Literature DB >> 28376833

Impact of school policies on non-communicable disease risk factors - a systematic review.

Ankur Singh1, Shalini Bassi2, Gaurang P Nazar2, Kiran Saluja2, MinHae Park3, Sanjay Kinra3, Monika Arora4.   

Abstract

BACKGROUND: Globally, non-communicable diseases (NCDs) are identified as one of the leading causes of mortality. NCDs have several modifiable risk factors including unhealthy diet, physical inactivity, tobacco use and alcohol abuse. Schools provide ideal settings for health promotion, but the effectiveness of school policies in the reduction of risk factors for NCD is not clear. This study reviewed the literature on the impact of school policies on major NCD risk factors.
METHODS: A systematic review was conducted to identify, collate and synthesize evidence on the effectiveness of school policies on reduction of NCD risk factors. A search strategy was developed to identify the relevant studies on effectiveness of NCD policies in schools for children between the age of 6 to 18 years in Ovid Medline, EMBASE, and Web of Science. Data extraction was conducted using pre-piloted forms. Studies included in the review were assessed for methodological quality using the Effective Public Health Practice Project (EPHPP) quality assessment tool. A narrative synthesis according to the types of outcomes was conducted to present the evidence on the effectiveness of school policies.
RESULTS: Overall, 27 out of 2633 identified studies were included in the review. School policies were comparatively more effective in reducing unhealthy diet, tobacco use, physical inactivity and inflammatory biomarkers as opposed to anthropometric measures, overweight/obesity, and alcohol use. In total, for 103 outcomes independently evaluated within these studies, 48 outcomes (46%) had significant desirable changes when exposed to the school policies. Based on the quality assessment, 18 studies were categorized as weak, six as moderate and three as having strong methodological quality.
CONCLUSION: Mixed findings were observed concerning effectiveness of school policies in reducing NCD risk factors. The findings demonstrate that schools can be a good setting for initiating positive changes in reducing NCD risk factors, but more research is required with long-term follow up to study the sustainability of such changes.

Entities:  

Keywords:  NCD risk factor; Non-communicable disease; School policy; Systematic review

Mesh:

Year:  2017        PMID: 28376833      PMCID: PMC5379668          DOI: 10.1186/s12889-017-4201-3

Source DB:  PubMed          Journal:  BMC Public Health        ISSN: 1471-2458            Impact factor:   3.295


Background

Non-communicable diseases (NCDs) cause about 40 million deaths each year globally [1]. The four most important modifiable behavioral risk factors for NCDs include unhealthy diet, physical inactivity, tobacco use [2, 3] and harmful use of alcohol [4]. According to the estimates from the most recent Global Burden of Disease study, out of all the deaths due to NCDs in 2015, approximately 12 million deaths were due to unhealthy diet, 6.5 million were due to tobacco use, 1.8 million were due to alcohol and drug use and 1.6 million deaths were attributed to low physical activity [1]. The major risk factors for NCDs are associated with behavioral patterns that are largely established during childhood and adolescence and continue into adulthood [5-7]. The onset of many NCDs like diabetes, obesity, and cardiovascular diseases can be prevented or delayed by addressing these risk factors earlier in life [8]. Children and adolescents should be prioritized as target groups for behavioral interventions due to their high adaptability and likelihood to be motivated for appropriate healthy modifications [9]. In support of this, evidence shows that behavioral modifications are more successful if implemented at an early stage [10, 11]. Behavioral changes during early years require conducive policies and programs [12]. Hence, in addition to prioritizing children for the adoption of healthy behavioral practices, they should be provided with a supportive environment for behavior change in settings where children live, play and study [13]. Schools are uniquely positioned as ideal settings to model, promote and reinforce healthy behaviors among children and adolescents. Children and adolescents spend much of the daytime at school and can easily access the schools’ health-related educational programs. Therefore, schools function as health hubs by educating and imparting healthy habits among students [14, 15] as they service a large population of children and adolescents [7]. Evidence suggests that school policies can positively impact Body Mass Index (BMI) [16], physical activity and dietary behaviors [17] among children. Previous studies have mostly looked at the relationship between school policies and specific risk factors. There exists no review that has systematically identified and collated evidence on the effectiveness of school-based policy interventions collectively for the four major preventable NCD risk factors (unhealthy diet, physical inactivity, tobacco use and alcohol use). Furthermore, no systematic review has examined the impact of school policies on the anthropometric & physiological measures in children. Therefore, the aim of this systematic review was to identify, collate and synthesize the existing literature on the impact of school policies on major risk factors of NCDs.

Methods

Search strategy and study selection criteria

A review protocol was developed in accordance with PRISMA guidelines [18]. The search strategy aimed to identify published articles on the effectiveness of school level policy interventions to reduce major preventable risk factors for NCDs (unhealthy diet, physical inactivity, tobacco use, alcohol use, excess body weight, high blood pressure, adverse lipid profile as well as anthropometric and physiological measures) among students. The search was carried out in three electronic databases: Ovid Medline, EMBASE, and Web of Science. The search strategy used to identify the studies in Medline is included in Additional file 1. The databases were searched for studies published from January 1990 to January 2014. The inclusion criteria were established to include studies assessing effectiveness of either existing or new school based policy interventions among children between the age of 6 to 18 years aimed at the reduction of NCD risk factors. Studies that assessed the effectiveness of pre-school policy intervention were excluded. The detailed inclusion and exclusion criteria guiding the selection of studies for the review is described in Table 1. Duplicate references were removed using software (Endnote X7), and titles and abstracts were independently screened by two reviewers (AS and SB). Any disagreements were resolved by discussion and consultation with a third investigator (MA). Following this step, full text of the selected studies were retrieved and then reviewed for relevance to the inclusion and the exclusion criteria by AS and SB independently. Disagreements at this stage were resolved through discussion between the two reviewers.
Table 1

Inclusion and exclusion criteria

Inclusion CriteriaExclusion Criteria
PopulationChildren or adolescents between the age-group of 6 – 18 years.PopulationChildren or adolescents not in the specified age-group and studies conducted on animal models.
InterventionPolicies that modify the four identified risk factors (unhealthy diet, physical inactivity, alcohol and tobacco use) and associated health related behaviors amongst the students either alone or as part of any intervention program.InterventionPolicy components those are insufficiently described to enable replication. School policies focusing on differently abled students.
ContextSchools as a setting.ContextCommunity, pre-schools and clinical settings.
OutcomePrevalence of health related behaviors identified as risk factors for NCDs.Study designEditorials, library thesis, opinions and letters, papers with insufficient methodological details reported to allow critical appraisal of study quality, studies not in English language. Studies published before 1990.
Study DesignAny experimental or observational study design (randomized controlled trial controlled before-after study, quasi-experimental, interrupted time series, cohort study or cross-sectional study).
Inclusion and exclusion criteria

Data extraction

Two reviewers (AS and SB) independently extracted information from the selected papers using pre-piloted data extraction forms. Any disagreements were resolved either by discussion or by the intervention of another investigator (MA). The following data were extracted: study characteristics (primary author, year of publication, study setting, age group, sub-groups analysed, sample size, data collection methods, inclusion criteria, randomization information, statistical analysis); intervention or policy component, study outcomes (primary outcomes: BMI, waist circumference, overweight, obesity, physical activity, tobacco use, alcohol use, other relevant outcomes; secondary outcomes: knowledge and attitude), type of effect estimates, main result and statistical significance of differences.

Quality assessment

All the papers included in the review were independently assessed for methodological quality using the Effective Public Health Practice Project (EPHPP) quality assessment tool [19] by AS and then cross-checked by SB. The EPHPP tool contains eight different components but the scoring on quality assessment is done by six parameters. These include selection bias, study design, identification and treatment of confounders, blinding, data collection methods and withdrawals and dropouts. The components were rated strong, moderate, or weak according to a standardized guide and corresponding guidelines in the dictionary. Those with no weak ratings and at least four strong ratings were considered ‘Strong.’ Those with less than four strong ratings and one weak rating were considered ‘Moderate.’ Finally, those with two or more weak ratings were considered ‘Weak.’ The two remaining components within the quality assessment included in the assessment were the integrity of the intervention and the use of appropriate analysis [19].

Synthesis of evidence

Due to the heterogeneity in policy components of the interventions included, outcomes and effect measures, a meta-analysis was not considered appropriate. A description of effectiveness measures and a narrative review were considered appropriate to present the findings of the study.

Results

Overall, 27 studies were included in the review after the full-text screening of the identified articles through systematic database searching (n = 2633), title and abstract screening (n = 90), application of inclusion and exclusion criteria (n = 39) and full-text review (Fig. 1).
Fig. 1

Flowchart for study identification and selection process

Flowchart for study identification and selection process The majority of included studies were from high-income countries, USA (15), Australia (4), UK (2), Canada (2), Spain (1), Greece (1), combined USA and Australia (1) with the exception of only one study from India (1). There were 15 interventional studies (eight randomized controlled trials (RCTs), seven quasi-experimental studies), 11 observational studies (ten cross-sectional studies, one case-control) and one natural experiment. Five out of 27 studies were based in schools from socioeconomically deprived areas. Of the 27 studies, ten assessed the effectiveness of multiple policy interventions and 14 studies evaluated multiple outcomes (physical measures, biomarker levels and behaviors). The remaining three studies only assessed single intervention or outcome. Collectively, the children within the selected studies ranged from 6 to 17 years and were in grades from 1st to 12th. Apart from one study [20] which included only boys, remaining studies included both boys and girls. Based on the quality assessment of the selected studies, 18 were categorized as having weak methodological quality, six with moderate quality and three with strong methodological quality (Table 2; Additional file 2).
Table 2

Descriptive summary of the included studies

S/NoStudyYearCountryStudy DesignSample size (n)Participant Inclusion CriteriaPolicy/ Policy InterventionOutcome/s measuredQuality
1Anthamatten et al.2011USAObservational study; case-control n = 3688Participation in Learning Landscape Program; recent schoolyard renovation, the size of the school, and the social and demographic characteristics of the school population.Physical Activity (learning landscape program)(Renovation of school grounds)Utilization of school yards for Physical ActivityWeak
2Blum et al.2008USAQuasi-experimental n = 456 students from 7 schools;Students from grade 9-11Elimination from SSB (Diet) and other junk food in schools food policyChange in students beverage servings/dayWeak
3Covelli et al.2008USAQuasi-experimental - Repeated Measures n = 48 (Intervention = 31; control = 17)(1) be of African-American ethnicity, (2) be between 14 and 17 years old, (3) be able to read and write in English, (4) have obtained a signed parental/guardian consent form, and (5) have signed a participant assent form.Integration of health promotion in existing curriculum (Provision of cognitive behavioral components of health knowledge, health promotion concepts, nutrition, and exercise).Health promotion knowledge, behaviors related to fruit and vegetable intake and exercise; blood pressureWeak
4Evans-Whipp et al.2010USACross-sectional n = 3466 from 285 schoolsOne class per school was invited to take part in the study. Selected classes were from three-year levels: Grade 5 (age 10), Year 7 (age 12) and Year 9 (age 14).Existing School tobacco policies (Washington and Victoria) - Comprehensive smoking bans, policy orientation towards abstinence and harm minimization principles, possession of tobacco products among studentsCurrent tobacco use; daily tobacco use; students perception about school smokingModerate
5Evans-Whipp et al.2013USA and AustraliaCross-sectional n = 1848Students from grade 5,7 or 9School alcohol policies (IYDS)Current alcohol use; alcohol use in schools groundModerate
6Foster et al.2008USARCT n = 10 schools; n = 1349 studentsNot mentionedSchool self-assessment; nutrition education; nutrition policy; social marketing; and parent outreach.Sales of lower-fat à la carte foods; lower fat food choices; fruit and vegetable intake; Environmental and behavioral perceptionsStrong
7French et al.2004USARCT n = 20 schoolsPresence of an à la carte area in the school cafeteria operated by the school food service; a food service director and principal willing to take part in the study for two school years; an informed consentSchool nutrition policy initiativeBMI-SD, height, overweight, obeseWeak
8Fung et al.2013CanadaCross-sectional n = 5215(in 2003); n = 5508(in 2011)All public schools were invited to participateSchool food and nutrition policy (Children’s Lifestyle and School Performance Study-CLASS)Dietary Status, Nutrient Intake, and Weight StatusModerate
9Gibson et al.2008USARCT n = 4905 children (Intervention = 2505 and control = 2400)Not mentionedPhysical Activity Across the Curriculum(PACC) - 90 mins moderate intensity physical activity delivered as part of academic instructionPhysical activity levelWeak
10Hamilton et al.2005AustraliaRCT n = 4636 adolescents from 30 government high schoolsNot mentionedSchool-based smoking intervention(The Smoking Cessation for Youth Project-SCYP) - Curricular, parent, nurse counselling cessation support and policy componentsThe primary outcome variable was regular smoking(smoking on 4 or more days in the previous week) and the more traditional measure of ‘current smoking’ within the last 30 days was used for secondary analysesStrong
11Llargues et al.2011SpainRCT509 (Control: 237, Intervention: 272)All the children born in 2000 who attended any of the schools in Granollers were eligible to participateTeacher Training, Develop activities related to food habits and/or physical activityPrimary outcome: Difference in BMI progression Secondary outcomes: changes in eating habits and in physical activityStrong
12Knox et al.2012AustraliaQuasi-experimental182 pupils attending year (n = 115 Inter; 77 control)Not mentionedPhysical Activity - Brisk Walking LessonsAdiposity variables, BP, lipids, lipoproteins, glucose, insulin, high sensitivity C-reactive protein, high molecular weight adenopectin, aerobic fitness, physical activity behavior and dietWeak
13Jhonson et al.2009USACross-sectional n = 9151 students from 64 middle schoolsAll public schools that enroll seventh-grade students and participate in USDA school meal programs were eligible to participateSchool district SSB policiesexposure of SSB and student consumption of SSB during the school days; school district policies about SSB and exposure to SSB in schoolsModerate
14Lovato et al.2006USACross-sectional n = 522,318 students from 81 secondary schoolsNot mentionedSchool/ District tobacco control policies - scale for prohibition, strength, and characteristics of enforcement. Seven policy components: developing, overseeing and communicating the policy, purpose, and goals, prohibition, strength of enforcement, tobacco use prevention education and assistance to overcome tobacco addictions (Perception of policy)Student smokingWeak
15Manios et al.1999GreeceRCT n = 4171 students (Intervention); n = 1510 students (control)All students in the first grade of selected schoolsMulticomponent workbooks covering dietary issues, physical activity and fitness, dental health hygiene, smoking and accident preventionHealth Knowledge, Dietary, Physical Activity, Fitness, Anthropometric Measurements, Biochemical IndicesModerate
16Moore and Tapper2008UKRandomized controlled trial43 primary schoolsThe school was excluded if existing tuck shop, selling any foodFruit Truck ShopsPurchase and Intake of FruitsModerate
17Murnaghan et al.2008CanadaCross-Sectional n = 4709 grade 10 studentsNot mentionedPolicy banning smoking in school property participated in provincially directed school-based smoking prevention programOccasional and Current SmokingWeak
18O Brien et al.2010USACross-Sectional n = 80,428 students in 328 schools across the state of Maine. n = 123 intervention;205 non-intervention schoolsNot mentionedComprehensive school health education, physical education and physical activity, school nutrition and food services, health promotion and wellness, school counselling physical and behavioral health services, school climate, physical environment, youth, parent, family and community involvementBehavior change: physical activity, nutrition, and tobacco useWeak
19Paek et al.2013USACross-Sectional n = 983; 14 schoolsAll regular public schools containing grades 9, 10, 11, or 12 were included in the sampling frameTobacco-free school policyFrequency of smokingWeak
20Patel et al.2012IndiaCross-Sectional n = 172 students from 2 schoolsMale adolescents (aged 13-15 yrs.) not meeting the age criteria were excludedTobacco promotion and availability around schoolsCurrent smoking and smokeless tobacco useWeak
21Schwartz et al.2009USAQuasi- ExperimentalNot mentionedRemoval of snacks of low nutritional valueIntake of beverages, salty snacks and sweet snacksWeak
22Spence et al.2013UKNatural Experiment n = 385 [2003–4]; n = 632 [2008–9]Not mentionedNutrient-based standardsMean daily intakes of macro & micro nutrients in school lunch packed lunch and total dietWeak
23Vandongen et al.1995USACross-Sectional1147 students from 30 schoolsNot mentionedFitness, fitness + school nutrition, school-based nutrition, school + home nutrition, home-based nutritionBP, Dietary Intake, 1.6 km run and Leger shuttle run, anthropometric measurements (subscapular skinfold) BMI, percentage fatWeak
24Raczynski et al.2009AustraliaRCT n = 2202Not mentionedComprehensive legislation to combat obesityBMIWeak
25Harris et al.1997USAQuasi- Experimental n = 170Not mentionedModified school lunches, Enhanced nutrition education and increased opportunities for physical activitiesCalorie intake, Physical fitness assessment, Knowledge, skills and attitudes related to nutrition and physical fitnessWeak
26Holt et al.2013USAQuasi- ExperimentalFour elementary schools(grade k-5; 68 classroom teachers; 1284 studentsNot mentionedDistrict mandated Physical Activity Policy (20 min)The level of intensity of physical activityWeak
27Jaenke et al.2012AustraliaQuasi- Experimental n = 127 children (11-12 years)Eligibility for participation in the study was for students to be enrolled in school Grades 5 or 6.Nutrition education, gardening programFood preference assessment, fruit and vegetable intakeWeak
Descriptive summary of the included studies

Physical and anthropometric measures

Seven studies assessed the effectiveness of policy interventions or its association with changes in anthropometric measures [14, 21–26]. Three studies assessed the effectiveness of school policy in controlling blood pressure [22, 26, 27]. The policy interventions targeted at anthropometric measurements (BMI, waist circumference, height and weight status) included school nutrition policy initiative [14, 21], comprehensive legislation at state level to combat obesity [25], brisk walking lessons [22], teacher trainings, developing activities related to food habits and/or physical activity [23], fitness guidance, fitness and school nutrition, school-based nutrition, school and home nutrition and home-based nutrition [26]; multicomponent workbooks covering dietary issues, physical activity and fitness [24] and integration of health promotion in the existing curriculum [27] (Table 3).
Table 3

Effectiveness of policies on physical, anthropometric measurements and biomarkers

StudyDesignPolicyOutcomesSpecific outcomeImpact (+) Favorable and significant change (=) No changeStrength of Association
Physical and Anthropometric measurements
Foster et al., 2008 [14]RCTSchool self-assessment; nutrition education; nutrition policy; social marketing; and parent outreach.BMI, Overweight, ObesityBMI=Control (Baseline: 20.76 kg/m2; Follow up: 23.06 kg/m2) Intervention (Baseline 21.07 kg/m2; Follow up 23.06 kg/m2) p-value 0.71
Overweight (BMI for age from the 85th to 94.9th percentile)+Adjusted Odds for Incidence:- 0.67 (0.47–0.96)
Obesity (BMI for age _95th percentile)=Adjusted Odds for Incidence:- 1.00 (0.66–1.52)
Fung et al., 2013 [21]Cross-sectionalSchool based nutrition policyOverweight and Obesity (BMI measurements)Overweight=Overweight (Prevalence ratio, adjusted change: 1.03 (0.94, 1.12)
Obesity+Obesity (Prevalence ratio, adjusted change: 1.26 (1.08, 1.48))
Knox et al., 2012 [22]Quasi-experimentalBrisk walking lessonsWaist circumference, Systolic Blood PressureWaist circumference+Prevalence of elevated waist circumference: Control:- 9.8% Intervention:- 6.9
Systolic Blood pressure+Prevalence of elevated BP: Control:- 3.3% Intervention:- 0%
Llargues et al., 2011 [23]RCTTeacher trainings, Activities around food habits and physical activityBMI progression after two yearsBMI+Control (Baseline: 16.5 kg/m2 (16.7 kg/m2 to 17.5 kg/m2) Follow up: 18.3 kg/m2 (17.9 kg/m2 to 18.7 kg/m2)) Intervention (Baseline: 17.1 kg/m2 (16.7 kg/m2 to 17.5 kg/m2) Follow up: 17.9 kg/m2 (17.4 kg/m2to 18.4 kg/m2)
Manios et al., 1999 [24]RCTMulti-component workbooks – National policy for health educationBMI ProgressionBMI+Control (Baseline: 24.4 kg/m2 Follow up: 32.8 kg/m2) Intervention (Baseline: 16.2 kg/m2 Follow up: 16.3 kg/m2) p = 0.001
Raczynski et al., 2009 [25]RCTComprehensive legislationBMIBMI=Mean BMI: (Baseline: 28.8 kg/m2; 1 year follow up: 23.2 kg/m2; 2 year follow up: 25.7 kg/m2; 3 year follow up: 26.9 kg/m2) p value non-significant.
Vandongen et al., 1995 [26]Cross SectionalGuidance around fitness and nutrition (Fitness, Fitness + School Nutrition, School nutrition, School and home nutrition, home nutrition, All groups together)BMI, Systolic blood pressure, Percentage body fat, Triceps skinfold, Subscapular skinfoldBMI=Means:BMI (Intervention Baseline: 18.0 kg/m2 (95% CI 17.8 kg/m2, 18.3 kg/m2) Follow up: 18.5 kg/m2 (18.0 kg/m2, 18.5 kg/m2) Control Baseline: 17.6 kg/m2 (16.9 kg/m2, 18.3 kg/m2) Follow up: 18.2 kg/m2 (17.4 kg/m2, 18.9 kg/m2)
Systolic blood pressure=Systolic blood pressure(Intervention Baseline: 104.8 mm/Hg (104.0 mm/Hg, 105.9 mm/Hg) Follow up: 102.2 mm/Hg (101.4 mm/Hg, 104.9 mm/Hg) Control Baseline: 105.9 mm/Hg (104.1 mm/Hg, 107.7 mm/Hg) Follow up: 103.1 mm/Hg (101.3 mm/Hg, 106.5 mm/Hg)
Percentage body fat=Percentage body fat (Intervention Baseline: 22.4% (21.9%, 23.0%) Follow up: 23.1% (22.5%, 23.7%) Control Baseline: 21.2% (19.6%, 22.8%) Follow up: 21.9%(20.3%, 23.6%)
Triceps skinfold+Triceps skinfold (Intervention Baseline: 14.5 mm (14.0 mm, 14.9 mm) Follow up: 15.1 mm (14.5 mm, 15.6 mm) Control Baseline: 13.0 mm (11.9 mm, 14.1 mm) Follow up: 14.2 mm (12.6 mm, 15.7 mm))
Subscapular skinfold=Subscapular skinfold (Intervention Baseline: 10.3 mm (9.8 mm, 10.8 mm) Follow up: 11.1 mm (10.5 mm, 11.6 mm) Control Baseline: 10.2 mm (8.7 mm, 10.8 mm) Follow up: 10.7 mm(9.1 mm, 12.2 mm))
Covelli, 2008 [27]Quasi-experimental - Repeated MeasuresIntegration of health promotion into curriculumMaintenance of blood pressureBlood pressure=SBP: Intervention (Baseline 119.7 mm/Hg Follow up 116.2 mm/Hg) Control (Baseline 119.2 mm/Hg Follow up 119.1 mm/Hg; p = 0.56)
DBP: Intervention (Baseline 66.2 mm/Hg Follow up 67.2 mm/Hg) Control (Baseline 66.8 mm/Hg Follow up 68.0 mm/Hg; p = 0.97)
Biomarkers
Knox et al., 2012 [22]Quasi-experimentalBrisk walking lessonsBlood levels of triglycerides, high density lipoprotein cholesterol, high density lipoprotein: total cholesterol, glucoseTriglycerides+Elevated Triglycerides (Control: - 2.5%; Intervention:-1.2%)
High density lipoprotein cholesterol+Elevated high density lipoprotein cholesterol(Control: - 3. 7% vs. Intervention:-1.2%2.7%)
High density lipoprotein: total cholesterol+High density lipoprotein cholesterol to total cholesterol ratio (mean + − SD: 2% ± 4% [confidence interval(CI)o.o5 = 1% to 2%>], t80 = −3.5, p = .001)
Glucose+Glucose (−.1 ± .4 mmol/L p = .002)
Manios et al., 1999 [24]RCTMulti-component workbooks – National policy for health educationSerum level lipid changesTotal Serum Cholesterol+Intervention (Baseline 187.4 mg/dl Follow up 173.7 mg/dl) Control (Baseline 177.3 mg/dl Follow up 190.6 mg/dl; p = 0.001)
Effectiveness of policies on physical, anthropometric measurements and biomarkers Mixed results were reported for the effects of school policies on BMI. Non-significant differences or associations with BMI for policy interventions were reported by three studies [14, 25, 26]; while two studies reported significantly lower progression of BMI among those exposed to policy interventions compared to those who did not [23, 24]. The studies that showed policies to be effective in reduction of BMI were assessed to have moderate and strong methodological quality. These effective policy interventions included teacher training, developing activities related to food habits and/or physical activity, multicomponent workbooks covering dietary issues, physical activity, and fitness. Decreased levels of elevated waist circumference as a result of brisk walking lessons was reported in one of the studies [22]; however, this study scored weak in quality assessment. Studies where case definitions included overweight and obesity also showed mixed results. While policy intervention of school nutrition policy initiative was effective in reduction of overweight in one study [14], an increase in the prevalence of both overweight and obesity was observed in another [21]. Though, the study showing effectiveness of school nutrition policy initiative had strong methodological quality. Two studies that assessed the effectiveness of policies including brisk walking lessons and fitness guidance, fitness and school nutrition, school-based nutrition, school and home nutrition and home-based nutrition in BP control showed desirable effects [22, 26]. On the other hand, one assessing the effectiveness of integration of health promotion in the existing curriculum reported non-significant changes [27] (Table 3). However, the three studies were judged to be of weak methodological quality.

Biomarkers

Two out of the 27 studies assessed changes in biomarker levels [22, 24]. One study [22] assessed whether extended brisk walking lessons as a school level intervention resulted in changes in serum levels of triglycerides, high-density lipoprotein cholesterol, high-density lipoprotein to total cholesterol ratio and glucose. They reported significantly lower levels of triglycerides, improvements in high-density lipoprotein cholesterol, high-density lipoprotein to total cholesterol ratio and reduction in glucose levels to be associated with the intervention. Similarly, desirable serum level lipid changes were reported by Manios et al. [26], in their study on the effectiveness of multicomponent workbooks covering dietary issues, physical activity and fitness, dental health hygiene, smoking and accident prevention as school level policies. Additionally, teaching aids including posters, audio-taped fairy tales for classroom use, workbooks, and teaching manuals were provided to class teachers and physical education (PE) instructors (Table 3). The studies were judged to have weak to moderate methodological quality.

Unhealthy diet

The majority of selected studies (n = 15) assessed the effectiveness of policy interventions in changing unhealthy dietary behaviors. These policies ranged from removal of sugar-sweetened beverages (SSBs) and junk food [28-30]; change in canteen policies (increasing the availability of lower-fat foods in cafeteria’s à la carte areas and implementing school-wide, student-based promotions of these lower-fat foods) [31]; school self-assessment; nutrition education; nutrition policy (meet nutritional standards based on Dietary Guidelines for Americans); social marketing; and parent outreach [14]; fruit truck shops [32]; nutrition education and gardening program [33]; brisk walking lessons [22]; integration of health promotion in curriculum [27]; teacher trainings and development of activities related to food habits and/or physical activity [23]; fitness guidance, fitness and school nutrition, school-based nutrition, school and home nutrition and home-based nutrition [26]; modified school lunches, enhanced nutrition education and increased opportunities for physical activities [34]; comprehensive school health education, physical education and physical activity, school nutrition and food services, health promotion and wellness, school counselling, physical and behavioral health services, school climate, physical environment, youth, parent, family and community involvement [35]. Six out of seven studies assessing policy effectiveness in reduction of sugar intake reported desirable changes and reduction in sugar or SSBs consumption [21, 26, 28, 29, 35, 36]. These effective policies included elimination of SSB and other junk food in schools’ food policy, having a school food and nutrition policy in place, school district SSB policies, school nutrition and food services, nutrition-based standards and fitness guidance, fitness and school nutrition, school-based nutrition, school and home nutrition and home-based nutrition. Among these policy interventions, studies with moderate methodological quality evaluated school food and nutrition policy and school district SSB policies, while the remaining studies were judged to have weak methodological quality. School policies were also observed to be effective in increasing fruit and vegetable intakes in four out of five studies [23, 27, 31–33]. Desirable effects of increased fruit and vegetable intakes were noted with the policy interventions of integration of health promotion in the curriculum, change in canteen policies, nutrition education and gardening program, teacher training and development of activities related to food habits and/or physical activity and fruit truck shops. Out of these effective interventions, teacher training and development of activities related to food habits and/or physical activity and fruit truck shops were observed to be reported from studies with moderate and strong methodological quality. Regarding fat reduction and salty snacks, school dietary policies were reported to reduce their prevalence [26, 30, 36] (Table 4). All the three studies were judged to have weak methodological quality.
Table 4

Effectiveness of policies on dietary behaviors

StudyDesignPolicyOutcomesSpecific outcomeImpact (+) Favorable and significant change(=) No changeStrength of Association
Blum et al., 2008 [28]Quasi-experimentalElimination from SSB (Diet) and other junk food in schools food policySugar-sweetened beverages consumptionSSB=Consumption of SSB decreased in both intervention and control boys (F = 53.69, P < .05) and girls (F = 22.87, P < .05). Intervention girls decreased diet soda consumption as compared to control girls (F = 6.57, P < .05)
Diet soda=
Juice=
Johnson et al., 2009 [29]Cross-sectionalSchool district SSB policiesSugar-sweetened beverages consumptionSSBs+β = − 9.50, p < .0002
Schwartz et al., 2009 [30]Quasi- ExperimentalRemoval of snacks of low nutritional valueConsumption of beverages, salty snack, and sweet snackBeverages+β = −.23, p < .05
Salty snack+β = −.30, p < .05
Sweet snack=Not reported
French et al., 2004 [31]RCTSchool nutrition policy initiative: Food availability in à la carte areas; Peer promotionsLower-fat food choices, Added fats score, Fruit and vegetable scoreLower-fat food choices=% Yes: Intervention (Baseline 0.29 First year 0.28 Second year 0.28) Control (Baseline 0.23 First year 0.26 Second year 0.24; p = 0.62)
Added fats score=% Yes: Intervention (Baseline 2.5 First year 2.6 Second year 2.4) Control (Baseline 2.6 First year 2.7 Second year 2.5; p = 0.97)
Fruit and vegetable score=% Yes: Intervention (Baseline 2.7 First year 2.9 Second year 2.9) Control (Baseline 2.8 First year 3.1 Second year 3.1; p = 0.95)
Foster et al., 2008 [14]RCTSchool self-assessment; nutrition education; nutrition policy; social marketing; and parent outreach.Total energy consumed (kilo- joules), fat consumption (grams), and the number of fruit and vegetable servingsEnergy=Adjusted difference:−104.27 (−234.28, 25.73) p = 0.12
Fat consumption=Adjusted difference:−3.78 (−8.59, 1.02) p = 0.12
Fruit and vegetable servings=Adjusted difference:−0.04 (−0.37, 0.3) p = 0.82
Fung et al., 2013 [21]Cross-sectionalSchool food and nutrition policy (Children’s Lifestyle and School Performance Study-CLASS)Fruit/vegetable, grain products, milk products, meat and alternatives, soda intake, SSBs,Fruit/vegetable=β = −0.08 (−0.27, 0.19)
Grain products+β = 0.26 (0.17, 0.34)
Milk products+β = 0.24 (0.18, 0.31)
Meat and alternatives+β = 0.06 (0.03, 0.09)
Soda intake+β = −0.09 (−0.11, −0.06)
SSBs+β = −0.20 (−0.27, −0.12)
Moore and Tapper, 2008 [32]RCTFruit Truck ShopsConsumption of fruit and sweet and savoury snacksFruits=β = 0.06 (−0.1, −0.21)
Sweets, Chocolates, Biscuits=β = −0.1 (−0.3, 0.01)
Crisps=β = −0.05 (−0.2, 0.06)
Jaenke et al., 2012 [33]Quasi- ExperimentalNutrition education, gardening programFruit and vegetable intakeFruits= P = 0.93
Vegetables+ P = 0.67
Knox et al., 2012 [22]RCTBrisk Walking LessonsConsumption of total fat, saturated fat, carbohydrates, proteins, fiber, and total caloriesConsumption of total fat, saturated fat, carbohydrates, proteins, fiber, and total calories=Non-significant changes, effect, estimates not reported
Covelli, 2008 [27]Quasi-experimental - Repeated MeasuresIntegration of health promotion in existing curriculum (Provision of cognitive behavioral components of health knowledge, health promotion concepts, nutrition, and exercise).Fruits/vegetables per dayFruits/vegetables per day+Fruits/vegetables per week: Intervention (Baseline 2.6 Follow up 4.9) Control (Baseline 2.7 Follow up 2.5; p = 0.0001)
Llargues et al., 2011 [23]RCTTeacher Training, Develop activities related to food habits and/or physical activityFruits, vegetables, SSBs, Sweets, Fizzy drinksFruits=No changes: Intervention 84.2% (p = 0.36) Control 80.0% (0.18)
Vegetables=No changes: Intervention 73.1% (p = 0.58) Control 81.4% (0.84)
Sweets=No changes: Intervention 93.7% (p = 1.0) Control 94.3% (0.7)
Fizzy drinks=No changes: Intervention 87.9% (p = 1.0) Control 89.2% (0.12)
Vandongen et al., 1995 [26]Cross-SectionalGuidance around fitness and nutrition (Fitness, Fitness + School Nutrition, School Nutrition, School and home nutrition, home nutrition, All groups togetherFat, sugar and proteinFatBoys =Girls +Fat % energy (Intervention Baseline: 33.1 (32.7, 33.7) Follow up: 33.7 (33.1, 34.3) Control Baseline: 33.2 (32.7, 33.7) Follow up: 33.2 (31.5, 34.9)
SugarBoys + Girls =Sugar % energy (Intervention Baseline: 22.8 (22.1, 23.5) Follow up: 21.9 (21.2, 22.7) Control Baseline: 21.7 (20.0, 23.3) Follow up: 23.3 (21.4, 25.3)
ProteinBoys + Girls +Protein (% energy) Intervention Baseline: 15.5 (15.3, 15.8) Follow up: 15.6 (15.2, 15.9) Control Baseline: 15.8 (15.1, 16.4) Follow up: 14.7 (13.9, 15.4)
Harris et al., 1997 [34]Quasi- ExperimentalModified school lunches, Enhanced nutrition education and increased opportunities for physical activitiesKnowledge and awareness regarding nutritionAwareness levels+(t [33] = −6.64, p < .0001)
O’Brien et al., 2010 [35]Cross-SectionalComprehensive school health education, physical education and physical activity, school nutrition and food services, health promotion and wellness, school counselling physical and behavioral health services, school climate, physical environment, youth, parent, family and community involvementSSB consumptionTwo or more sodas/week+OR: 0.83 (p = .023)
Spence et al., 2013 [36]Natural ExperimentNutrient-based standardsNon-milk extrinsic sugar% energy NMES=Mean difference: −2.6 (−3.2, −1.9) (p < 0.001)
Effectiveness of policies on dietary behaviors

Tobacco and alcohol use

Seven out of 27 studies assessed the effects of school tobacco control policies on the prevalence of tobacco use [20, 35, 37–41]. These school level tobacco control policies included comprehensive smoking bans, policy orientation towards abstinence and harm minimization principles, penalty on possession of tobacco products among students [37]; school-based smoking intervention: curriculum, parent, nurse counselling cessation support and policy components such as scale for prohibition, strength and characteristics of enforcement [38]. One study assessed seven policy components: developing, overseeing and communicating the policy, purpose, and goals, prohibition, the strength of enforcement, tobacco use prevention education and assistance to overcome tobacco addictions (perceptions regarding policy) [39]. Others assessed a policy banning smoking in school property [40], tobacco-free school policy [41], reduced tobacco promotion and availability around schools [20] and finally comprehensive school health education, school counselling, physical and behavioral health services, school climate, physical environment, youth, parent, family and community involvement [35] (Table 5).
Table 5

Effectiveness of policies on substance misuse (tobacco and alcohol use)

StudyDesignPolicyOutcomesSpecific outcomeImpact(+) Favorable and significant change(=) No changeStrength of Association
Tobacco use
Evans-Whipp et al., 2010 [37]Cross-sectionalComprehensive smoking bans, policy orientation towards abstinence and harm minimization principles, possession of tobacco products among studentsCurrent tobacco use, Daily smoking, Perception of smoking in school campusSmoking ban – current smoking=OR (95% CI): 0.86 (0.59, 1.25)
Harm minimization – current smoking=OR (95% CI): 1.09 (0.99, 1.21)
Strict enforcement – current smoking=OR (95% CI): 0.78 (0.57, 1.05)
Smoking ban – daily smoking=OR (95% CI): 0.95 (0.53, 1.69)
Harm minimization – daily smoking=OR (95% CI): 1.01 (0.85, 1.20)
Strict enforcement – daily smoking=OR (95% CI): 0.70 (0.44, 1.12)
Smoking ban – perception=OR (95% CI): 1.39 (0.67, 2.89)
Harm minimization – perception=OR (95% CI): 1.18 (0.97, 1.43)
Strict enforcement – perception+OR (95% CI): 0.45 (0.25, 0.82)
Hamilton et al., 2005 [38]RCTSchool-based harm minimization smoking interventionRegular smoking, smoking within previous monthRegular smoking+Intervention vs comparison OR (95% CI): Baseline 0.74 (0.45, 1.22) Post-intervention: 0.50 (0.33, 0.74)
Smoking within previous month+Intervention vs comparison OR (95% CI): Baseline 0 0.95 (0.71, 1.28) Post-intervention: 0.69 (0.53, 0.91)
Lovato et al., 2007 [39]Cross sectionalSchool/ District tobacco control policies – policy intention (written policy), policy implementation, perception of policy enforcementPrevalence of smokingPolicy intention – smoking prevalence+β = −0.11 (R2 = 0.27) (P < 0.05)
Policy implementation – smoking prevalence+β = −0.04 (R2 = 0.21) (P < 0.05)
Policy perception – smoking prevalence+β = −0.55 (R2 = 0.62) (P < 0.05)
Murnaghan et al., 2008 [40]Cross-sectionalPolicy banning smoking in school property participated in provincially directed school-based smoking prevention programCurrent smoking, Occasional smoking and Regular smokingOccasional vs nonsmoker=OR (95% CI): 1.54 (0.79, 3.01)
Regular vs occasional smoker=OR (95% CI): 0.92 (0.69, 1.23)
O’Brien et al., 2010 [35]Cross-SectionalTobacco control school-based policy – Teacher shared information of consequences of smokingFrequency of smoking in past monthAverage cigarettes smoked/day=Not reported
Paek et al., 2013 [41]Cross-sectionalTobacco-free school policyFrequency of smokingFrequency of smoking+β = −0.56 (P < 0.05)
Patel et al., 2012 [20]Cross-sectionalAvoiding tobacco promotionTobacco useTobacco use+ P < 0.05
Alcohol use
Evans-Whipp et al., 2013 [42]Cross-sectionalLow policy enforcement, Abstinence alcohol message, Harm minimization alcohol messageAlcohol use: alcohol use on school grounds, current alcohol use. Binge drinking, student alcohol harmLow policy enforcement - Use on school grounds+OR (95% CI): 1.48 (1.07, 2.05)
Low policy enforcement - Current alcohol use=OR (95% CI): 1.12 (0.95, 1.32)
Low policy enforcement - Binge drinking=OR (95% CI): 1.14 (0.94, 1.38)
Low policy enforcement - Student alcohol harm=OR (95% CI): 1.02 (0.84, 1.25)
Abstinence alcohol message - Use on school grounds=OR (95% CI): 0.85 (0.66, 1.10)
Abstinence alcohol message - Current alcohol use=OR (95% CI): 0.90 (0.78, 1.04)
Abstinence alcohol message - Binge drinking=OR (95% CI): 0.84 (0.59, 1.25)
Abstinence alcohol message - Student alcohol harm=OR (95% CI): 0.86 (0.71, 1.04)
Harm minimization alcohol message - Use on school grounds=OR (95% CI): 0.90 (0.73, 1.10)
Harm minimization alcohol message - Current alcohol use=OR (95% CI): 0.92 (0.83, 1.02)
Harm minimization alcohol message - Binge drinking=OR (95% CI): 0.82 (0.72, 1.92)
Harm minimization alcohol message - Student alcohol harm+OR (95% CI): 0.83 (0.71, 0.96)
Effectiveness of policies on substance misuse (tobacco and alcohol use) Current smoking was the preferred outcome of evaluation for tobacco use among four out of seven studies [20, 37, 38, 40] and smokeless tobacco use was measured as an outcome in only one of the seven studies [20]. Several other outcomes such as frequency of tobacco use, perception about school smoking and occasional smoking were also assessed in some of the included studies. Two studies reported non-significant differences between those exposed and not exposed to policy [35, 37] while five studies reported a significant reduction in tobacco use among those exposed [20, 38–41]. Among the effective interventions, only school based harm minimization smoking intervention was observed to be tested within a study with strong methodological quality. The remaining four studies scored weak in quality assessment. Only one study tested the association between school-level policies and alcohol use and reported that when the students believed the policy enforcement was not strict, the chances of students consuming alcohol on school grounds were higher [42] (Table 5). This study was judged to have moderate methodological quality.

Physical inactivity

Among the 27 studies, ten assessed associations between school policies and changes in physical activity [22–24, 26, 27, 34, 35, 43–45]. The school policies included learning landscape program (renovation of school grounds) [43]; 90 min moderate intensity physical activity delivered as part of academic instruction [44]; lessons on brisk walking [22]; district mandated physical activity policy (20 min per day) [45]; integration of health promotion in existing curriculum (provision of cognitive behavioral components of health knowledge, health promotion concepts, nutrition and exercise) [27]; teacher trainings, developing activities related to food habits and/or physical activity [23]; fitness trainings [26]; increased opportunities for physical activities (installing physical fitness stations in each classroom; initiating a non-competitive incentive system based on students’ personal goals; training of PE teachers and lesson plans for PE teachers) [34]; comprehensive school health education, including physical education and physical activity, school nutrition and food services, health promotion and wellness, school counselling, physical and behavioral health services, school climate, physical environment, youth, parent, family and community involvement [35]; multicomponent workbooks covering dietary issues, physical activity and fitness, dental health hygiene, smoking and accident prevention [24]. All studies reported significant and positive changes in physical activity with the implementation of school policies except one [34] (Table 6). However, majority of these studies were of weak methodological quality and policies that were observed to be effective from moderate and strong methodological studies included teacher trainings, developing activities related to food habits and/or physical activity; and, multicomponent workbooks covering dietary issues, physical activity and fitness, dental health hygiene, smoking and accident prevention.
Table 6

Effectiveness of policies on physical inactivity

StudyDesignPolicyOutcomesSpecific outcomeImpact(+) Favorable and significant change(=) No changeStrength of Association
Anthamatten et al., 2011 [43]Case-controlPhysical Activity (learning landscape program) (Renovation of school grounds)Utilization of school yards for Physical ActivityOverall utilization of school yards+Mean difference: 7.0 p = 0.003
Covelli, 2008 [27]Quasi-experimentalIntegration of health promotion in existing curriculum (Provision of cognitive behavioral components of health knowledge, health promotion concepts, nutrition, and exercise).ExerciseExercise per week+Intervention group: Mean Baseline (2.6 (SE:0.9) Follow up 4.5 (SE: 1.4))
Control group: Mean Baseline (2.1 (SE(0.8) Follow up 2.2 (SE 0.1)) p = 0.001
Gibson et al., 2008 [44]RCTPhysical Activity Across the Curriculum (PACC) - 90 mins moderate intensity physical activity delivered as part of academic instructionPhysical activityLevels of physical activity+Intervention students 3.40 ± 0.02 vs control students 2.17 ± 0.03, p < 0.0001
Harris et al., 1997 [34]Quasi-experimentalModified school lunches, Enhanced nutrition education and increased opportunities for physical activitiesPhysical activityFitness levels=Pretest (18%) to post-test (29%) (p = 0.29)
Holt et al., 2013 [45]Quasi-experimentalDistrict mandated Physical Activity Policy (20 min)Physical activity: Walk/run, Movement activityWalk/run+Not reported
Movement=Not reported
Llargues et al., 2011 [23]RCTTeacher Training, Develop activities related to food habits and/or physical activityPhysical activityWalking to school+No changes: Control 83% Intervention: 73.4% p < 0.05
Exercise+No changes: Control 74.2% Intervention: 76.4% p < 0.05
Manios et al., 1999 [24]RCTMulticomponent workbooks covering dietary issues, physical activity and fitness, dental health hygiene, smoking and accident preventionLeisure time physical activityLeisure-time MVPA+Intervention (Baseline 0.9) (Follow up 2.8) Control (Baseline 1.4) (Follow up 2.0)
O’Brien et al., 2010 [35]Cross-sectionalComprehensive school health education, physical education and physical activity, school nutrition and food services, health promotion and wellness, school counselling physical and behavioral health services, school climate, physical environment, youth, parent, family and community involvementPhysical activityTV viewing >2 h/day+Odds ratio: 0.95 p = 0.28
Vandongen et al., 1995 [26]Cross-sectionalFitness, fitness + school nutrition, school based nutrition, school + home nutrition, home based nutritionFitnessLeger score+Means: Leger score (Intervention Baseline: 43.2 (41.9, 44.4) Follow up: 44.7 (43.2, 46.2) Control Baseline: 42.2 (38.6, 45.7) Follow up: 41.0 (37.2, 44.9)
Run time (minutes)+Means:Run time (Intervention Baseline: 9.9 (9.8, 10.1) Follow up: 9.6 (9.4, 9.8) Control Baseline: 10.4 (9.9, 10.7) Follow up: 9.9 (9.4, 10.4)
Effectiveness of policies on physical inactivity

Policy effectiveness

In total, for 103 outcomes independently evaluated within these studies, 47 outcomes (46%) had significant desirable changes when exposed to the school policies. In terms of the frequency, these interventions included: school self-assessment (n = 1); nutrition education (n = 5); nutrition policy (n = 9); social marketing and parent outreach (n = 1); health education (n = 5); extended brisk walking lessons (n = 6); teacher trainings (n = 3); guidance around fitness or fitness training (n = 4); school district SSB policies (n = 1); integration of health promotion in curriculum (n = 2); creating opportunities for physical activity (n = 1); smoking bans, policy orientation towards abstinence and penalty on possession of tobacco (n = 1); school-based harm minimization intervention (n = 2); district or school-based tobacco control policies (n = 3); tobacco free school policy (n = 1); alcohol abstinence and harm minimization messages (n = 2); investment on school infrastructure to promote physical activity (n = 2); physical activity in curriculum (n = 1); district mandated physical activity policy (n = 1). However, the policy interventions observed to be effective after restricting the evidence from studies having strong and moderate methodological quality were fewer in numbers. These included teacher trainings, activities related to food habits and physical activity, and multicomponent workbooks for desirable outcomes on anthropometric measurements, and biomarkers. For the outcome of change in dietary behaviors, evidence was supportive for school district SSB policies, school food and nutrition policy. Evidence from strong and moderate methodological quality studies showed that school based harm minimization smoking intervention was effective for reduction of smoking, and low policy enforcement for alcohol use for the desirable outcome of reduced alcohol intake. Finally, for desirable changes in physical activity; the teacher trainings, developing activities related to food habits and/or physical activity; and, multicomponent workbooks were reported to be effective.

Discussion

The current study systematically reviewed the evidence on the effectiveness of school policies in the reduction of risk factors for NCDs. Although the overall evidence indicates effectiveness of policies on behavioural outcomes and biomarkers, majority of these studies were judged to have weak to moderate methodological quality. Compared to these outcomes, school policies were evident to be less effective for the outcomes such as anthropometric measurements, overweight and obesity, and, alcohol use. None of the included studies reported long-term follow-up of participants. Therefore, it is not known whether beneficial changes in NCD risk factors resulting from school policy interventions are sustained in the longer term. The NCD risk factors evaluated within the selected studies ranged from individual health behaviors to anthropometric measurements and biomarkers. The observed differences in the effectiveness of the policies according to these different types of outcomes may reflect the lag time between exposure to the intervention and effect on the outcome (NCD risk factor). For example, behavioral changes such as reduced sugar intake may be immediate following an intervention, but behaviors need to be sustained over a longer period to produce changes in anthropometric measures. These differences can also be due to the variations in the number of studies reporting these outcomes. While most selected studies tested the effectiveness of school policies on health behaviors (diet, smoking and physical activity) and anthropometric measurements, fewer studies tested associations between the school policies and biomarkers as well as between school policies and alcohol use. High sugar consumption is associated with multiple NCDs including overweight/ obesity [46], diabetes [47] and dental caries [48]. The effective policy interventions targeted at the school level to reduce sugar consumption among school children were to have a school nutrition policy restricting SSBs. These findings are consistent with those reported in independent reviews on determinants of high sugar intake [49, 50]. Tobacco use is a well-established independent risk factor for NCDs and the most prevalent behavioral risk factor globally [51]. The most efficient school policy interventions included school-based harm minimization smoking intervention. These findings further substantiate the results on the positive influence of school environment on tobacco abstinence among children [52, 53]. Physical inactivity or sedentary behavior is also associated with worse health outcomes [54-56]. Teacher trainings, developing activities related to food habits and/or physical activity and, multicomponent workbooks were reported to be effective in increasing physical activity among school children from methodologically stronger studies. Another systematic review on school policy interventions and NCD risk factors reported the majority of the school policy interventions being effective [57]. This systematic review had several strengths and some limitations. A previous systematic review on the effectiveness of school policies was limited to the outcomes like physical inactivity, diet, and tobacco consumption [57] while the current review also included anthropometric measures, alcohol use, and biomarkers. Furthermore, the current systematic review included different study designs. Evidence suggests that RCTs are inappropriate for evaluating most health promotion interventions [58]. Thus, being inclusive of studies regardless of study designs allowed to present more comprehensive evidence on school policies. The review also had some limitations. First, the review was limited to English-language articles, which may have led to the exclusion of some relevant studies in other languages. Second, the review did not include grey literature including government reports due to lack of access. However, governments are likely to evaluate context specific school policy interventions which are less likely to be generalized to different contexts. Third, a meta-analysis of the evidence could not be conducted due to the heterogeneity among the policy components of the interventions included and the lack of uniformity in outcomes and effect measures. Finally, the evidence can only be summarized for the direction of association rather than its strength due to multiple heterogeneities within studies in terms of exposure, outcomes, and the effect estimates.

Research and policy implications

The findings from the current review have important research and policy implications. The mixed evidence on the effectiveness of school policies according to different outcomes indicates that when planning intervention studies, the time lag between any policy exposure and the outcomes of interest should be considered carefully. Another important consideration is the duration of follow-up within studies; studies with longer-term follow-up of students are needed to assess whether positive changes in NCD risks are maintained beyond the intervention period and school years. Some of the school based policy interventions are expensive to design and resource intensive to carry out. The lack of good quality evidence on the effectiveness of school based policy interventions highlights the need for well-designed studies to inform the policymakers. Finally, all except one study were from high-income countries, which underscores the gap in research evidence from low- and middle-income countries. Global estimates indicate that 80% of the deaths due to NCDs occurs within low- and middle-income countries [59]. Thus more research on the effectiveness of school policies in the reduction of NCDs and their risk factors should also be conducted within these countries. In most societies, NCDs are unequally distributed [60] and a shift in policy attention from individual to environmental and structural factors, such as the school environment, could be a more equitable approach [61]. The evidence from this systematic review will be used as a wider framework to aid in developing a contextually relevant and tailored comprehensive NCD intervention model for schools. It will also guide the drafting of an evidence-based global school policies checklist for promoting a healthy lifestyle and preventing NCDs. The school checklist will inform policy-makers on aligning school curriculum, school activities and school health services, food availability and school infrastructure to be conducive for NCD prevention.

Conclusions

Mixed findings were observed concerning effectiveness of school policies in reducing risk factors of NCD. More good quality evidence is required to conclude on the effectiveness of school level policies in reduction of NCD risk factors. Additionally, further research is required to assess whether healthy changes are sustained over long-term to reduce NCD risk in later life. Search strategy for Ovid Medline. (DOCX 34 kb) Quality assessment of the selected studies. (DOCX 39 kb)
  55 in total

Review 1.  Environmental influences on eating and physical activity.

Authors:  S A French; M Story; R W Jeffery
Journal:  Annu Rev Public Health       Date:  2001       Impact factor: 21.981

Review 2.  A life course approach to diet, nutrition and the prevention of chronic diseases.

Authors:  I Darnton-Hill; C Nishida; W P T James
Journal:  Public Health Nutr       Date:  2004-02       Impact factor: 4.022

Review 3.  Reducing obesity and related chronic disease risk in children and youth: a synthesis of evidence with 'best practice' recommendations.

Authors:  M A T Flynn; D A McNeil; B Maloff; D Mutasingwa; M Wu; C Ford; S C Tough
Journal:  Obes Rev       Date:  2006-02       Impact factor: 9.213

4.  Impact of school district sugar-sweetened beverage policies on student beverage exposure and consumption in middle schools.

Authors:  Donna B Johnson; Barbara Bruemmer; Anne E Lund; Carina C Evens; Corinne M Mar
Journal:  J Adolesc Health       Date:  2009-06-04       Impact factor: 5.012

Review 5.  A new understanding of the relationship between sugars, dental caries and fluoride use: implications for limits on sugars consumption.

Authors:  Aubrey Sheiham; W Philip T James
Journal:  Public Health Nutr       Date:  2014-06-03       Impact factor: 4.022

6.  Assessment of a school-based intervention in eating habits and physical activity in school children: the AVall study.

Authors:  Esteve Llargues; Rosa Franco; Assumpta Recasens; Ana Nadal; Maria Vila; Maria José Pérez; Josep Maria Manresa; Isabel Recasens; Gemma Salvador; Jaume Serra; Eulàlia Roure; Conxa Castells
Journal:  J Epidemiol Community Health       Date:  2011-03-12       Impact factor: 3.710

Review 7.  Are interventions to promote healthy eating equally effective for all? Systematic review of socioeconomic inequalities in impact.

Authors:  Rory McGill; Elspeth Anwar; Lois Orton; Helen Bromley; Ffion Lloyd-Williams; Martin O'Flaherty; David Taylor-Robinson; Maria Guzman-Castillo; Duncan Gillespie; Patricia Moreira; Kirk Allen; Lirije Hyseni; Nicola Calder; Mark Petticrew; Martin White; Margaret Whitehead; Simon Capewell
Journal:  BMC Public Health       Date:  2015-05-02       Impact factor: 3.295

8.  Tracking of physical activity, fitness, body composition and diet from adolescence to young adulthood: The Young Hearts Project, Northern Ireland.

Authors:  Colin Boreham; Paula J Robson; Alison M Gallagher; Gordon W Cran; J Maurice Savage; Liam J Murray
Journal:  Int J Behav Nutr Phys Act       Date:  2004-10-05       Impact factor: 6.457

9.  Physical activity across the curriculum: year one process evaluation results.

Authors:  Cheryl A Gibson; Bryan K Smith; Katrina D Dubose; J Leon Greene; Bruce W Bailey; Shannon L Williams; Joseph J Ryan; Kristin H Schmelzle; Richard A Washburn; Debra K Sullivan; Matthew S Mayo; Joseph E Donnelly
Journal:  Int J Behav Nutr Phys Act       Date:  2008-07-07       Impact factor: 6.457

Review 10.  Determinants of sugar-sweetened beverage consumption in young children: a systematic review.

Authors:  V Mazarello Paes; K Hesketh; C O'Malley; H Moore; C Summerbell; S Griffin; E M F van Sluijs; K K Ong; R Lakshman
Journal:  Obes Rev       Date:  2015-08-07       Impact factor: 9.213

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  18 in total

Review 1.  What should governments be doing to prevent diabetes throughout the life course?

Authors:  Patrick Timpel; Lorenz Harst; Doreen Reifegerste; Susann Weihrauch-Blüher; Peter E H Schwarz
Journal:  Diabetologia       Date:  2019-08-27       Impact factor: 10.122

Review 2.  School-based physical activity programs for promoting physical activity and fitness in children and adolescents aged 6 to 18.

Authors:  Sarah E Neil-Sztramko; Hilary Caldwell; Maureen Dobbins
Journal:  Cochrane Database Syst Rev       Date:  2021-09-23

Review 3.  A systematic review of existing observational tools to measure the food and physical activity environment in schools.

Authors:  Hannah G Lane; Hannah G Calvert; Rachel Deitch; Ryan Harris; Oyinlola T Babatunde; Lindsey Turner; Erin R Hager; Stephanie Jilcott Pitts
Journal:  Health Place       Date:  2020-09-06       Impact factor: 4.931

4.  Effectiveness of Interventions to Promote Healthy Eating Habits in Children and Adolescents at Risk of Poverty: Systematic Review and Meta-Analysis.

Authors:  Rosario Pastor; Josep A Tur
Journal:  Nutrients       Date:  2020-06-25       Impact factor: 5.717

5.  A qualitative study on knowledge, perception, and practice related to non-communicable diseases in relation to happiness among rural and urban residents in Bhutan.

Authors:  Hiromi Kohori-Segawa; Chencho Dorji; Kunzang Dorji; Ugyen Wangdi; Chimi Dema; Yankha Dorji; Patou Masika Musumari; Teeranee Techasrivichien; Sonia Pilar Sugimoto Watanabe; Ryota Sakamoto; Masako Ono-Kihara; Masahiro Kihara; Yuichi Imanaka
Journal:  PLoS One       Date:  2020-06-29       Impact factor: 3.240

6.  School policies, built environment and practices for non-communicable disease (NCD) prevention and control in schools of Delhi, India.

Authors:  Shalini Bassi; Vinay K Gupta; MinHae Park; Gaurang P Nazar; Tina Rawal; Soumyadeep Bhaumik; Kanwal Preet Kochhar; Monika Arora
Journal:  PLoS One       Date:  2019-04-18       Impact factor: 3.240

7.  Effectiveness of School based Awareness Programmes against Tobacco among Users and Non- Users- A Cross- Sectional Study from Rural Kerala, India.

Authors:  Radhakrishnan Jayakrishnan; Jagathnath Krishna Kumara Pillai Mohanan Nair; Geetha Seema; Gigi Thomas; Paul Sebastian
Journal:  Asian Pac J Cancer Prev       Date:  2019-07-01

8.  The Association between Perceived Adequacy and Capacity for School Food Policy Implementation with Food Availability and Policy Adherence in Nova Scotia, Canada.

Authors:  Jessie-Lee D McIsaac; Tarra L Penney; Louise Mâsse; Sara F L Kirk
Journal:  Int J Environ Res Public Health       Date:  2019-06-04       Impact factor: 3.390

9.  Significant Decrease in Childhood Obesity and Waist Circumference over 15 Years in Switzerland: A Repeated Cross-Sectional Study.

Authors:  Isabelle Herter-Aeberli; Ester Osuna; Zuzana Sarnovská; Michael B Zimmermann
Journal:  Nutrients       Date:  2019-08-15       Impact factor: 5.717

Review 10.  School environment assessment tools to address behavioural risk factors of non-communicable diseases: A scoping review.

Authors:  Kiran Saluja; Tina Rawal; Shalini Bassi; Soumyadeep Bhaumik; Ankur Singh; Min Hae Park; Sanjay Kinra; Monika Arora
Journal:  Prev Med Rep       Date:  2018-01-31
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