach/tool used. |
The review assessed the impact of tax/price policy changes in five countries (Denmark, Finland, Hong Kong, Sweden, and Switzerland). Results not clearly synthesized; little to no discussion of effect sizes; of the 29 studies included, 13 used Nordic Tax Study (NTS) data: ‐ binge drinking was reduced in 4/18 studies included; young adults and youth responded to changes in 4/14 studies, and changes seemed to have had little effect on older adults. |
Search strategy not comprehensive; no formal quality assessment conducted; poorly justified or unclear exclusion criteria; data/results do not support all conclusions; limited generalizability to LMIC. |