| Additional Table 3: Adverse outcomes and unintended consequences |
Note: In this table, we present data on the following outcome categories:
Outcomes prespecified in our protocol as potential adverse outcomes or unintended consequences Outcomes described by the authors of primary studies as adverse or unintended Any other outcome which can arguably be perceived as adverse, including increases in direct or indirect measures of SSB intake, and increases in diet‐related anthropometric measures
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Albala 2008:
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Anand 2007:
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Baker 2016:
Outcomes: Per capita sales of sports and energy drinks Reported effects: Quote: "The FTA [free trade agreement] may have resulted in increased FDI‐inflows and soft‐drink production and also contributed to the diversification of soft drinks produced and sold in Peru with some positive (stagnated carbonates and increased bottled water) and some negative (increased juice and sports & energy drinks) implications for nutrition"
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Ball 2015:
Outcomes: Self‐reported SSB intake Effects: Quote: "The findings of (…) increased consumption of sugar‐sweetened beverages in the price‐reduction (time 2) (…) interventions were unexpected. The potential that these interventions had unintended adverse effects on increasing the purchasing or consumption of sugar‐sweetened beverages should be considered. For example, price‐reduction participants may have spent the money saved from discounted products to purchase more sugar‐sweetened beverages (substitution effects), or behavior‐change intervention activities may have unintentionally promoted increased consumption of sugar‐sweetened beverages. The latter effect seems unlikely because the objective outcome of the purchasing of carbonated sugar‐sweetened beverages increased at time 3 (6 mo postintervention) but not immediately postintervention when it might have been expected that any effect would have been the strongest. In addition, there was no significant increase in the purchasing of consumption of sugar‐sweetened beverages in the combined price‐reduction skill‐building intervention. (..) The magnitudes of increases were also very small. Values of sugar‐sweetened beverage purchasing were highly variable at baseline with highest values in the control group; subsequent increases in intervention groups could have reflected a regression to the mean"
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Bauhoff 2014 cohort and Bauhoff 2014 crosssectional
Outcomes: Compensatory consumption Reported effects: Compensatory intake of other foods and beverages are assessed indirectly through simulations comparing reductions in SSB and snack intake with changes in body weight, and study authors conclude that such effects may occur. Quote: "Basic simulations suggest that the observed reduction in intake (flow) translates into the observed lower obesity rates (stock) over the period during which the policy was active. However, the simulated effect is larger than the observed effects for overweight students, indicating that the restrictions may not have been entirely effective for this group of students. If this apparent mismatch is due to substitution behavior, this could suggest that further limiting substitution may be critical to successful school nutrition regulations. Children may substitute in‐school consumption with foods bought or brought from outside, or with foods that are still allowed on the premises but have high energy content”
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Blake 2018
Outcomes: Total revenue from beverage sales, target group and stakeholder perceptions Reported effects: Blake 2018 reports that total revenue from beverage sales decreased by −10% (95% CI −14 to −7) at four months. Blake 2018 reports that “39% [of customers] disagreed that the store should continue with higher prices, and 29% of surveyed customers disagreed that higher prices are generally a good way to reduce community consumption of sugary beverages. (…) The issue of customer complaints was a strong sub‐theme from the qualitative interviews of store and hospital staff. (…) [O]ngoing concerns about customer perceptions of the store and the long‐term impact on the business were expressed by all staff interviewees”
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Boelsen‐Robinson 2017
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Bollinger 2011
Outcomes: Total store revenue, compensatory consumption, stakeholder discontent Reported effects: Bollinger 2011 reports that total store revenue increased (regression coefficient: 0.005, SE: 0.004, P > 0.05), and that calories from foods and beverages per transaction decreased from 247 kcal to 232 kcal, or by −6.0% (95% CI −6.2 to −5.8). Bollinger 2011 reports that "[t]he NYC Board of Health first voted in the law in 2006, but legal challenges from the New York State Restaurant Association delayed its implementation until mid‐2008"
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Breeze 2018
Outcomes: Total cold beverage unit sales Reported effects: Breeze 2018 reports that total cold beverage unit sales decreased from 0.1 per attendance to 0.095 per attendance, equivalent to a decrease by −5% (P > 0.05) at 12 months
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Brimblecombe 2017
Outcomes: Compensatory consumption Reported effects: Brimblecombe 2017 reports that "[t]here have been concerns that total calories purchased might increase with price subsidies on healthy foods thereby potentially negating health gains. Our findings add to this evidence because we observed increases (albeit non‐significant) in the volume of other food purchases and increases in energy and sodium (due to its ubiquity in the food supply) during and after the price discount. Similar increases in purchases were observed for both healthy and less healthy food groups"
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Cawley 2015
Outcomes: Total unit sales, compensatory consumption Reported effects: Cawley 2015 reports that total unit sales decreased by −4.9% (95% CI −9.7 to 0.07) at 16 months, and that in the average food and beverage category, the number of zero‐star rated items sold per week decreased by −3183 units/week (95% CI −5454 to −913; P = 0.006) or −8.31% (95% CI −13.50 to −2.80; P = 0.004)
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Cohen 2015
Outcomes: Selection and consumption of white milk, stakeholder discontent Reported effects: Cohen 2015 reports that there was no statistically significant change (results not shown) in the selection and consumption of white milk, and that the intervention "met with substantial resistance from teachers, who were concerned that younger students were having trouble accessing the less prominently displayed sugar‐sweetened milk"
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Collins 2016 SNAP and Collins 2016 WIC
Outcomes: Compensatory consumption Reported effects: Collins 2016 reports that "[t]he $60 monthly SEBTC intervention had no impact on total daily consumption of added sugars from all foods and beverages (Appendix Exhibit 4.G)—a main contributor to empty calories in Americans’ diets. This is a positive finding considering that the greater financial resources for households that received from the SEBTC benefits could have increased children’s consumption of food high in added sugars or empty calories, and it did not"
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Cornelsen 2017
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Cradock 2011
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Da Costa 2014
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Ebbeling 2006
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Ebbeling 2012
Outcomes: Ebbeling 2012 reports that “[a]n adverse event was defined as any symptom or safety concern requiring medical attention that was reported by an adolescent or a parent during participation in the study.” Reported effects: Ebbeling 2012 reports that “[a] total of seven events were reported by the parents of participants in the experimental group during motivational telephone calls (diagnosis of Graves’ disease, diagnosis of polycystic ovary syndrome, an infected finger, an asthma attack, a mild head injury due to a car accident, the development of a blood clot after knee surgery, and temporary hearing loss due to the buildup of fluid and wax in the ears).” None of these events was deemed related to study participation
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Elbel 2013
Outcomes: Self‐reported number of fast‐food restaurant visits, compensatory consumption Reported effects: Elbel 2013 reports that the self‐reported number of fast‐food restaurant visits increased by 0.9 visits/week (P = 0.07), and that calories from foods and beverages per transaction decreased by −3.8 kcal/transaction (95% CI −125 to 119)
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Elbel 2015a
Outcomes: Milk‐taking events per 100 students Reported effects: Elbel 2015a reports that the number of milk‐taking events per 100 students decreased by −7 events (P = 0.17) at three months and decreased by −4 events (P = 0.24) at 10 months
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Emerson 2017
Outcomes: Total milk purachses Reported effects: Emerson 2017 reports that total milk purchases increased by +0.16 servings/day (P < 0.001). The study discusses the possibility of a number of unintended consequences. Quotes: "There are concerns as described previously by Birch et al. that giving external rewards for food selection may lead to avoiding a particular food when the rewards are stopped. We did see PP purchases drop on days that rewards were not given with PP sales remaining marginally higher than baseline PP sales. Even with our extended intervention children reverted to close to their baseline choices on days without the incentives suggesting that the intervention is useful for changing foods purchased/chosen but not sufficient for changing preferences. (…) Also, this study did not evaluate the impact of the intervention on the overall diet of the children. Further, we only had purchase data and did not measure actual food / beverage consumption. We cannot comment on how consumption was affected or how individual purchases varied during the study. However, consumption data using the PPP in a previous inner city elementary school pilot showed that waste was unaffected by the program"
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Ermetici 2016
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Finkelstein 2011
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Foster 2014
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Franckle 2018
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French 2010
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Harnack 2016
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Hartigan 2017
Outcomes: Sales revenue from all beverages Reported effects: Hartigan 2017 reports that monthly sales revenue from all beverages increased from USD 34,624 at baseline to USD 35,390 during the intervention (no statistical analyses shown)
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Hendy 2011
Outcomes: Food waste Reported effects: Quote: "Also, because the opaque beverage cartons made it difficult to determine the exact amount of fluid consumed, HDRINK was measured only as the type of drink chosen. However, we have observed that nearly 100% of children open and drink from their chosen cartons"
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Hernández‐Cordero 2014
Outcomes: Hernández‐Cordero 2014 reports that study authors “closely monitored the development of any adverse event (any symptom or safety concern requiring medical attention reported by a participant during a contact). Participants reporting potential adverse events were referred to the project’s physician” Reported effects: Hernández‐Cordero 2014 reports that "[t]wenty‐two participants from the IG group reported an adverse event during the intervention. The most common adverse events reported were tiredness, nausea, stress, or frequent urge to urinate"
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Hobin 2017
Outcomes: Total revenue, compensatory consumption Reported effects: Hobin 2017 reports that total revenue increased (coefficient estimate: 0.042, SE: 0.013, P < 0.01) at seven months, and that the average star rating of all products sold increased from 1.22 to 1.24 on a three‐star scale, with higher numbers indicating improved healthfullness (P < 0.001, coefficient estimate 0.014, SE 0.003)
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Hua 2017
Outcomes: Revenue, target group discontent Reported effects: Hua 2017 reports that "the control machines and machines that had product guidelines and price changes both had small but significant decreases in revenue (‐$156.10 and ‐$593.55, respectively; P<0.05)." Hua 2017 reports that "the intervention was discontinued in two vending machines in the improved‐availability‐only arm due to employee discontent, but these two machines were nevertheless included in the analysis." (For one of these vending machines, which sold solid foods, further details on the employee discontent is provided; it is not reported if the other vending machine in which the intervention was discontinued due to employee discontent sold beverages or solid foods only)
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Huang 2012
Outcomes: SSB purchases outside school, advertisement exposure Reported effects: Huang 2012 reports that SSB purchases outside school by households with school‐aged children decreased by −13 ml/day (95% CI −137 to 112) at six months. Huang 2012 reports that "[the graphic analysis of advertisement exposure rates before and after the introduction of the SSB ban, shown in figure 2 of the study's primary report] seems to indicate that major advertisers in the soft drink industry, such as the Coca‐Cola Company and Pepsi Co., largely operate their advertising campaigns on a national level. (...) [W]hile there are considerable differences in levels of advertising exposure that potential consumers in different age groups are exposed to, we see no discontinuities in the advertising exposure for any age group in the experimental DMAs [designated marketing areas] around the effective dates of the bans. If anything, overall advertising exposure went down after the implementation of the ban in July 2006. This might be more a result of seasonal differences, however, as we see a similar pattern in the following year"
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Lichtman‐Sadot 2016
Outcomes: SSB purchases outside school Reported effects: Lichtman‐Sadot 2016 reports that SSB purchases outside school increased by 36 ml/day (95% CI 13 to 60) in households with high‐school‐aged children during a 36‐month follow‐up period. Lichtman‐Sadot 2016 reports that during a 36‐month follow‐up period SSB purchases outside school decreased by −20 ml/day (95% CI −50 to 10) in households with middle‐school‐aged children, and decreased by −2 ml/day (95% CI −47 to 44) in households with elementary‐school‐aged children
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Minaker 2016
Outcomes: Switching behaviour (i.e. compensatory SSB purchases in stores that did not implement the intervention) Reported effects: Minaker 2016 reports that in one of the two stores which continued selling SSB, SSB sales increased by CAD 3/day (95% CI −93 to 99), and that in the other of the two stores, SSB sales decreased by CAD −17/day (95% CI −54 to 21) during the eight‐month intervention period
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Muckelbauer 2009
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Ng 2014a
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Ng 2014b
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Ni Mhurchu 2010
Outcomes: Purchases of less‐healthy products (including foods and beverages) Reported effects: Ni Mhurchu 2010 reports that purchases of all less‐healthy products (including foods and beverages) increased by 0.07 kg/week (95% CI −0.15 to 0.29) at six months, and by 0.05 kg/week (95% CI −0.18 to 0.27) at 12 months (including six months additional follow‐up without intervention)
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Olsho 2016
Outcomes: Stigma, alcohol beverage intake Reported effects: 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.” Olsho 2016 reports that alcoholic beverage intake increased by 0.08 drinks/day (95% CI 0.01 to 0.15) at four to nine months. Study authors note that this result 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
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Øverby 2012
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Peters 2016a
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Schram 2015
Outcomes: SSB sales per capita Reported effects: Quote: "SSCB [sugar‐sweetened carbonated beverage] sales per capita rose significantly faster pre‐ and post‐intervention in Vietnam compared with the control country the Philippines (DID: 4.6 L per annum, 95 % CI: 3.8 to 5.4 L, p < 0.008). (...) Vietnam’s increase in SSCBs was primarily attributable to products manufactured by foreign companies, whose annual sales growth rates rose from 6.7 to 23.1 %, again unmatched within the Philippines over this period (DID: 12.3 %, 95 % CI: 8.6 to 16.0 %, p < 0.049)"
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Schwartz 2009
Outcomes: Body dissatisfaction and dieting behaviour, compensatory SSB intake outside school Reported effects: Schwartz 2009 reports that there were no statistically significant effects on body dissatisfaction and dieting behaviour (results shown graphically only), and that consumption of beverages excluded by nutrition standards (mainly SSB) outside school decreased (P > 0.05, results not shown) at 12 months
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Schwartz 2016
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Schwartz 2017
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Siegel 2016a
Outcomes: Share of students selecting any milk Reported effects: Siegel 2016a reports that there was no statistically significant effect on the share of students selecting any milk (results not shown in the study)
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Siegel 2016b
Outcomes: Total milk purchases Reported effects: Siegel 2016b reports that total milk purchases decreased by −0.03 servings/day (P < 0.0001).Hudgens 2017 (a secondary publication to Siegel 2016b) reports that food waste (i.e. the share of total milk selected but not consumed by students) increased from 67% to 72% from before to after intervention implementation, from which we calculated an increase by 5 percentage points (P > 0.05, length of follow‐up not reported)
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Simons 2015
Outcomes: Various (see below) Reported effects: Simons 2015 reports that at 10 months "1/5 of the intervention group reported having experienced an injury (the most frequently mentioned injuries were bruises or strained muscles/tendons) while playing the Move video games"
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Sturm 2015:
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Taillie 2015:
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Tate 2012:
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Van de Gaar 2014:
Outcomes: Non‐standardised BMI, share of students with overweight or obesity Reported effects: Van de Gaar 2014 reports that non‐standardised BMI increased by 0.26 kg/m2 (95% CI 0.11 to 0.41) and that the share of students with overweight or obesity increased (OR 1.27, 95% CI 0.78 to 2.07) at 11 months
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Visscher 2010:
Outcomes: Leakage and misuse Reported effects: Quote: "As leakage depots were rather small, dripping of water took place, and this was solved by canteen personnel without major problems. One incident occurred in which pupils removed the water discharge hose in order to be replaced by a condom. (...) Throwing with water was not observed and not reported by the school canteen personnel"
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Waehrer 2015:
Outcomes: The study does not report if adverse outcomes occured or not, but notes an increase in caloric intake from SSB in the intervention group Reported effects: Waehrer 2015 reports that SSB intake increased by 34 kcal/day (95% CI 7 to 60) at eight months
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Whatley Blum 2008:
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