A Review of the Literature on Policies Directed at the Youth Consumption of Sugar Sweetened Beverages^,,

Abstract

Sugar sweetened beverages (SSB) constitute a large percentage of energy consumed by youth. This paper reviews the literature on school nutrition policies and price interventions directed at youth SSB consumption. In addition to considering the direct effect of policies on SSB consumption, we provide an overview of the literature on how SSB consumption affects total energy intake (TEI) and BMI, as well as on how TEI affects BMI. By considering each of these links, we attempted to gauge the effect of policies directed at SSB consumption, as well as highlight areas that merit future research. We found that school nutrition and price policies reduce SSB consumption and that reduced SSB consumption is associated with a reduction in energy intake that can influence BMI. Policies directed at SSB consumption can play an important role in reducing youth overweight and obesity.

Introduction

The consumption of sugar sweetened beverages (SSB)⁸ doubled in the US between 1977 and 2002 (1). Children and adolescents derive 10–15% of their total energy from SSB (2). SSB are not only associated with weight gain but have also been linked to diabetes, dental decay, and displacing healthier options such as milk (3, 4).

Of the low nutrition, energy dense (LNED) foods, SSB have been singled out as a target for policies aimed at reducing youth obesity (5). Limits on their availability have been suggested in schools, where youth are a “captive audience.” In 2006, the American Beverage Association and 3 major beverage firms agreed to limit access to SSB in schools, and many schools have adopted their own policies. However, schools contribute to only a small portion of youth consumption (6) and it is important to curtail availability from other sources, especially in the home environment. If the literature on tobacco is instructive (7), imposing taxes on SSB may be a particularly effective way to reduce youth consumption (8). SSB purchases would not only be discouraged among adolescents and young adults, but also among adults, who serve as role models for youth and purchase most of the SSB consumed by children (2).

Recent reviews (9–11) have considered school nutrition policies, but only James and Kerr (12) focused specifically on school policies directed at SSB consumption. Since their review, many new studies of school policies directed at SSB consumption and pricing have been published. This paper reviews the literature on both these sets of policies.

Although the public health concern is the effect of SSB policies on youth BMI, few studies have examined the effect on BMI and obesity, and those that did often failed to observe significant results. Consequently, we also consider how SSB consumption affects youth BMI. As shown in Figure 1, the effect of SSB policies on BMI involves 3 separate pathways. Reducing energy from SSB may not always translate into reduced total energy intake (TEI): youth may substitute SSB for other foods or beverages that contribute energy. Consequently, we considered studies that examined how changes in SSB consumption translate into changes in TEI and how TEI affects BMI. We attempted to gauge the effect of policies on BMI and highlight areas meriting additional study.

Figure 1.

The links from policies directed at SSB to BMI.

Methods

Studies were collected using searches of PubMed, the Social Science Index, and Social Science Research Network by using various combinations of the terms BMI, overweight, obesity, SSB, school, nutrition policies/interventions, and price. In addition, references were identified from pertinent articles, including recent reviews (9–11, 13).

Although some of the literature focused on carbonated beverages (i.e. soda), we considered all SSB beverages, including carbonated beverages, sports and vitamin drinks, and juice drinks. Most of the studies were conducted in the US, but we considered all English language studies from other countries. Because studies examined highly heterogeneous policies, meta-analytic techniques were eschewed. Rather, a comparative approach was employed that focused on the better studies.

Results

Levels and trends in U.S. SSB consumption

Using nationally representative data from the NHANES, Wang et al. (2) found that 79% of U.S. youth ages 2–19 y consumed SSB in 1999–2004, showing little change from 1988–1994. However, among youth who reported SSB consumed on the recalled day, average consumption increased from 252 to 273 kcal/d (1 kcal = 4.184 kJ). Average daily consumption for all youth was 228 kcal (10.7% of average daily intake): 24 kcal (7%) for ages 2–5 y, 184 kcal (9%) for ages 6–11 y, and 301 kcal (13%) for ages 12–19 y. Carbonated drinks contributed 55% and fruit drinks 33% of all SSB energy. On a typical weekday, 55–70% of all SSB energy was consumed at home, whereas 7–15% occurred in school (increasing with age).

Using the 3rd School Nutrition Dietary Assessment Study (2004–5), Briefel et al. (14) found that 68% of school children consumed SSB on a school day. Youth consumed an average of 159 kcal, of which 93 were at home, 36 were at school, and 31 were at other locations. In a separate study, the authors (15) found that SSB were consumed in school by 17% of students in elementary school (ES), 32% in middle school (MS), and 36% in high school (HS), of which only a portion were actually purchased at schools (27% in ES, 67% in MS, and 74% in HS). They (14) found a higher percentage of SSB obtained at school than Wang et al. (2) In addition to differences in the population surveyed, Briefel et al. (14) sampled on school days, whereas Wang et al. (2) sampled on weekdays. Both studies (16) found that most SSB are obtained by youth from home, but both relied on 24-h recall, which is subject to underreporting (17), especially by those who consume the most SSB.

In-school nutrition policies affecting SSB

As shown in Table 1, in-school policies to reduce SSB may involve price changes, limits on access, and educational policies. Results of experimental studies are shown in Table 2 and results of population/studies in Table 3. While few of the policies studied were directed solely at SSB, all studies had a component discouraging LNED foods and all reported effects on SSB consumption.

Table 1.

School nutrition policies that can be directed at SSB

Policy
SSB price increase
Cafeteria
Vending machines and snack bars
Limits on access to SSB
Limits on portion size or á la carte offerings
Cafeterias
All meals
Lunch and breakfast programs
Open vs closed campus during lunch
Education/information policies
Education in health classes
Parent education programs
Ingredient labeling

Table 2.

Randomized control studies of in-school policies directed at SSB¹

Study (reference, country)	Design and sample	Description of intervention	Analysis	Outcome measurement	Initial outcome levels	Final outcome levels	Conclusions	Comments
Blum et al. (31), United States (Maine), grades 9–11	Convenience sample of 235 students in 4 INT HS and 221 students in 3 CON HS. Schools volunteered to participate in study.	Reduced availability of SSB and diet soda offered á la carte and in VMs for 1 school year. Post-INT in the spring of 2005, 9 mo after start. Monitored compliance.	2 x 2 mixed ANOVA comparing subjects’ pre-INT servings/d to post-INT servings/d, stratified by gender. Beverage type weighted by baseline consumption.	SSBC (servings/d) in INT vs. CON schools. FFQ regarding foods consumed during past 30 d.	Girls SSBC: INT = 0.79 ± 0.8; CON = 0.82 ± 0.9; Boys: INT = 1.16 ± 1.0; CON = 1.3 ± 1.0.	1 school year f/u: SSBC decreased in both INT and CON boys and girls (F = 22.87, P < 0.05). Girls: INT = 0.69 ± 0.8; CON = 0.7 ± 0.8; Boys: INT = 1.07 ± 1; CON = 1.08 ± 1.0	No difference found in the change over time between INT and CON.	Nonrandomized convenience sample of short duration. State-wide school initiatives were considered during study, potentially influencing CON schools.
James et al. (43), United Kingdom, ages 7–11	644 children from 6 ES in southwest England. 29 classes randomized (15 INT, 14 CON).	Christchurch obesity prevention project to eliminate sodas and eat healthy diet. Over 1 school year (2001–2). INT included 4-session educational program.	11 randomized clusters. t test between INT and CON and paired t.	Total soda consumption. Children complete diaries on drinks consumed over 3 d. Records made over 2 weekdaysand 1 weekend day.	Mean carbonated SSB ± SD: 1.6 ± 0.6 for CON clusters, 1.2 ± 0.3 for INT clusters.	At 1-y f/u, totals: CON = 1.2 ± 0.5, INT = 0.9 . ± 6. Mean change: INT = 0.0 (95% CI = −0.3–0.4, P = 0.9), CON = −0.3 (95% CI:−0.6–0.1, P = 0.2). Consumption difference: 0.1 (95% CI = −0.4 to 0.5).	Targeted, school based education program reduced carbonated drinks consumed and the number of OW and obese children.	The low return rate of drink diaries at baseline and completion may have led to a response bias, although the % OW was similar in those who did or did not return the diaries.
				OW and obese (IOTF cutoffs) t- test. Intra-cluster correlation coefficient using Searle’s method. BMI. Waist circumference using centile charts. BMI converted to Z- scores and centiles.	BMI; CON = 17.6, INT = 17.4. Mean percentage > 91st centile (Z-score > 1.34) CON = 19.4, INT = 20.3.	One-year f/u: BMI: CON = 18.3, INT = 17.9. Diff: = 0.4 (−0.2–1.0). Mean %age > 91st centile (Z-score > 1.34); CON = 26.9, INT = 20.1; 95%, difference = 6.8 (−0.7–14.3).	The % OW and obese children increased in the CON by 7.5%, compared with a decrease in the INT of 0.2% (difference = 7.7%).
James et al. (44), United Kingdom, Ages 7–11	Of the original sample (644 children aged 7–11), 511 were tracked and measurements obtained from 434 children 3 y after baseline.	Same as James and Kerr (2004). Drink diaries were not collected due to lack of funding.	Same as James and Kerr (2004).	Change in BMI Z-score and rate of OW. BMI converted to Z-scores (SD scores) and to centile values with growth reference curves. Waist circumference converted to Z-scores.	Mean BMI at baseline: 17.5 for CON; 17.2 for INT, mean difference of 0.24, P = 0.24.	BMI:CON = 19.7, INT = ≥19.0, difference = 0.7, P = 0.03; change in BMI Z-score: CON = 0.1, INT = −0.01, difference = 0.10, P = 0.06; OW: increased in INT and CON; change in BMI:CON = 2.1, INT = 1.9, diff = 0.3, P = 0.12. Waist circumference increased in both groups w/difference of 0.09, P = 0.25.	For INT discontinued after 1 y, difference in rate of OW at 12 mo was not sustained at 3 y, although OW prevalence was still higher in the CON.	At f/up, 67% of original cohort was measured at 3 y. Because of the natural progression of children at school, the original clusters did not remain intact.
Lo et al. (46), Canada, 9th graders	Included 2 INT classes in different cities (n = 33, n = 24). 2 CON classes were paired with an INT class in 1 of the 2 cities (n = 24, n = 24). Schools selected according to neighborhoods and SES to include diversity.	2 classes (9th graders each in first city: (A) multiple peer educator and (B) self-taught (CON), and second city: (C) single peer educator class (C) and (D) self-taught (CON). Six sessions of nutrition education delivered by 2 peer educator models. INT: 45-min class over 6 wk.	Cronbach α used to determine internal reliability of the data. Based on Shapiro-Wilk, nonparametric tests used. Beverage assessments tested w/ Friedman test. Wilcoxon’s test used as a multiple comparison test with Bonferroni correction.	Mean carbonated soft drinks/wk. SSB intake, knowledge, and attitude assessed by self-administered questionnaire. Mean noncarbonated drinks/wk (at baseline); total SSB (at follow-ups).	Carbonated:I1 = 5; I2 = 8; C1 = 5; C2 = 4. Noncarbonated: 11 (I1); 7 (I2); 8 (C1); 11 ± 1 (C2).	Peer educator classes decreased SSB intake, sustained for 3 mo. Decreased juice and SSB intake in single model peer educator class, but disappeared after Bonferroni correction. Carbonated SSB intake in CON declined, but not sustained at 3-mo f-u.	After INT, classes with the peer educator multiple and single strategy showed a reduction in SSB intake, but students in Class A and C returned to baseline behavior at the 1-y f/up.	Possible misclassification, some fruit juice companies also produce fruit drinks. Questionnaire was self-administered. As a pilot project, the number of subjects was small.
Sichieri et al. (45), Brazil, Ages 9–12 y	1140 4th graders. 435 in INT and 608 in CON. Schools, randomized. Schools ranked based on the rate of obesity. 47 classes in 22 schools. Most from low-SES families.	7-mo INT focused on the reducing carbonated SSB. Healthy lifestyle education program using simple messages. Banners hung, and water bottles with the logo of the campaign given to children. Ten 1-h sessions.	Students completing the study compared (baseline v. after INT) using paired t tests. Intent-to-treat analysis using longitudinal analysis accounting for cluster (classes) effects through mixed models.	Daily carbonated drink consumption measured by one 24-h recall at baseline and at end of trial. At baseline, children also asked usual frequency of all beverages intake compared to previous month.	SSBC: INT = 552 mL/d ± 365; CON = 542 mL/d ± 367; P = 0.76.	End of school year: Significant decrease in carbonated drinks consumption in INT compared to CON (mean difference: −56 mL; 95% CI −119, −7 mL). Net change: INT = -69, 95% CI = −114- −24, CON = −0.13, 95% CI = -56–31.	Decreasing SSB intake resulted in no change in overall group BMI but in reduced BMI among OW children, mainly among girls.	The INT may not have been of sufficient intensity or duration. The reduction in carbonated SSB was associated with an increase in juice intake, suggesting that juices may have blurred the effects of soda reduction.
				BMI. Weight variation measured by change in mean BMI, OW, and obesity, defined using the BMI IOTF cutoffs.	BMI: INT = 18.3 ± 3.6; CON = 18.2 ± 3.2; P = 0.69.	End of year: No change (P = 0.33), after adjusting for age and f/up time. Net change: INT = 0.32 kg/m2; CON = 0.22; net difference = 0.1, 95% CI: −0.06 to 0.1
				Decrease in body fat and increase in lean body mass.	Total fat: INT = 36.46 ± 0.75; CON = 35.99 ± 0.71; P = 0.65. Total lean mass: INT = 24.71 ± 0.41, CON = (24.85 ± /46, P = 0.82.	16-wk f/u: no change in percent body fat, but accretion of lean mass was greater in INT than CON (P = 0.04). Total body fat: INT = 0.36 kg; .CON = 89 kg; P = 0.81. Lean mass (kg): INT = 0.92; .CON = 62, P = 0.04.

¹SSBC, SSB consumption; OW, overweight; VM, vending machine; INT, Intervention group; CON, control group; Diff, difference; h, hour.

Table 3.

Population studies of in-school intervention effects on sugar-sweetened beverage consumption¹

Study, reference, location, year	Methods	Sample	Intervention/independent variables	Outcome measures	Effect sizes	Major findings	Comments
Availability of VM, snack bars, and á la carte
Fernandes (20); US; 1998–1999; ES	Chi-square tests and t tests to determine differences across sociodemographic groups. Multivariate logistic regressions to estimate the effect of availability on soft drink consumption.	Early Childhood Longitudinal Survey-Kindergarten Cohort survey, a nationally representative survey of kindergarten students. Includes 10,215 children in 5th grade in 2303 schools across 40 states.	School administrator and student reports of availability of soft drinks in vending machines, school store/snack bar, or á la carte items at lunch.	Consumption or purchase of any SSB in the past week and overall consumption (or purchase) of SSB in the past week. Measures reported by child in direct assessments by interviewers.	Of students w/access at school (40%), 26% consume SSB (50% of their consumption). Limiting availability led to 4% decrease (OR 1.4) in any SSBC w/ 6% decrease for African Americans.	Soft drink availability at school may have a impact on overall consumption for ES children.	Limited to ES where consumption is typically low. Those who consume more SSB at school (low-income and African Americans) were more likely to consume more SSB overall.
Grimm et al. (29); Minnesota; 2000; ES and MS	Frequency distributions and chi-square tests to examine SSBC by gender and age. Multivariate logistic regression to examine role of each factor after adjusting potential confounders.	Mail-in surveys collected by a children‘s educational magazine distributed. The sample consisted of 560 children, 8–13 y old, who completed and mailed in the survey.	VM in 81.7% of schools.	~30% of the respondents reported soft drink consumption daily and 85% reported usually drinking regular (nondiet) soft drinks.	Odds of consuming soft drinks ≥ 5 times/wk = 2.4 if available in VM at school.	Those w/ strongest taste preference 4.50*** times more likely, and youth w/ parents who regularly drank soft drinks 2.88*** more likely to consume 5+ times/wk.	Crude measures of availability, used mail-in surveys. SSB intake related to taste preferences, SSB habits of parents and friends, SSB availability in the home and near school, and TV viewing.
Cullen and Zakeri (22); Texas; 1998–1999; ES and early MS	Assessed longitudinal change over 2 y. Cohort 1 in 4th grade ate NSLP meals during y 1, transitioned to 5th and 6th grade (MS) w/ access to a snack bar + NSLP in y 2; Cohort 2 students in MS = control.	Students from a school district in southeast Texas. Cohort 1 students (n = 430) and Cohort 2 students (n = 422).	Snack bar became available with SSB.	SSB consumption in oz.	SSB servings increased 62% (2.1 to 3.4 oz.***) in y 1, but decreased 12%* (4.9 to 4.3 oz.) in y 2. Similar patterns by gender and racial/ethnic groups.	A net effect of a 50% increase was observed.
Cullen et al. (23); Texas; 2001–2003	Assessed the impact of changes in school food policy on student lunch consumption in MS. Independent t tests and time series analyses used to document the impact of the policy change on consumption and sales data.	3 Houston Texas MS, 2790 6th-8th graders (61% Hispanic, 48% free lunch). Two years of lunch records. Students recorded amount and source of food and beverages consumed. Point-of-service machines provided sales from snack bars.	During the first year, no changes in the school food environment. During second year, chips and dessert foods were removed from the snack bars of all schools.	SSB consumption in oz. and sales	Student record: mean SSB intake declined (5.4 to 3.5 oz.**) and SSBC declined (5.2 to 2.6 oz.**) in lunch and snack bar, but more use of VM and home***. Snack bar sales: no change in SSBC.	Changes in foods sold in schools resulted in changes in student consumption, compensation may occur if other sources continue to sell LNED.	Discrepancy between sales data and student reports. Sales data may not have been punched correctly.
Cullen et al. (25); Texas; 2001–2003; MS	Assessed the effect of the Texas Public School Nutrition Policy on MS student lunchtime food consumption. ANOVA and ANCOVA and nonparametric tests were used to compare intake after the policy change with intake during the 2 previous years.	Three years of lunch food records (2671 in y 1, 5273 in y 2, and 5273 in y 3) collected from MS in southeast Texas: baseline: 2001–2002, after local changes: 2002–2003, and 1 y after School Nutrition Policy (2005–2006).	Voluntary state school nutrition policy restricting SSB portion sizes (<12 oz). Principals determined number of VM in their school. Beverage contract specified 20-oz. beverages, but were being changed to 12-oz. beverages during 2005–2006 to adhere to the Texas guidelines.	Students recorded amount and source of foods and beverages consumed. In y 1, the 3 schools had 21 VM, 86% dispensed beverages. In y 2, 42 VM w/ 83% dispensing SSB. After policy, only 23 machines (6, 7, and 10 per school), w/ 61% dispensing beverages.	SSB consumption fell (5.4 to 3.5 to 1.5 oz.) and soda consumption fell (4.8 to 2.7 to 0.1 oz. in y 1, 2, and 3). Consumption shifted from lunch and from VM (in y 3) to snack bar and home, with little compensation.	After the policy, consumption of vegetables, milk, and other nutrients increased and SSB and chips decreased. Fewer SSB, candy, chips, and dessert foods purchased and consumed, but more were brought from home and bought at snack bar.	Based on student report in last 24 h, did not control for clustering of schools.
Hartstein et al. (26); Texas, CA, NC; 2003; MS	Pilot study. Mixed models, accounting for the clustering of observations within schools, used to analyze changes between baseline and wk 6 for 2 models. Analyzed changes in nutrients and food offerings (kcal, percent kcal from fat, protein, and carbohydrate, water, SSB, regular, and reduced-fat/baked chips) sold per student.	Two MS at each of 3 field centers were recruited. Inclusion criteria of at least a 50% ethnic minority population and at least 50% of students eligible for free/reduced price meals. Included 13 pilot intervention goals, with 6 specific to the á la carte/ snack bar area, and others pertaining to the NSLP. Program length was 6 wk.	Pilot nutrition interventions were conducted in 6 schools by 3 field centers in Houston, Irvine (CA), and Chapel Hill (NC). á la carte/snack bar goals to reduce all regular chips serving size bags to ≤1.5 oz., increase lower-fat chip offerings by 25%, offer bottled water in 20-oz. size, and limit all sweetened beverages to ≤12 oz).	Cafeteria sales data from the á la carte/snack bar lines to assess goals (achieving 75% of unmet baseline goals) using daily school food production and sales records. Nutrients sold were computed. Weekly nutrient per student and number of items sold calculated for baseline and wk 6.	Significant changes in percent oz. of water*** and kcal of SSB*** were found across the 6 schools (average change in SSB oz. per school of −0.8. −0.4, −1.7, −1.0, 0.8, 0.15).	Reducing portion can reduce SSB consumption, especially if accompanied by a change in the size of bottled water portions	Pilot study.
Johnson et al. (27); Washington, US; 2007–2008; MS	Multivariate (random intercept) analysis w/ multilevel nature of the data and separate equations for SSBC (as affected by exposure) and exposure (as affected by policy). Aggregated to school level.	9151 students in 64 MS in 28 districts, designed to be representative. All public schools that enroll 7th graders and participate in USDSA school meal programs were eligible.	Strength of school district SSB policies scored on 3 SSB policy indicators ranging from 0 to 6 with a mean score of 3.25 ± 2.15. Exposure to SSB defined as the no. of vending slots and SSB venues determined by school.	Student SSB consumption at school assessed by a self-administered Beverage and Snack Questionnaire. Proportion of students who consumed any SSB at school 59% (19.2–79.8%).	SSB exposure effect on SSB consumption β = 0.157***. District SSB policy effect SSB exposure β = −9.50***. Policy effect on SSB consumption β = 2.43***.	School district SSB policies and exposure to SSB in MS were associated with student SSB consumption.	Cannot distinguish the effect of specific policies but found that policies reduce consumption (as much as a 12% absolute reduction in the percent of students consuming at school).
Vereecken et al. (34); Belgium; 2002; MS and HS	Multi-level logistic regressions to control for differences in school as distinct from personal characteristics.	360 schools in survey on school policy. Pupils of 197 schools (n = 16,560); for 157 schools data were available for both (n = 12 360). 11–12 y olds, and 13–18 y olds	17% of ES and 88% of secondary schools had SSB. Of 64 ES, 5% had school store and 9% had VM; of 183 secondary school, 27% had school store and 88% had VM.	Response options recoded to dichotomous variables. For soft drinks, daily consumers were compared to those who consumed less than daily.	Secondary school or available at school 1.40***. School policy 0.82**.	Found significant effects of school variables in secondary but not primary schools.	Just considered daily SSB consumers, appears comparable to US.
van der Horst et al. (33); Holland; 2005–2006; MS and HS	The relationship of availability of canteen food and drinks, the presence of food stores near schools, and individual cognitions to soft drink and snack consumption examined. In 2007, multilevel regression models. Analyzed associations and mediation pathways between cognitions, environmental factors, and behaviors.	Environmental Determinants of Obesity in Rotterdam School-children, a prospective 2-y study of adolescents (aged 12–13 y) in the 1st and 3rd year (aged 14–15 y) of secondary school. Cross-sectional study (2005–2006) among 1293 adolescents aged 12–15 y.	Data on the availability of soft drinks and snacks in school canteens were gathered by observation. The presence of food stores and the distance to the nearest food store were calculated within a 500-m buffer around each school.	Soft drink and snack consumption and related cognitions were assessed with self-administered questionnaires.	SSB and snack consumption associated w/ adolescents’ attitudes, subjective norms, parental and peer modeling, and intentions and inversely related to distance to nearest store and no. of small food stores. Effects mediated by cognitions. School canteen availability not related to SSB intake.	Provided little evidence of environmental factors in the school affecting soft drink and snack consumption. Individual cognitions appeared to be stronger correlates of intake than physical school-environmental factors.	Crude measures of availability, not US. Longitudinal research is needed to confirm these findings.
Neumark-Sztainer et al. (32); Minnesota; 2000; HS	Descriptive analyses of student eating patterns with individual level means and SD. For analyses of school policies and student eating patterns, mixed models (SAS Release 8.2, proc MIXED) used specifying the school as nested in the policy, implying each student in a school is under the same policy.	A randomly selected sample of 1088 HS students from 20 schools completed surveys about lunch practices and ending machine purchases. Part of TACOS study, a 2-y, group randomized, school based nutrition intervention trial. School policies assessed by the principal and food director surveys. The number of VM and their hours of operation assessed by trained research staff.	Students purchased snacks from VM 0.9 d/wk. Students purchased soft drinks from VM 1.6 d/wk; 61.5% of students reported purchasing soft drinks at least 1 d/wk. Of the 16 schools that had snack VM, 25% (n = 4) were closed during lunchtime. Of the 20 schools that had soft drink machines, 55% (n = 11) had them closed during lunchtime.	VM practices were assessed with 2 questions: “During a normal school week, how many days per week do you: 1) Get food from a school snack/food VM?; and 2) Get soft drinks from a school VM?"	In schools in which soft drink machines were turned off during lunchtime, students purchased soft drinks from VM 1.4 ± 1.6 d/wk compared to 1.9 ± 1.8 d/wk in schools in which soft drink machines were turned on during lunch (P = 0.040) and with policy about food sold in VM = 1.4 (1.7) d/wk, with no policy = 1.6 (1.7), P = 0.11).	Students w/ open campus more likely to eat at fast food restaurants than students w/closed campus (0.7 vs. 0.2 d/wk***). Snack food purchases associated with the no. of snack machines*** and students in schools w/ policies re: type of food sold. Snack food purchases in schools of 0.5 compared to 0.9 d/wk in schools w/out policies***.
Wiecha et al. (30); Massachusetts; 2002–2004; MS	Chi-square and nonparametric tests + C2 performed on unadjusted data; multivariable models adjusted for sex, grade, BMI, and race/ethnicity, and accounted for clustering within schools.	From a group randomized obesity intervention, 1474 students in 10 Massachusetts MS with VM that sold soda and/or other sweetened drinks.	Purchases from school VM and visits to fast-food restaurants in the preceding 7 d estimated by self-reports.	Daily SSB consumption (regular soda, fruit drinks, and iced tea) self-reported in the preceding 7 d. SSB intakes averaged 1.2 servings/d.	Among students using VMs(44%), 71% purchased SSB. Relative to no VM purchase, servings increased 0.21*** for 1–3 purchases/wk, and 0.71*** for 4+ purchases. Relative to no fast-food restaurant visits, SSB servings increased 0.13* for 1 visit/wk and by 0.49*** for 2–3, and by 1.64*** for 4+ visits.	Among students who use school VM, more report buying SSB than any other product category examined. Both school VM and fast-food restaurant use are associated with overall SSB intake. Reduction in added dietary sugars may be attainable by reducing use of these sources or changing product availability.	Did not consider the effect of specific policies, suggestive that increased use of VM associated with increased SSBC.
Shi (28); California; 2005; adolescents	Regression analysis to control for characteristics of students in schools with VM bans, using Kernel-based propensity score	Adolescents 2005 California Health Interview Survey, 4029 adolescents.	Whether SSB is available from VM in school (57% had available).	An average of 1.1 drinks on the prior day.	1.81 fewer drinks in schools without VM and 1.6 fewer drinks using the Kernel-based propensity score	SSB are consumed when not provided by VM. Considers overall consumption.	Does not consider other beverages and not longitudinal
Forshee et al. (6); US; various years before 2001; ages 13–18 y	A risk analysis equation of the relationship of carbonated soft drink consumption (CSSBC) in schools and BMI. The relationship between CSSB consumption and BMI was based on the largest estimate from 5 recent prospective observational studies.	Age 13–18 y. Continuing Survey of Food Intake by Individuals 1994–1996, 1998 (CSFII 536 male respondents and 549 female), and the NHANES 1999–2000 839 male respondents and 824 female respondents.	Counterfactual considered of removing SSB from school VM by subtracting out SSB consumption from school VM.	NHANES, males consumed 668 g/d CSSB, a 78-g increase from CSFII. Females consumed 442 g/d CSSB, an increase of 83 g from CSFII. CSSB consumed at home more than 5 times that at school, and more than one-half total consumed	No significant relationship between CSSB from all sources and BMI in either the CSFII or the NHANES data. The risk assessment showed no impact on BMI by removing CSSB consumption in schools (NHANES) or in school VM (CSFII).	The findings suggest that focusing on CSSB in schools will not affect BMI, both because consumption in schools is low and the relationship of CSSB and BMI is weak.	Limited to CSSB, does not include noncarbonated CSSB. Pre-2001, assumes fixed relationship of SSBC to BMI of −0.24 kg/m2 per serving/d. Does not examine the impact of specific policies. SSB consumption is low.
Fletcher et al. (38); US 5th grade, 2004; 8th grade, 2007	T-tests on mean differences in SSBC and weight.	Early Child-hood Longitudinal Survey. Nationally representative at baseline; 5th and 8th graders.	Students asked if soda could be purchased from VM, stores, etc. 27% of 5th graders and 60% of 8th graders had access from some outlets	Asked about soda, sports drinks, or SS fruit juice consumption in the last week. 84% of students consumed some SSB. 13% of 5th graders and 25% of 8th graders purchase at school.	Less soft drink consumption in schools w/ limited access (8 vs. 26% of 5th graders, 20 vs. 28% of 8th graders). Total consumption almost identical, little difference in % OW and % obese.	While consumption is reduced in school, it is offset through consumption outside of school	Cross sectional w/ no controls for differences in population in schools w/ vs. w/out limited access.
Lunch policies
Condon et al. (36); US; 2005	Considers foods consumed by children who did vs. did not participate in the school lunch and breakfast meal programs. Percentages of daily menus that offered and percentages of children who consumed specific foods. Two-tailed t tests used to assess differences between school meal program participants and nonparticipants.	Data were collected as part of the 3rd School Nutrition Dietary Assessment Study, a cross-sectional, nationally representative study conducted in 2005.	Effects of National School Lunch and Breakfast Programs	1% of lunch programs offer SS juice vs. 7% nonNSLP, Percentage consuming SSB.	Lunch in NSLP vs. non-NSLP: SS- juices 9 vs. 27*** overall, 4 vs. 31*** in ES, 15 vs. 32 in MS, and 16 vs. 20 in HS. Soda: 3 vs. 16*** overall, ES = 1 vs. 8***, MS = 4 vs. 11**, HS = 8 vs. 25** Breakfast in NSLP vs. non-NSLP: SS juices 4 vs. 8**, carbonated soda 2 vs. 8***.	School lunch participants more likely than nonparticipants to consume milk, fruit, and vegetables, and less likely to consume desserts, snack items, and SSB. Breakfast participants more likely to consume milk and fruit (mainly 100% juice), and less likely to consume SSB.	Cross-sectional study
Briefel et al. (14); US; 2004–2005; ES, MS, HS	Frequency distributions and regression equations by ES, MS, and HS and by food type, SSBC focusing on NSLP participation controlling for school and child/family characteristics.	4th School Nutrition Dietary Assessment Study, a nationally representative sample of public school districts, schools, and children, 287 schools and 2314 in grades 1–12.	Effects of National School Lunch and Breakfast Programs.	2-h dietary recall data converted to kcal.	NSLP participants consumed less energy from SSB at school than nonparticipants (11 vs. 39 kcal in ES*** and 45 vs. 61 kcal in secondary school***), but more energy from LNED foods.	NLSP participants consumed fewer LNED foods and SSB than nonparticipants. Energy density highest away from home and school. Improving home eating behaviors is warranted.	Participants were not more likely to consume SSB or LNED foods at home or other locations.
Access and lunch policies
Briefel et al. (14); US; 2004–2005; ES, MS, HS	Frequency distributions and ordinary least squares regression equations by ES, MS, and HS and by food type, outcome SSB consumption focusing on the effect of school policies (practice guidelines, availability, and mean practices) controlling for other school and child/family characteristics.	3rd School Nutrition Dietary Assessment Study, a nationally representative sample of public school districts, schools, and children, 287 schools and 2314 (732 in ES, 787 in MS, and 795 in HS).	No pouring rights (43.2% ES, 35.4% MS, 16.3% HS). No store or snack bar selling SSB (93.7% ES, 84.1% MS, 46.6% HS). No VM (75.6% ES, 8.5% MS, 1.6% HS). French fries not offered (30.7% ES, 17.5% MS, 19.7% HS).	24-h dietary recall converted to kcal. SSB = 17% in ES, 32% in MS, and 36% in HS, of which 27, 67, and 74% purchased in school. SSB at school (all youth, kcal/d): ES = 3, MS = 29, HS = 46. Of those consuming SSB: ES = 100, MS = 136, HS = 170 kcal.	Attending a school without stores or snack bars −22 kcal/school day in MS*** and −28 kcal in HS children.*** Lack of a pouring rights contract −16 kcal** and no à la carte offerings −-52 kcal***in MS, stricter rules against VM, − 40Kcals in HS,* not offering French fries -41 kcal in HS***.	Schools Wellness Policies or Nutrition Promotion Practices had no or a positive effect. Attending a school with stricter overall availability practices −-6 kcal*** in MS and −7 kcal*** in HS, no effect in ES. Stricter school lunch characteristics and school-related meal practices −11 kcal*** in HS and − 4 kcal in MS (P < 15%). Most effective practice was not offering French fries.	Study includes many policies, effects for individual policies may be overstated for those policies with the highest impact due to the high correlation of policies.
Woodward-Lopez et al. (35); California; 3 surveys 2005–2008; ES, MS, and HS	T-test of mean differences	3 surveys of California students, primarily Healthy Eating, Active Community (HEAC, 3527 students pre-, and 3828 student post-) study, 2006–2008, also the High School Study (2004–8) and School Wellness Study (2007–8).	Effect of the 2007 California nutrition standards bill.	Compliance, effect on SSB availability and consumption in and out of schools.	An increase in sports drink availability, but substantial reductions in soda and other sweetened beverages. They found that soda consumption at school fell by 8% with minimal and nonsignificant increases at home. Water consumption increased at school and home. (HEAC).	Sodas nearly eliminated, other SSB reduced by half. Reductions in soda consumption without compensation at home.	Does not control for differences in compliant and noncompliant school.

¹Includes only studies that provided the effect of school nutrition policies on SSB consumption by youth. Studies are cross sectional, unless otherwise indicated. **Significant at 0.05 level, ***significant at 0.01 level. SSBC, sugar-sweetened beverage consumption; VM, vending machines.

School pricing policies.

We found no studies that directly examined in-school SSB price policies, but reducing the price of lower fat snacks, fruits, and vegetables in school has resulted in increased sales (18), suggesting that students may be also sensitive to price differentials for SSB.

School access studies.

Using the 2004–2005 School Nutrition Dietary Assessment Study, Briefel et al. (15) found that 34% of students (43% of ES, 35% of MS, and 16% of HS) were in schools that had no “pouring rights” to soda with bottling companies, 78% (94% ES, 84% MS, and 47% HS) had no store or snack bar selling SSB, 15% (24% ES, 6% MS, and 5% HS) had no á la carte food or beverages except skim milk, and 40% (76% ES, 9% MS, and 2% HS) had no vending machines. However, vending and á la carte sales in 15% of MS and 21% of HS were free of LNED foods. Only 25% of schools had a policy that meals average <30% of energy from fats (33% in ES and 15% in MS and HS). The 2006 School Health Policies and Practices Study data (19) also indicates SSB are more accessible in older grades: 33% of ES, 71% of MS, and 89% of HS had either vending machines or a snack bar, and 13% of ES, 29% of MS, and 58% of HS allowed students to buy SSB from a vending machine or in a school snack bar during lunch periods.

For 5th graders, Fernandes (20) found that, of the 40% of children who had access, 26% consumed SSB at schools. Having access in schools increased the odds of consuming any SSB in or out of school in the previous week by 40%. As a result, eliminating access was predicted to reduce the percent who consumed SSB by 4%, with greater reductions among Black non-Hispanics (6%) and girls (5%).

Cullen et al. (21–25) examined the effect of school nutrition policies in a Texas MS with high Hispanic and lower income populations. Cullen and Zakeri (22) found that consumption increased by 60% (from 2.1 to 3.4 oz/d) as children advanced from 5th to 6th grade and SSB became more available, and fell only 10% in the next year. Upon removing LNED from snack bars and in cafeteria vending machines (23), student reported mean SSB school intake declined 35%, but slightly more SSB were obtained from non-cafeteria vending machines and home. However, changes in snack bar SSB sales were not significant, suggesting that results are sensitive to how SSB consumption is measured. In another study (25), a policy limiting portion size (≤12 oz) and vending machine availability was associated with a decline in overall SSB consumption, with little change in home consumption. The absence of compensatory increase in home consumption suggests that school based policy is effective in reducing overall SSB consumption.

Studies of programs in other states have also found that limiting access or serving sizes reduced SSB consumption in MS. In a pilot study conducted in 3 states, Hartstein et al. (24, 26) found that limiting serving size reduced average SSB consumption by almost 50% among students in 2 Texas and 2 California MS but found no change in 2 North Carolina schools. In Washington, Johnson et al. (27) found that SSB policy predicted SSB exposure (measured by vending machine slots and other SSB venues) and that greater exposure predicted higher consumption. Their results imply a 25% reduction in SSB intake between schools with no policy (score = 0) to a strong policy (score = 6). For California, Shi (28) found that adolescents in schools without SSB in vending machines consumed 0.16 fewer servings/d. In Minnesota, Grimm et al. (29) found children 2.4 times more likely to consume SSB 5 times/wk or more if SSB were available in school vending machines. In Massachusetts, Weicha et al. (30) found that SSB consumption increased with vending machines use and fast food restaurant visits.

For HS, Blum et al. (31) found that reduced á la carte and vending machine availability decreased SSB consumption in both intervention and control groups by ∼10% after 9 mo. The lack of difference between the 2 groups may have been due to local publicity during the study that influenced both groups. Neumark-Sztainer et al. (32) found that when vending machines were turned off during lunchtime, HS students purchased 25% fewer soft drinks (from 1.9 to 1.4 d/wk). Whereas a study (33) from the Netherlands did not find a significant association between SSB consumption and snack bar access in secondary schools, Vereecken et al. (34) found 40% more daily consumption by those Belgian secondary school students with SSB access in schools but found no difference in primary schools.

In the most comprehensive study of school access policies to date, Briefel et al. (15) found that SSB consumption was reduced by 22 kcal/school day (P < 0.01) in MS and by 28 kcal in HS (P < 0.01) without stores or snack bars, by 16 kcal (P < 0.05) in MS without a pouring rights contract, by 52 kcal (P < 0.01) in MS with no á la carte offerings, and by 40 kcal (P = 0.07) in HS with stricter rules against vending machines. Whereas their results indicate that some policies lead to large reductions in average SSB consumption, many were found to have no effect due to the difficulty in distinguishing their effects. Using an overall index of policies, their results indicated that daily SSB consumption was reduced by 48 kcal in MS and 56 kcal in HS with the strictest access policies compared to schools with no access restrictions and was 77 kcal lower in HS with the strictest meal practices. Relative to average consumption in schools with strict minimal policies, these reductions imply a 30% decrease in both MS and HS by the 21 and 27% of students, respectively, buying SSB in MS and HS, and by 40% from improved meal practice of the 27% purchasing SSB in HS. No effects were found in ES.

Woodward Lopez et al. (35) examined how the California nutrition standards bill affected SSB availability and consumption in and out of schools. They found substantial reductions in the availability of soda and other sweetened beverages but an increase in sport drinks. They found that soda consumption at school fell by 8%, with minimal and nonsignificant increases at home. Water consumption increased at school and home.

The National School Lunch Program (NSLP) provides limited SSB. Briefel et al. (14) found that students in the NSLP consumed 28 kcal less SSB energy in ES and 16 kcal in secondary schools than nonparticipants. Condon et al. (36) found that NSLP participants consumed less energy from sodas (3% in NSLP vs. 16% in non-NSLP, but 8 vs. 25% in HS) and sugar-sweetened juices (9% in NSLP vs. 27% in non-NSLP, but 4 vs. 31% in ES).

Forshee et al. (37) considered in-school SSB consumption and BMI but found no effect on BMI among those aged 13–18 y after removing SSB from school vending machines. Fletcher et al. (38) also found little effect on weight of SSB availability in vending machines. Although not explicitly distinguishing the effect on SSB consumption (and not reported in Table 3), 3 studies found varying effects of school access to LNED foods on BMI (39–41).

School education and wellness policies.

In 2006, 70% of states required nutrition and dietary behavior to be taught at the ES, MS, and HS levels as part of the health education curriculum (42). Briefel et al. (15) found no relationship to SSB consumption for nutrition education programs. Vereecken et al. (34) found that having a school policy against SSB access was associated with 18% less SSB consumption but found no relationship with education programs in either primary or secondary schools.

Three randomized control trials examined the effects of school education programs targeted at SSB consumption. James and Kerr (43) reported that SSB consumption over 3 d decreased by 0.6 servings (0.8 oz. or 236 mL) in the intervention group receiving an ES curriculum while increasing by 0.2 servings in the control group. At 12 mo, the percentage of overweight youth decreased 0.2% in the intervention group while increasing 7.5% in the control group, but the difference had disappeared within 2 y after the program ended (44). For an education program aimed at discouraging SSB among Brazilian students aged 9–12 y, Sichieri et al. (45) found that daily consumption of carbonated SSB decreased in the intervention group by ∼20%, with almost no change in the control group. The participants who were overweight at the beginning of the trial had a greater reduction in BMI, but the reduction was only significant for girls. In a 6-wk school nutrition education program directed at Canadian 9th graders, Lo et al. (46) found that peer educator classes (intervention) significantly reduced SSB intake at 3 mo compared with the self-taught classes (control). However, the effect disappeared after 1 y, possibly due to the lack of refresher courses.

Summary: in-school policies.

Policies that limit SSB availability and improve food offerings in school lunches have generally been associated with reduced SSB consumption. Policies restricting access in MS can reduce the percent of students consuming SSB by 25% (27) and the energy consumed by those students by 30% (15). Some studies indicate less effect, while studies by Cullen et al. (21–25) generally obtain larger effects. Fewer studies have been conducted for HS, but reductions of energy intake on the order of 30% (15) from access policies and 40% from improved meal practices were observed for the 27% of students buying SSB. Restricting SSB availability in vending machines and snack bars appears particularly effective. Whereas an experimental study found more prominent effects on those at higher BMI, such differences were not reported for cross-sectional studies (14). The role of initial weight, race/ethnicity, and socioeconomic status (SES) merit further attention.

Cross-sectional studies generally have not found that nutrition education programs reduce SSB consumption, although none of these programs targeted only SSB. Experimental education programs targeting SSB showed effects on students with higher initial BMI, but the effects faded after the programs stopped.

The effects of nutrition policies on BMI are less conclusive. Most of the studies considered a limited set of policies and have not examined the effect of school access policies over a period of longer than 2 y. The lack of evident impact of SSB policies on BMI may be due to the lack of an adequate follow-up period or may indicate that reduced SSB consumption in school is compensated by increased SSB consumption outside of schools or by increased intake of other LNED foods. However, studies (14, 20, 35, 47) have not found increased SSB consumption at home in response to reduced consumption in schools. In addition, lunch policies discouraging LNED consumption (e.g. French fries) were associated with reduced SSB consumption (15).

SSB tax policies

Unlike school nutrition policy, tax policies apply to all purchasers, not just those in school. Price may be increased through a direct tax on SSB or through disfavoring SSB from sales tax exclusion. Taxes have been imposed mostly on sodas. In 2007, 34 U.S. states taxed soda sold in grocery stores and 39 states taxed soda sold through vending machines at mean rates of 3.4 and 4.0%, respectively (48). The tax was never >10% of the price.

Table 4 summarizes studies on the effect of soda taxes on youth. Using a large, nationally representative survey, Powell et al. (49) found no effect of state level soda taxes on adolescent BMI, but found a weak effect of vending machine soda tax rates on BMI among teens at risk for overweight. A 1 percentage point increase in the vending machine tax rate was associated with a 0.006-kg/m² reduction in BMI among adolescents at risk of being overweight (P = 0.09). Sturm et al. (50) examined the effect of taxes on young school children and found limited effects on soda consumption or BMI, although stronger effects were observed for those with high income and those with high BMI. Using regression analysis, Fletcher et al. (51) found no effect of soda taxes on BMI or the probability that a youth consumes soda, but a 1% increase in the tax rate was associated with nearly 8 fewer kcal from soda consumed (P < 0.05), an approximate 6% reduction. Using the same dataset to examine mean BMI and soda consumption, Fletcher et al. (38) found no significant differences associated with differences in state taxes.

Table 4.

Population studies of the effect of tax interventions on youth consumption of SSB or youth weight¹

Study, location, year	Methods	Sample	Intervention/ independent variables	Outcome measures	Effect sizes	Major findings	Comments
Powell et al. (13); US; 1997–2006; Grades 8, 10, and 12	Multivariate regression to examine the association between state-level grocery store and vending machine soda taxes and adolescent BMI. Repeated cross-section of individual level data on adolescents, with controls for sociodemographic factors, food store and restaurant availability.	National data for 8th, 10th, and 12th grade students from the MTF study, combined with external data on state level soda grocery store and vending machine sales tax rates over the 10-y period from 1997 to 2006. n = 153,673 (29,319 OW).	The existing soda tax rates are relatively small resulting in fairly minimal dollar changes in prices. The average state sales tax on a $1.00 bottle of soda is 4.25% (SD = 2.47; range = 0%–7%) and 4.51% (SD = 2.28; range = 0–8%) when sold through grocery stores and VM, respectively.	BMI, distinguish youth at risk for OW.	No significant effect of soda taxes on adolescent BMI, except among those OW. Although all tax measures were negatively associated with BMI among high risk youth, only the VM tax rate was significant. A 1 PP increase in VM tax rate yielded a 0.006 reduction in BMI among youth at risk of OW (P = 0.09).	Current state-level tax rates are not linked to a decrease in adolescent weight. Taxes would probably need to be raised substantially in order to detect an association.	No state fixed effects, but has year effects. Does not include noncarbonated SSB, such as fruit juice drinks. Limited to small tax differences.
Sturm et al. (50); US; 2004; Grade 5	Multivariate linear regression to examine the effects of soft drink taxes on soft drink consumption patterns. Conducted a series of specification checks.	Early Child-hood Longitudinal Survey-Kindergarten Nationally representative of kindergarten students. Includes 5th graders.	State level taxes and measures of TV viewing and physical activity, as well as individual characteristics.	Consumption or purchase of any SSB in the past week (mean of 6) and data on BMI (level and change).	No significant relationship to consumption. A 1 PP increase in the tax rate reduces BMI by 0.013, with larger effects on those w/high BMI.	The findings suggest that soft drink taxes have a limited impact on overall consumption and BMI for ES children, although larger for high BMI and low income.	Limited to ES where consumption is typically low. Limited to small tax differences.
Fletcher et al. (38); US; 1988–2006; ages 3–18 y	In 2010 a, multivariate methods to examine the effects of soft drink taxes on soft drink consumption patterns and weight, with year and state fixed effects. Conducted a series of robustness checks. 2010 b analysis examines mean differences.	State soft drink sales and excise tax information between 1988 and 2006 and the NHANES (n = 20,953).	From 1988 to 2006, average soft drink tax rate varies between 1.5 and 2.3%. The number of states with any tax in each year varies between 19 and 24 and, among states with a tax, the average rate varies between 4.1 and 5.1%, with 53 tax rate changes over time.	59% of children consume any soft drink during the day with an average of 12 oz. and 122 kcal. Average energy intake from soda represents only 6%t of the average TEI, but the energy consumed from soft drinks are also approximately twice the amount of energy consumed from other SSB.	For 2010a study, soft drink tax has no effect on the probability of consumption. A 1 PP increase in tax rate reduces soda consumed by 8 kcal** (6% of sample mean), with little switch to diet soft drinks, but completely offset by increases in energy from other beverages. Found no relationship between soft drink taxes and BMI, OW, or obesity. For 2010b study, no mean differences.	The results suggest that soft drink taxation, as currently practiced in the US, leads to moderate reduction in youth soft drink consumption. Point estimates suggest that increase in tax rate of over 12 PP is required to reduce soda by 100 kcal.	Does not include noncarbonated SSB, such as fruit juice drinks. Finds substitution to whole milk, not fruit juices. Does not distinguish by age. The decrease in energy from soft drinks in response to an increased soft drink tax is offset by an increase in energy from whole milk. Limited to small tax differences.

¹Limited to studies that examine SSB consumption by youth. SSBC, SSB consumption; PP, Percentage Point, OW, overweight.

For adults, Kim and Kawachi (52) found no difference in obesity rates between states with and states without a ≥5% tax, but states repealing a soft-drink or snack food tax had an increase in obesity. Fletcher et al. (53) found that a 1% increase in the soda tax rate decreased BMI by 0.003 points and had a greater effect on low income and Hispanic adults. Although they did not distinguish beverages, Miljkovic et al. (54) found that a 10% increase in the price of sugar products was associated with a decrease in the prevalence of overweight by 2% and of obesity by 8%.

Although no study found a substantial effect of soda prices on BMI, demand studies generally found that price affects soda consumption. A recent review (55) concluded that the price elasticity for soft drinks is in the range of −0.8 to −1.0. For low-income consumers, Yen et al. (56) found that a 10% price increase was associated with an 8% reduction in soda consumption, with little effect of soda prices on the consumption of other beverages. Smith et al. (57) obtained SSB own price elasticities of −1.3, but found some evidence of cross-price elasticities with other beverages, indicating some offsetting effect. A 20% SSB price increase was found to reduce SSB energy intake by 38.8% for adults and 48.8% for youth, with an offset of 1.9% for adults and 6.1% for youth.

In sum, past studies have considered relatively small variations in soda tax rates that were generally applied to a limited set of SSB, thus providing weak evidence on their relationship to weight. Powell and Chaloupka (13) concluded that substantial tax increases will be necessary to have potent effects. Estimates from Andreyev et al. (55) imply that a tax increase at 20% of current prices would reduce consumption by between 16 and 20%. A 16–20% reduction in youth SSB consumption would translate into a reduction of 36–45 kcal, assuming average intake of 225 kcal (2). Although the studies do not distinguish youth, Epstein et al. (58) found that youth food consumption was closely related to purchases by their parents. Furthermore, studies have found that youth at risk for overweight and from low-SES families are particularly sensitive to fruit and vegetable prices (59, 60) and that high-BMI youth (61, 62) are more sensitive to food prices than low-BMI youth, suggesting that higher SSB taxes may have a greater impact on youth than on adults and on those at a high BMI or from low-SES families. However, if a tax is applied only to sodas, youth may substitute with nontaxed SSB and/or other LNED foods.

The relationship of SSB consumption and BMI

SSB consumption and BMI.

Reviews by Malik et al. (3) and Vartanian et al. (4) support a strong relationship of SSB consumption to BMI for adults and youth. A meta-analysis funded by the American Beverage Association (63) found almost no relationship of SSB to BMI, but that study was found (64) to be subject to scaling errors and failing to allow for the full impact on BMI (because TEI was held constant).

Three longitudinal studies found youth SSB consumption related to weight. For 11,654 youth ages 9–14 y followed for 3 y (65), BMI increased by 0.04 kg/m² (P < 0.01) for boys who increased soda consumption by 1 serving/d in the previous year. An increase of >2 servings/d was associated with a 0.14-kg/m² increase in boys (P < 0.01) and a 0.10-kg/m² increase in girls (P = 0.05). For 548 youth aged 11–12 y followed for 19 mo, Ludwig et al. (66) found a 0.24-kg/m² (P < 0.03) increase for each 8 oz. of SSB/d, and the odds of obesity increased 60% for each additional serving. For 10,904 low-income children ages 2–3 y followed for 1 y, Welsh et al. (67) found that SSB consumption was related to normal weight children becoming overweight (OR ≈ 1.5) and to overweight children remaining overweight (OR ≈ 2). Two recent studies (68, 69) also found SSB consumption related to the BMI of low-income, young children.

During a 25-wk experimental program delivering noncaloric beverages to adolescents’ homes, Ebbeling et al. (70) found that the intervention group’s consumption of SSB decreased by 82% and BMI was reduced by 0.75 kg/m² for the heaviest 3rd of the group, with no change in the control group. The experimental study by James and Kerr (43) obtained similarly large effects. Cross-sectional studies (3, 63, 64) obtain mixed results, but may be subject to bias if those at a high BMI abstain from consuming soda or switch to diet soda as part of a weight-loss strategy.

Studies of the effect of SSB consumption on BMI are often underpowered, have a short follow-up, or use weak assessment methods, e.g. a single 24-h recall (3). However, Ludwig et al. (66) found that, by replacing SSB, the BMI of those aged 8–12 y could be reduced by between 0.1 and 0.24 kg/m² over 19 mo, which translates to between 0.035 and 0.08 kg/y, a substantial portion of the 0.25-kg reduction needed to maintain appropriate weight (71). They also found that BMI depends on initial SSB consumption as well as changes in consumption, suggesting that diet history is important. Results from Ebbeling et al. (70) imply that BMI is reduced by 0.26 kg/m² for every serving per day of SSB displaced, comparable to the increase obtained by Ludwig et al. (66) Chen et al. (72) found that a reduction in SSB intake of 1 serving (12 oz.)/d was associated with a weight loss of 0.5 kg at 6 mo and 0.65 at 18 mo.

SSB consumption and TEI.

Wang et al. (73) compared 2 nonconsecutive 24-h dietary recalls of beverage consumption from the 2003–2004 NHANES to determine how intra-individual SSB consumption affects TEI. Each additional 8-oz. serving of SSB was associated with a net increase in intake of 106 kcal on that day (P < 0.001). This is similar to the 100 kcal found in an 8-oz serving of colas and lemon-lime sodas, suggesting no compensation. Each 1% of SSB beverage replacement with water was associated with 6.6 kcal lower TEI, which would result in an average reduction of 235 kcal among U.S. youths. Although the extent of compensation did not differ by age, they found a reduction of 172 kcal for ages 2–5 y, 183 kcal for ages 6–11 y, and 302 kcal for ages 12–19 y, all due to differences in average consumption. Although energy intake was 80–90 kcal higher in those with a BMI ≥ 85th percentile than those with a BMI < 85th percentile, the difference was not significant.

Lack of compensation is also supported by several other studies, as demonstrated in a recent meta-analysis by Vartanian et al. (4) In general, compensation appears to be no more than 50% and some studies find that SSB may lead to increased energy consumed from other foods.

Changes in energy intake and BMI.

Inferred from observed population weight changes, Hill et al. (74) found that reducing energy balance by 100 kcal “could prevent weight gain in the majority of the population.” However, Butte and Ellis (75) argued that the energy gap was higher for children, especially those overweight, due to greater energy expenditures. Studies indicate that the required energy reductions to prevent weight gain vary by age, initial weight, and physical activity levels; lower estimates of 100–140 kcal were indicated at younger ages by Plachta-Danielzik et al. (76) and Wang et al. (71), mid-range estimates of 300–500 kcal at slightly higher ages were obtained by Swinburn et al. (77) and Butte et al. (75, 78), and upper estimates of 600–1100 kcal were obtained by Wang et al. (71) for those who became overweight adolescents over 10 y. The results indicate that relatively modest behavioral modifications are required to prevent weight gain at younger ages, but larger reductions are required at higher weights and higher ages.

Discussion

The research to date provides promising results indicating that, like the effects of policies on other public health problems such as tobacco use, policies can play an important role in decreasing SSB consumption and obesity rates among youth. In MS, studies have found lower youth SSB intake in school with policies directed at reduced access to vending machines, snack bars, and á la carte. Although there is less evidence for HS, access policies and improved meal practices still hold potential to significantly reduce the amount of SSB consumed. One critical insight from several studies is that reduced SSB consumption in schools is unlikely to be offset by increased SSB consumption outside of schools.

Studies also find that higher prices reduce overall SSB consumption. Although the effect of price on youth merits further study, research indicates that price increases will influence adult as well as youth purchases and will affect purchases inside and outside of school. They may have the greatest impact on youth who are overweight or from low-income families, but additional study is warranted.

Although several long term longitudinal studies have established the role of SSB and increased BMI, and school access, nutrition, and price policies have been shown to reduce SSB consumption, the direct estimate of these policies’ effects on BMI is less conclusive. Another line of research has found that, due to the lack of offset from consuming other foods or beverages, overall energy intake appears to decline by as much as and perhaps more than the decline in energy from SSB. The reduction in energy intake from even just one 8-oz. serving of SSB appears enough to have important effects on the prevalence of overweight and obese youth if policies are started at early ages and maintained.

Suggestions for future research.

The policy studies reviewed involve data collected before recent U.S. policies to reduce SSB consumption in schools. With access to LNED foods reduced since 2005 (40), new studies will need to track SSB consumption inside and outside of schools and examine their effects.

While some studies consider more than one policy, they often do not explicitly consider how the effects of a policy may depend on the other policies in effect or how the effects vary by initial BMI, racial/ethnic group, and SES. Furthermore, the effects of policies may depend on exposure to past policies. For example, the effects of a MS program may depend on whether the child has been exposed to similar programs in ES, because those programs may have already affected their consumption habits and knowledge about nutrition. The effects of a specific policy may also vary over time. Research (79) indicates that the likelihood of being overweight depends not only on parents, but also peers, suggesting that the effects of a policy may be amplified as its effects spread through social networks. On the other hand, the effects of a policy could diminish over time if food manufacturers adapt their marketing practices to maintain sales of SSB or if individuals adapt by consuming other LNED foods.

Other policies besides those considered above, such as limits on advertising, parent-student educational polices, or nonschool mass media policies, may also be used to reduce SSB intake. Although studies indicate that advertising affects LNED consumption (80), research is needed on the population effect of advertising restrictions and public media campaigns on SSB consumption. In addition, further study is needed on how the effects of nutrition policies may be enhanced by physical activity policies.

Obesity is a complex problem, and solutions appropriate for complex problems are required. Better information is needed on how the effects of policies unfold over time as an individual ages and how changes in consumption patterns affect future dietary preferences and BMI trajectories. Empirical studies will need to use longitudinal data to consider these interrelationships over time. Alternatively, information from different studies may be combined in a modeling framework that explicitly considers the links from a policy change to reduced SSB consumption to lower BMI, as well as how policy effects may maintain or taper with age.

Because the effect of SSB has probably been studied more than other types of food and the links to BMI are relatively well understood, longitudinal studies and simulation models of the effects of SSB policies can also provide guidance to help better understand the effects of policies directed at other food types.