Summary of findings 8. Action across sectors compared to no or alternative intervention.

G Action across sectors compared to no or alternative intervention in children, youth and adults: impact on primary outcomes
Outcomes (follow‐up) No. of clusters or participants No. of studies Certainty of Evidence	Impact
G.1 Trade and investment liberalisation in low‐ and middle‐income countries
SSB sales ( 4 years) 4 countries 2 controlled ITS studies ⊕⊝⊝⊝ VERY LOWa	−Baker 2016 (annual rate of change in volume sales of SSB per capita): −1.4 percentage points (95% CI −2.5 to −0.4) Baker 2016 (annual rate of change in volume sales of sugar from SSB per capita): −1.0 percentage points (95% CI −1.9 to −0.06) Baker 2016 (annual rate of change in volume sales of sports and energy drinks per capita): +0.3 percentage points (P > 0.05, SE 0.8) Schram 2015 (retail sales of SSB): +13 ml/capita/day (95% CI 10 to 15)
G.2 Government food benefit programmes with incentives and restrictions
SSB intake (3 to 12 months) 2274 adults and 18,207 children 3 RCTs with 5 comparisons ⊕⊕⊕⊝ MODERATEb	Collins 2016 WIC (intake of sugar from SSB, USD 60 versus no USD benefit/month):−5 g/day (95% CI −8 to −3) Collins 2016 WIC (intake of sugar from SSB, USD 60 versus USD 30 benefit/month): −1 g/day (95% CI −3 to 2) Collins 2016 WIC (intake of sugar from SSB, USD 30 versus no USD benefit/month): −5 g/day (95% CI −8 to −2) Harnack 2016 (SSB intake, incentives + restrictions): −180 ml/day (95% CI −338 to −22) Harnack 2016 (SSB purchases, incentives + restrictions):USD −0.3/day (95% CI −0.5 to −0.2) Olsho 2016 (energy intake from SSB): −5 kcal/day/person (95% CI −21 to 11) Olsho 2016 (sugar intake from SSB): −1 g/day/person (95% CI −5 to 2)
Stigma (9 ‐ 11 months) 2009 adults 1 RCT N/A	Olsho 2016 reports that “the (…) evaluation found no evidence of increased stigma associated with rebate use. This may be because in most settings [the project] was implemented automatically via electronic cash registers.”
Alcoholic beverage intakec (9 ‐ 11 months) 2009 adults 1 RCT ⊕⊕⊝⊝ LOWd	Olsho 2016 (alcoholic beverage intake): +0.08 drinks/day (95% CI 0.01 to 0.15)
G.3 Government food benefit programmes without incentives and restrictions
SSB intake (3 months) 25,150 children 1 RCT with 3 comparisons ⊕⊕⊝⊝ LOWe,f	Collins 2016 SNAP (intake of sugar from SSB, USD 60 vs no USD benefit/month):−0.5 g/day (95% CI −2 to 1) Collins 2016 SNAP (intake of sugar from SSB, USD 60 vs USD 30 benefit/month): +1 g/day (95% CI −1 to 3) Collins 2016 SNAP (intake of sugar from SSB, USD 30 vs no USD benefit/month): −2 g/day (95% CI −4 to 1)
SSB intake (8 months) 2844 adults 1 CBA study ⊕⊝⊝⊝ VERY LOWg	Waehrer 2015 (SSB intake, median): +34 kcal/day (95% CI 7 to 60)
G.4 Multi‐component community campaigns focused on SSB
SSB sales (3 years) 32 supermarkets from 6 chains in 2 counties 1 controlled ITS study ⊕⊕⊕⊝ MODERATEh	Schwartz 2017 (SSB sales per product and store): −1.6 l/day (95% CI −2.0 to −1.2) (equivalent to a −20% decrease in the intervention group and a 0.8% increase in the control group) Schwartz 2017 (sports drinks sales per product and store):−0.4 l/day (95 CI −1.5 to 0.7) Schwartz 2017 (fruit drinks sales per product and store): −1.5 l/day (95% CI −2.0 to −0.9)
CBA: Controlled‐before‐after study; CI: Confidence interval; ITS: interrupted‐time‐series study; NRCT: non‐randomised controlled trial; RCT: randomised controlled trial; SSB: sugar‐sweetened beverages

^aDowngraded for risk of bias: Study authors of Baker 2016 and Schram 2015 note that there were relevant baseline differences between intervention and control countries, which may have affected the results. In Schram 2015 in particular, differences in baseline outcome measurements were large, approximately five times the size of the observed intervention effect. In Baker 2016 study authors note that the intervention may have had regional effects affecting the control country. In both studies study authors note that factors not attributable to the intervention may have differentially affected outcome measures in the intervention and control countries.
 ^bDowngraded for risk of bias: In Collins 2016wic, Harnack 2016 and Olsho 2016 participants were not blinded, and SSB intake data is self‐reported. Harnack 2016 also assessed SSB purchasing data based on grocery receipts, which may have been turned in selectively by participants, as noted by the study authors.
 ^cOutcomes included as potential adverse outcomes.
 ^dDowngraded by two levels for risk of bias: In Olsho 2016, study authors note that reported effects on alcoholic beverage intake may have been driven by several outliers in the second follow‐up assessment, who reported more than eight alcoholic drinks in the prior 24 hours. Participants were not blinded and outcomes self‐assessed.
 ^eDowngraded for risk of bias: In Collins 2016 SNAP participants were not blinded, and SSB intake data is self‐reported.
 ^fDowngraded for imprecision: Collins 2016 SNAP reports three comparisons (USD 60 vs no USD, USD 60 vs USD 30, and USD 30 vs no USD monthly benefit), and the 95% CI for all three comparisons include zero.
 ^gDowngraded for risk of bias: In Waehrer 2015, baseline outcome measurements as well as demographic and socio‐economic characteristics of participants differed substantially between the intervention and control groups. Study authors note that the control group may have included a substantial number of individuals receiving SNAP benefits at some time point during the study phase, and that this may have biased the results towards null.
 ^hUpgraded for magnitude of effect: We judged the effects on beverage sales to be large, and unlikely to be arisen by chance or through bias.