A systematic review of associations between the primary school built environment and childhood overweight and obesity

Health & Place 18 (2012) 504–514

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A systematic review of associations between the primary school built environment and childhood overweight and obesity Andrew James Williams a,b, Katrina Mary Wyatt a,n, Alison Jane Hurst a, Craig Anthony Williams b a b

Institute of Health Service Research, Peninsula College of Medicine and Dentistry, Veysey Building, Salmon Pool Lane, Exeter, Devon EX2 4SG, UK Children’s Health and Exercise Research Centre, Sport and Health Sciences, University of Exeter, St. Luke’s Campus, Heavitree Road, Exeter, Devon EX1 2LU, UK

a r t i c l e i n f o

a b s t r a c t

Article history: Received 31 October 2011 Received in revised form 9 February 2012 Accepted 13 February 2012 Available online 21 February 2012

This systematic review considers current literature on the association between childhood overweight and obesity and the primary school built environment. Bibliographic databases from the fields of medicine, social science, exercise science and education were systematically searched. The following elements of the built environment were found to have been investigated: playground availability and adequacy; gymnasium availability and adequacy; school field, showers and covered playground availability. One intervention study was identified which utilized the built environment as an adjunct to a behavior change intervention. This systematic review identified minimal research upon the association between the school built environment and weight status and the current results are inconclusive. & 2012 Elsevier Ltd. All rights reserved.

Keywords: Child Obese School environment Playground Body mass index

1. Introduction Within the United Kingdom (UK), between 1995 and 2008, the prevalence of overweight and obesity among 2–10 years old rose from 23.1% to 27.3% (The NHS Information Centre, 2010). Obesity in childhood is associated with increased risk of asthma, chronic inflammation, cardiovascular disease, low self-esteem and behavioral problems (Reilly et al., 2003). In addition to these health consequences there are social and financial ramifications (House of Commons Health Select Committee, 2004; Reilly et al., 2003). In 2004 the UK House of Commons Health Select Committee estimated the total annual cost of overweight and obesity in England to have been nearly £7 billion in 2002 (House of Commons Health Select Committee, 2004). The combination of these issues has made childhood obesity both a national and international public health concern (Cross-Government Obesity Unit, 2008; World Health Organization, 2008). Subsequently, the Foresight report was commissioned in the UK to investigate this epidemic (Butland et al., 2007). The Foresight report identified the complex system of elements involved in the development of obesity and highlighted the need for population based behavior change interventions (Butland et al., 2007). Those elements external to the individual n

Corresponding author. Tel.: þ44 1392 722971; fax: þ44 1392 425299. E-mail addresses: [email protected] (A.J. Williams), [email protected] (K.M. Wyatt), [email protected] (A.J. Hurst), [email protected] (C.A. Williams). 1353-8292/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.healthplace.2012.02.004

that are involved in the development of obesity have become known as the obesogenic environment (Swinburn et al., 1999). The purpose of this systematic review was to identify those elements of the primary school built environment (see Box 1 for definition) that may be associated with overweight or obesity in children aged 4–11 years and, therefore, could be part of the obesogenic environment. In adults, the associations between the built environment and obesity have been extensively researched, including two comprehensive systematic reviews (Feng et al., 2010; Papas et al., 2007). A systematic map of reviews on social and environmental interventions to reduce childhood obesity identified a need for reviews focusing on interventions or changes to the built environment (Woodman et al., 2008). Currently, no consistent associations between elements of the built environment and obesity in children, of all ages, gender, socioeconomic strata and locations have been identified (Dunton et al., 2009; Galvez et al., 2010). However, some built environment factors have been identified as having mainly small but significant associations with body mass index (BMI) in some subgroups of children (Dunton et al., 2009; Galvez et al., 2010). In particular distance to playgrounds, school playgrounds being locked outside of school hours, heavy traffic, and density of fast food restaurants, convenience stores and underground (subway) stations were positively associated with BMI in some subgroups of children (Dunton et al., 2009; Galvez et al., 2010). While neighborhood hazards and vegetation, intersection (road junction) density, road safety, walkability, and access to physical activity facilities, including paths for cycling

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Box 1–Definitions utilized throughout the systematic review and study inclusion and exclusion criteria. Definitions Obesogenic environment was defined as the sum of factors external to the individual which prompt the development of obesity Built environment was defined by Papas et al. (2007) as ‘anything made or modified by humans which is external to the individual’ (p. 129) School built environment was defined as anything made or modified by humans which is external to the individual but within the school boundaries. Smaller or variable elements of the built environment which were more likely to influence individuals than populations were excluded including vending machines which were considered more part of the food environment than the build environment and small items of play equipment Inclusion criteria

Exclusion criteria

Population: 4–11 years old children enrolled in primary school or equivalent Intervention: any changes to the school built environment including policies specific to the school built environment

Population: animal models or people outside the specified age range Interventions: studies in which the description of the intervention is not considered sufficiently detailed to enable replication Outcomes: knowledge, change in physical activity or diet

Outcomes: body mass index (using valid reference curves to define overweight and obesity), body mass index z-score or standard deviation score, percentage of body fat, waist circumference, waist-to-hip ratio, waist-to-height ratio, skin pinch/skin fold thickness Context: primary school or equivalent Context: clinical setting Study design: any experimental or observational study design. Study design: narrative reviews, editorials, opinions and letters, reports published as meeting abstracts only (where insufficient methodological details are reported to allow critical appraisal of study quality) Follow up: Z6 months (National Institute for Health and Clinical Follow up: o6 months Excellence, 2006)

and walking, were negatively associated with BMI in some subgroups of children, neither study considered the built environment within the school (Dunton et al., 2009; Galvez et al., 2010). Both reviews conclude by calling for more research on the association between the built environment and obesity, and especially studies designed to provide better quality evidence (Dunton et al., 2009; Galvez et al., 2010). In order to monitor the prevalence of childhood overweight and obesity in the UK, the National Child Measurement Programme (NCMP) was introduced in 2005 (Ridler et al., 2009). As part of this program, the BMI of all school children is measured in the first and final year of their primary education (Ridler et al., 2009). Within the UK, children undertake primary education from the age of 4–11 years during which a child may attend a junior or primary schools which are equivalent to elementary schools in the United States of America (USA). Early results from the NCMP program demonstrated a significant rise in the prevalence of obesity during the period of primary education, while the prevalence of overweight did not change (Ridler et al., 2009). This demonstrated that in the UK, the period of primary education is an important time for obesity development. This systematic review was, therefore, developed to examine the effect of the school built environment during the period of primary education. Given the range of study designs that previous reviews (Dunton et al., 2009; Feng et al., 2010; Galvez et al., 2010; Papas et al., 2007) have encountered, this systematic review was designed to be able to incorporate both experimental and observational studies. The search strategy was designed to be sensitive to identify any studies which examined the school built environment rather than specific to certain elements of the built environment (Box 2). Key definitions and the study inclusion and exclusion criteria are listed in Box 1. Within this review the built

environment was limited to the environment within the school boundaries as the authors considered this environment to be more accessible to change. The built environment was also restricted to larger infrastructural or more permanent items thereby excluding small items of play equipment and vending machines. This decision was taken to incorporate any changes to the built environment which had the potential to influence the whole school population not just individuals, e.g. food bought by individuals from vending machines.

2. Methods The methodology of this review was informed by the guidance from the Cochrane Collaboration and the National Health Service (NHS) Centre for Reviews and Dissemination and followed a protocol which is available from the corresponding author (Higgins and Green, 2011; NHS Centre for Reviews and Dissemination, 2009). 2.1. Eligibility criteria The review inclusion and exclusion criteria are listed in Box 1. The authors decided upon a minimum study duration of 6 months in line with the criteria used by the National Institute for Health and Clinical Excellence in the development of the UK guidance on the identification, prevention and treatment of obesity in children and adults (National Institute for Health and Clinical Excellence, 2006). 2.2. Search strategies The authors considered that research on the school built environment may have been published in a variety of medical

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Box 2–Complete search strategy as implemented in Ovid MEDLINEs In-Process and Other Non-Indexed Citations and Ovid MEDLINEs. 1. exp Education, Nonprofessional/ 2. exp Child/ 3. ((primary or junior or elementary) adj2 (school or schools)).ti,ab. 4. (primary adj2 (pupil or pupils or schoolchildren)).ti,ab. 5. (elementary adj2 (pupil or pupils or schoolchildren)).ti,ab. 6. (junior adj2 (pupil or pupils or schoolchildren)).ti,ab. 7. (school and (child or children or infantn)).ti,ab. 8.

9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40.

41.

42. (schooln and recreation).ti,ab. 43. (schooln and equipment).ti,ab. 44. (schooln and transport).ti,ab. 45. (schooln and (food environment or nutrition environment)).ti,ab. 46. 19 or 20 or 21 or 22 or 23 or 24 or 25 or 26 or 27 or 28 or 29 or 30 or 31 or 32 or 33 or 34 or 35 or 36 or 37 or 38 or 39 or 40 or 41 or 42 or 43 or 44 or 45 47. 18 and 46

48. Body weight/or body weight changes/or weight gain/or weight loss/or overweight/or obesity/or obesity, morbid/or thinness/ (pre-schooln or preschooln).ti,ab. 49. Body constitution/or ‘‘body weights and measures’’/or body fat distribution/or adiposity/or body mass index/or body size/or body height/or body weight/or ideal body weight/or overweight/or obesity/or obesity, abdominal/or obesity, morbid/or thinness/or waist circumference/or skinfold thickness/or waist–hip ratio/ girl.ti,ab. 50. obesn.ti,ab. girls.ti,ab. 51. (over weight).ti,ab. boy.ti,ab. 52. overweight.ti,ab. boys.ti,ab. 53. BMI.ti,ab. kid.ti,ab. 54. (body mass).ti,ab. kids.ti,ab. 55. (body mass index).ti,ab. preadolescent.ti,ab. 56. (body fat).ti,ab. preadolescence.ti,ab. 57. (body composition).ti,ab. prepubescent.ti,ab. 58. (body weight).ti,ab. 1 or 2 or 3 or 4 or 5 or 6 or 7 or 8 or 9 or 10 or 11 59. (body shape).ti,ab. or 12 or 13 or 14 or 15 or 16 or 17 exp Public policy/ 60. (waist circumference).ti,ab. exp Environment design/ 61. skinfold.ti,ab. (schooln adj2 (programn or interventionn or 62. (skin fold).ti,ab. policn or situational factors)).ti,ab. (schooln and environmentn and (determinantn 63. (waist to hip ratio).ti,ab. or design)).ti,ab. (schooln and physical and environmentn).ti,ab. 64. (waist–hip ratio).ti,ab. (schooln and built and environmentn).ti,ab. 65. (waist to height ratio).ti,ab. (schooln and perceived and environmentn).ti,ab. 66. (waist–height ratio).ti,ab. (schooln and natural and environmentn).ti,ab. 67. (abdominal fat).ti,ab. (schooln and cultural and environmentn).ti,ab. 68. adiposity.ti,ab. (schooln and urban and environmentn).ti,ab. 69. IOTF.ti,ab. 70. (international obesity task force).ti,ab. (schooln and rural and environmentn).ti,ab. (schooln and obesogenic and 71. (international obesity taskforce).ti,ab. environmentn).ti,ab. (schooln and sociocultural and 72. (weight adj2 gain).ti,ab. environmentn).ti,ab. (schooln and socio-cultural and 73. (weight adj2 loss).ti,ab. environmentn).ti,ab. (schooln and socioeconomic and 74. (weight adj2 change).ti,ab. environmentn).ti,ab. (schooln and socio-economic and 75. (BMI adj2 gain).ti,ab. environmentn).ti,ab. (schooln and political and environmentn).ti,ab. 76. (BMI adj2 loss).ti,ab. (schooln and local and environmentn).ti,ab. 77. (BMI adj2 change).ti,ab. (schooln and playground).ti,ab. 78. ((body mass index) adj2 gain).ti,ab. (schooln and playing field).ti,ab. 79. ((body mass index) adj2 loss).ti,ab. 80. ((body mass index) adj2 change).ti,ab. (schooln and field).ti,ab. (schooln and access).ti,ab. 81. 48 or 49 or 50 or 51 or 52 or 53 or 54 or 55 or 56 or 57 or 58 or 59 or 60 or 61 or 62 or 63 or 64 or 65 or 66 or 67 or 68 or 69 or 70 or 71 or 72 or 73 or 74 or 75 or 76 or 77 or 78 or 79 or 80 (schooln and facilitn).ti,ab. 82. 47 and 81

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and non-medical journals and consequently medicine, social science, exercise science and education databases were searched. The following databases were searched: Medline In-Process and Other Non-Indexed Citations (Ovid 1948 to January 2011), Medline (Ovid 1948 to January 2011), Embase (Ovid 1980 to January 2011), PsychINFO (Ovid 1806 to January 2011), SportDiscus (Ebscohost 1939 to 2011), Web of Science (ISI Web of Knowledge 1900–2011), Education Resource Information Center (ERIC) (Dialog Datastar 1966 to January 2011), British Education Index (Dialog Datastar 1975 to January 2011), Australian Education Index (Dialog Datastar 1979 to January 2011), Cumulative Index to Nursing and Allied Health Library (CINAHL Plus) (Ebscohost 1986–2010), The Cochrane Library (Wiley Online 1898 to January 2011), and Applied Social Science Index and Abstracts (ASSIA) (CSA Illumina 1987 to January 2011). The search strategy implemented in Medline is given as an example in Box 2. The search strategy was adapted for use in each of the databases listed above (the complete search log is available from the corresponding author). The metaRegister of Controlled Trials, Clinical Trials.gov and the International Clinical Trials Registry Platform were searched in March 2011 for any ongoing or unpublished trials with the search term ‘school and (overweight or obesity) and (environment or design)’ with the age limiter child. In order to retrieve material which was ‘not published in an easily accessible form’ (p. 266) gray literature, the websites of the Robert Wood Johnson Foundation and the National Trust for Historic Preservation were searched (NHS Centre for Reviews and Dissemination, 2009). The Robert Wood Johnson Foundation had been identified as funding a number of interventions around childhood obesity and the National Trust for Historic Preservation has a campaign around community-centered schools (National Trust for Historic Preservation, 2011; Robert Wood Johnson Foundation, 2011). The bibliographies of included studies and retrieved systematic reviews were searched to identify any additional studies. Three authors were contacted for further data or information on the intervention, of whom two responded. 2.3. Study identification Following the removal of duplicates, article titles were screened for appropriateness by a researcher (AJW or KMW). The resulting titles and abstracts which were not screened out were reviewed independently by two researchers (AJW and KMW) and any disagreement was resolved by a third reviewer (AJH). A more detailed review of the full text of retrieved articles was undertaken by two researchers (AJW and AJH or KMW) prior to quality assessment and data abstraction. 2.4. Quality assessment and data extraction As this review sought to incorporate randomized and nonrandomized study designs and observational studies, multiple methods of quality assessment and data extraction were required. The data collection checklist and data abstraction form utilized by the Cochrane Effective Practice and Organisation of Care (EPOC) Group incorporates quality assessment and data extraction of structural interventions (Cochrane Effective Practice and Organisation of Care Review Group, 2002a, b). These tools were adapted and amalgamated with the Newcastle–Ottawa scales for assessing the quality of non-randomized studies to provide a quality assessment and data extraction form for this review (available from the corresponding author) (Wells et al., n.d.). The quality assessment and data extraction tool was piloted on four papers by two reviewers (AJW and AJH) to assess suitability. Quality assessment and data extraction on all papers appearing to

507

meet the inclusion criteria was undertaken by one reviewer (AJW) and then checked by a second reviewer (AJH or KMW). The following data was extracted from each retrieved articles: study design; geographic location of study (country); source of funding; ethics approval; details of the study sample and recruitment; summary characteristics of the study population; details of the intervention, including target behavior and evidential or theoretical foundation; treatment of any control group; definition of obesity; duration of follow-up; and results. 2.5. Data analysis As the purpose of this systematic review was to identify the obesogenic elements of the primary school built environment it was expected that the study designs and variety of interventions would prevent the use of meta-analysis. Therefore, data summaries are narrative without combining results.

3. Results 3.1. Identified studies Fig. 1 illustrates the study identification process. Bibliographic databases identified 5015 unique articles and the search of clinical trials registers and gray literature identified 233 unique items. Through the study identification process described above, eleven eligible articles were identified including six intervention articles and five observational articles (Amigo et al., 2007; Fernandes and Sturm, 2010; Kelly et al., 2010; Muckelbauer et al., 2009a, b, c, 2010; Ozdemir and Yilmaz, 2008; Robert Wood Johnson Foundation, 2010; University of Lausanne Hospitals, 2009; Zhu et al., 2010). Two of these studies were still ongoing and hence could not be reviewed (Robert Wood Johnson Foundation, 2010; University of Lausanne Hospitals, 2009). Given that the search strategy had been designed to be more sensitive than specific the majority of articles were excluded during the initial screening. Fig. 1 also summarizes the reasons for the exclusion of the articles. Examining the biographies of the nine identified articles any retrieved systematic reviews did not identify any additional eligible studies. 3.2. Study and participant characteristics Although the search strategy did not limit the time period during which studies could be published, all nine included articles were published between 2007 and 2010 (Table 1). Out of the nine articles, four articles all relate to the same intervention study which took place in Germany (Muckelbauer et al., 2009a, b, c, 2010); of the five observational studies, three took place in the USA (Fernandes and Sturm, 2010; Kelly et al., 2010; Zhu et al., 2010), one in Chile (Amigo et al., 2007) and one in Turkey (Ozdemir and Yilmaz, 2008). Table 1 summarizes the characteristics of each of the included studies. Only two studies incorporated less than 1000 participants and both the smaller studies included in excess of 200 participants. All the studies utilized objectively measured BMI as an outcome. The majority of studies, age and gender standardized the BMI outcome into BMI standard deviation scores (BMI-SDS) using national or USA reference populations. The USA Centers for Disease Control and Prevention (CDC 2000) (Kuczmarski et al., 2002) or International Obesity Task Force (IOTF) (Cole et al., 2000) cut-offs were used to categories participants as overweight or obese in those studies which calculated BMI-SDS. The study undertaken in Chile did not indicate whether a reference population was utilized or which cut-offs were used to categories

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Records identified through database searching (n = 7557)

Additional records identified through other sources (Gray literature) (n = 427)

Records after duplicates removed (n = 5015+233 Gray)

Records screened (n = 5015+233 Gray)

Title and abstract reviewed for eligibility (n = 450+233 Gray)

Full-text articles assessed for eligibility (n = 92+2 Gray)

Articles included in systematic review Intervention articles (n = 6 incl. 2 in progress) Observational articles (n = 5)

Records excluded (n = 4565) Population (n=66) Intervention (n=1049) Outcome (n=296) Context (n=1434) Study design (n=1718) Follow-up (n=2) Records excluded (n = 358+231 Gray) Population (n=13+26 Gray) Intervention (n=123+85 Gray) Outcome (n=57+36 Gray) Context (n=7+36 Gray) Study design (n=158+48 Gray) Full-text articles excluded (n = 83). Population (n=4) Intervention (n=55) Outcome (n=10) Context (n=1) Study design (n=12) Follow-up (n=1)

Fig. 1. Flow diagram of the identification of literature for inclusion in this systematic review.

overweight and obesity (Amigo et al., 2007). One of the remaining two studies reported BMI without standardization for gender and age, and the other used the Fitnessgrams BMI Health Fitness ZoneTM (BMIHFZ) method of assessing weight status (Table 1) (Going et al., 2008). The cut-off of the BMIHFZ lies between the 85th and 95th CDC 2000 percentiles, which indicate that this study was similar to those studies assessing the prevalence of overweight and obesity (Going et al., 2008; Kuczmarski et al., 2002; Welk et al., 2010; Zhu et al., 2010). All the studies examined both males and females. Two studies examined the entire school population (Muckelbauer et al., 2009a, b, c, 2010; Zhu et al., 2010), while the other studies examined specific year groups within the school. The two studies from the USA (Fernandes and Sturm, 2010; Kelly et al., 2010) which did not examine the entire school, examined children aged 10–11 years at the end of their primary education, while the studies from Turkey (Ozdemir and Yilmaz, 2008) and Chile (Amigo et al., 2007) examined children around the mid-point of their primary education. While four of the studies took place in developed countries, only two studies presented an indication of the socioeconomic status of the participants (Table 1). Fernandes and Sturm (2010) report, of those who provided data on household income, 21.4% had a household income r$25,000 per annum, while Amigo et al. (2007) report the median household income of participants was around Chilean$50,000 per capita. Data regarding ethnicity was reported by two studies, Muckelbauer et al. (2009a, b, c, 2010) report that around 45% of their participants had migrated into Germany, while Fernandes and Sturm (2010) report that the majority (59.3%) of their participants were white with the largest minority (17.3%) being Hispanic (Table 1). Four of the included studies report the prevalence of overweight or obesity (Table 1). Amigo et al. (2007) report the median BMI of participants as 18.40 kg/m2 for males and 18.39 kg/m2 for females, Kelly et al. (2010) report the mean BMI of their male participants to be 20.91 kg/m2 and 21.10 kg/m2 for female participants (Table 1). Fernandes and Sturm (2010) and Ozdemir and

Yilmaz (2008) both report the prevalence of obesity to be around 20% in their sample, while Muckelbauer et al. (2009a, b, c, 2010) and Zhu et al. (2010) report the prevalence of overweight or obesity to be between 25% and 30% (Table 1). These prevalence data are similar to those reported in the UK for this age group (The NHS Information Centre, 2010). 3.3. Study quality The quality of the included studies is summarized in Table 2. Three of the observational studies report using samples representative of their population (Fernandes and Sturm, 2010; Kelly et al., 2010; Ozdemir and Yilmaz, 2008). Amigo et al. (2007) selected a sample to examine a range of obesity prevalences rather than being representative of the Chilean population. Within Table 2 it is listed that the representativeness of the sample in the Zhu et al. (2010) study is not described. However, the data comes from the state-wide Texas Youth Fitness Study and, therefore, may be considered representative of the Texan population (Zhu et al., 2010). All of the observational studies assessed differences between the exposed and unexposed groups by controlling for ethnicity and/or socioeconomic status with the exception of Ozdemir and Yilmaz (2008), and Zhu et al. (2010) (Table 2). Three of the observational studies measured exposure to the built environment variable as part of the study, while one relied on information reported in questionnaires and another relied upon information reported by the head teacher or principal of the school (Fernandes and Sturm, 2010; Kelly et al., 2010). Although, within their paper, Ozdemir and Yilmaz (2008) report measuring the built environment as part of the study, this information is summarized as the school yard being ascribed a score of one or two. The article describes the allocation of the scores such that ‘environments with low physical qualities’ score one, while ‘environments with advanced features’ score two (Ozdemir and Yilmaz, 2008). The group which allocated these scores included architects and landscape architects, but there is no reference to

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Table 1 Summary characteristics of the included studies. Built environment intervention or variable

Outcome measure

Covariates

Results

Male (n ¼272): median age 7.6 Amigo et al. (2007)/ Chile/n¼ 504/cross- (IQR 7.3–7.10) years, median household income Chilean$ sectional study 45,833 (IQR 30,000–70,000) per capita, median BMI 18.40 (IQR 16.37–20.06) kg/m2 Female (n¼ 232): median age 7.7 (IQR 7.4–7.10) years, median household income Chilean$ 54,000 (IQR 32,000– 83,333) per capita, median BMI 18.39 (IQR 16.19–20.16) kg/m2 No ethnicity data provided

Availability of gym, covered yard, shower and sports field and whether the yard is large enough for the school

BMI, BMI-SDS (no reference population indicated)

Duration of parents education, household income, family size, calorie intake, whether the parents are obese, whether the child has a sedentary lifestyle, how much television the child watches, whether the school is able to maintain the infrastructure, whether the school has a physical education teacher, whether the school provides sports equipment and whether children participate in championships

No statistically significant differences in facility availability or adequacy between schools with low, medium or high prevalence of obesity were identified

Fernandes and Sturm (2010)/USA/ n¼ 8392/cohort studya

Male and female: 10–11 years (5th grade), 59.3% white, 10.7% black, 17.3% Hispanic, 12.7% other, 21.4% household income r$25,000, 20.4% obese

Availability of gym and adequacy of gym and playground

BMI, BMI-SDS (CDC 2000)

Childs ethnicity, household income, whether the child is eligible for free or reduced school meals, school enrollment, proportion of pupils from ethnic minorities attending the school, school location (urban, suburban, rural), climate zone.

Adjusted mean difference 7SE Gym availability: female 1.40 71.19, male 0.167 1.31, gym available and adequate: female 0.747 1.18, male 0.707 1.19, playground available and adequate: female  0.327 1.48, male  0.417 0.91

Kelly et al. (2010)/ USA/n¼ 5248/ cross-sectional study

Male (mean BMI 20.91 kg/m2) and Female (mean BMI 21.10 kg/m2): 10–11 years (5th grade) and 12–13 years (7th grade) No socioeconomic status or ethnicity data provided

Availability of gym and field

BMI

Adjusted mean difference Whether PE was a required subject, whether schools required  0.94* a set duration of PE, whether PE was used as a punishment, reasons for exemption from PE, whether the community could access school facilities and were free intramural opportunities available and did PE teachers require certification

Muckelbauer et al. (2009a, b, c, 2010)/ Germany/n¼ 2950, I: n¼ 1641, C: n¼ 1309/cluster randomized controlled trial

Installation of water Male (I: n¼ 824,C: n ¼658) and fountains female (I: n ¼817, C: n ¼651): mean age I: 8.26 (SD 0.73) years, C: 8.34 (SD 0.76) years, I: 42.1% with migrational background, C: 47.0% with migrational background, I: 23.4% overweight, C: 25.9% overweight No socioeconomic status data provided

BMI, BMI-SDS (IOTF German reference population)

Intervention pupils also received Adjusted odds ratio of overweight in intervention water bottles and lessons on water; migration background and group 0.69 (95% CI 0.48–0.98)* beverage consumption

Ozdemir and Yilmaz (2008)/Turkey/ n¼ 290/crosssectional study

Male (n ¼135) and Female (n ¼155): 8–10 years (3rd–4th grade), 18.2% obese No socioeconomic status or ethnicity data provided

Adequacy of school yard

BMI (CDC 2000)

No covariates were included in the analysis

Mean BMI 7 SD in school with worse yard score 16.75 7 2.65, better yard score 17.76 7 2.68 F(1,288) ¼ 9.626*

Zhu et al. (2010)/ USA/n¼ 783 elementary schools, crosssectional study

Male and female: 6–10 years (elementary school), 71.7% (SD 12.6) of elementary school children achieved the Fitnessgrams BMI Health Fitness Zone (43)

Availability of playground, football field, track, and indoor and outdoor PE facilities

Fitnessgrams BMI Healthy Fitness Zone (Going et al., 2008)

Teacher demographics and training, PE/recess variables, overcrowding, extracurricular activities, PE funding and PE policy elements and Fitnessgrams experience

Adjusted change in proportion of school within BMIHFZ7 SE: playground 2.46 71.25, football field 0.87 7 0.93, track 0.79 70.74, in/outdoor facilities 1.657 1.30

Study/location/ sample size/study design

Demographics and weight characteristics

Abbreviations—BMI: body mass index, BMI-SDS: BMI standard deviation score, C: Control group, CDC(2000): Centers for Disease Control and Prevention 2000 growth reference charts, I: Intervention group, IOTF: International Obesity Task Force, IQR: Interquartile range, PE: physical education, SD: standard deviation, SE: standard error. a n

The results reported incorporate information attained during personal communication with Fernandes, M. (2011). p o 0.05.

assessing the validity and reliability of the scoring system (Ozdemir and Yilmaz, 2008). The lack of explicit reporting of the method of assessing the environment, limits the external validity of this study. Two of the papers, which examined adequacy of the built environment, utilized lower quality methods of assessing the built environment which may have been due to the difficulty in objectively assessing a subjective concept such as adequacy (Fernandes and Sturm, 2010; Ozdemir and Yilmaz, 2008).

Two studies reported exposure of participants to the school built environment in excess of one year. Zhu et al. (2010) do not report how long participants had been exposed to the school built environment, but, as a state-wide initiative, the sample may have included pupils who had only recently joined the school, while others may have had sufficient exposure. All the incorporated studies measured BMI as the anthropometric outcome measure. BMI is commonly used in epidemiology to assess

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Table 2 Summary of study quality. Adequacy of exposure

Observational studies

Representativeness of the sample

Comparability of cohorts

Ascertainment of exposure

Assessment of outcome

Duration of exposure

Amigo et al. (2007)

At risk group

Controlled for socioeconomic status and additional factors

Measured as part of the study

Independent of exposure

Complete Possibly not sufficient only 1 year

Fernandes and Sturm (2010)a

Representative

Controlled for ethnicity, socioeconomic status and additional factors

Written self report

Independent of exposure

Sufficient

Complete

Kelly et al. (2010)

Representative

Controlled for ethnicity Written self report and additional factors

Independent of exposure

Sufficient

Missing data may have introduced bias

Ozdemir and Yilmaz (2008)

Representative

Did not control for ethnicity or socioeconomic status

Measured as part of the study however, not sure of objectivity

Independent of exposure

Sufficient

Complete

Zhu et al. (2010)

Not described

Did not control for ethnicity or socioeconomic status

Measured as part of the study

Independent of exposure

Not clear

Complete

Interventional study

Concealment of allocation

Baseline measurement

Reliability of outcome measure

Blinding

Duration of Protection against follow-up contamination

Muckelbauer et al. (2009a, b, c, 2010)

Completed, through random selection of schools

Completed

Completed

Not clear due to the nature of the Sufficient intervention it is unlikely that the outcome was assessed blindly

a

Completed as the intervention schools were in a different city to the control schools

The results reported incorporate information attained during personal communication with Fernandes, M. (2011).

weight status and, therefore, may be considered as a reliable measure (Reilly et al., 2010). However, none of the studies used two independent assessors to measure the children and, therefore, no measures of agreement can be reported. All the observational studies were considered to have measured anthropometry independently from the measurement of exposure. Participants within the Amigo et al. (2007) study had been exposed to the school built environment for only one year, which may not be sufficient to observe changes in BMI. However, the intervention study observed an effect within a school year (Muckelbauer et al., 2009a, b, c, 2010). Due to the nature of observational studies, these studies did not report significant quantities of missing data. However, Kelly et al. (2010) did report missing data which may have introduced bias and prevented the inclusion of private schools. Overall, the intervention study met each criteria of the quality assessment apart from criteria related to the cluster nature of the study design or the nature of the intervention for example, individual randomization, double blinding. Although schools were randomly selected, in order to prevent contamination, intervention schools (Dortmund) were in a different city to control schools (Essen) (Muckelbauer et al., 2009c). It is reported that these are neighboring cities with similar population size, location and history, but there may have been differences in demographics which were not reported (Muckelbauer et al., 2009c). As elements of the built environment were introduced as part of the intervention it may not have been possible to blind the assessment of outcome (Table 2) (Muckelbauer et al., 2009c). 3.4. School built environment The narrative analysis of the retrieved studies will be undertaken thematically. Initially the intervention study is discussed which assessed the effect of altering the built environment as an

adjunct to a behavior change intervention. Subsequently, the observational studies will be discussed examining, firstly, the results related to playground, then gymnasia and indoor facilities and finally other miscellaneous facilities (Table 1).

3.4.1. School built environment as an adjunct to obesity prevention interventions Muckelbauer et al. (2009a, b, c, 2010) installed water fountains in schools as part of their intervention to promote water consumption, with the secondary effect of displacing sweetened beverage consumption. Intervention participants received a 500 mL plastic water bottle, and teachers gave four 45 min lessons on the role of water in the human body and nature, which were grounded in the theory of planned behavior (Ajzen, 1991; Muckelbauer et al., 2009a, b, c, 2010). The difference in the change in BMI-SDS between the intervention and control schools was  0.004 (95% confidence interval, 95% CI  0.045 to 0.036) which was not significant (Muckelbauer et al., 2009c). However, a significant intervention effect upon the prevalence of overweight was observed (Table 1) (Muckelbauer et al., 2009c). The odds of being overweight at an intervention school following adjustment for the baseline prevalence of overweight and clustering by school were 0.69 (95% CI 0.48 to 0.98, p¼ 0.040) when compared with the control schools (Table 1) (Muckelbauer et al., 2009c). In particular the incidence rate of overweight was significantly lower in intervention schools (3.8% compared to 6.0%, p ¼0.018) (Muckelbauer et al., 2009b). However, the observed intervention effect upon overweight prevalence and incidence was only observed among non-immigrant children (Muckelbauer et al., 2010). As the only intervention study meeting our inclusion criteria Muckelbauer et al. (2009a, b, c, 2010) demonstrates the effective use of an aspect of the built environment to support a behavior change intervention, but this is insufficient evidence

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upon which to base a recommendation and therefore further research is needed. 3.4.2. Playgrounds Only one study examined the potential for an association between availability of a playground and BMI, while three studies investigated the association between playground adequacy and BMI. Zhu et al. (2010), utilized both ordinary least squares regression and multilevel modeling and combined the elementary, middle, and high school data in the multilevel models. Because this data could not be disaggregated the extraction of the results of multilevel models relevant to this systematic review was prevented (Zhu et al., 2010). The results from the ordinary least squares regression indicated that presence of a playground was associated with an additional 2.46% (standard error, SE¼1.25) of pupils being categorized within the BMIHFZ which was not significant (Table 1) (Zhu et al., 2010). Of the three studies which examined associations with playground adequacy, one described adequacy as relating to size, one assessed physical qualities and the other did not describe what indicated adequacy (Amigo et al., 2007; Fernandes and Sturm, 2010; Ozdemir and Yilmaz, 2008). Amigo et al. (2007) qualified adequacy as relating to whether the playground met the size standards set by the Chilean government. They found that the provision of an ‘adequate’ playground did not significantly (p¼ 0.988) differ between schools with low, medium or high prevalence of obesity. Fernandes and Sturm (2010) asked the school head teacher or principal to assess playground adequacy and found no association between BMI and playground adequacy (Table 1). However, logistic regression indicated that having an adequate playground was significantly associated with lower prevalence of obesity in males (adjusted odds ratio, AOR ¼0.98, SE¼0.12) but not females (AOR¼1.15, SE ¼0.13) (Fernandes, M., personal communication, 2011; Fernandes and Sturm, 2010). However, the reduction in the odds of obesity in males is too small to be clinically significant. The categorization of playground (school yard) adequacy used by Ozdemir and Yilmaz (2008) has been described above. The study identified a significant association (F(1,288)¼9.626, p ¼0.002) between BMI and playground adequacy (Ozdemir and Yilmaz, 2008). However, the lower (less adequate) yard score was associated with lower BMI which was contrary to their expectations (Ozdemir and Yilmaz, 2008). However, participants with less adequate playgrounds expressed higher satisfaction with the playground, which could indicate that the adults’ perceptions of the playground differ from the child’s and may explain part of the identified association (Ozdemir and Yilmaz, 2008). Overall there is insufficient research to support any conclusions upon the role of playgrounds in the development of overweight and obesity in children. However, based upon the four included studies future research should examine the adequacy and perceptions of the playground not just presence or absence. 3.4.3. Gymnasia and indoor facilities Four observational studies examined whether the availability of a gymnasium or indoor physical activity facility were associated with BMI (Table 1). Amigo et al. (2007) found no significant difference (p ¼0.267) between gymnasium availability in schools with low, medium or high prevalence of obesity (Table 1). However, gymnasium availability was highest in schools with the lowest prevalence of obesity (61.5% of low prevalence, 57.1% of medium prevalence, and 33.1% of high prevalence schools had a gymnasium) (Amigo et al., 2007). Fernandes and Sturm (2010) examined both gymnasium availability and adequacy, and found no significant associations

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with BMI (Table 1). However, results showed that BMI was higher among those pupils whose schools had an available and/or adequate gymnasium (Fernandes, M., personal communication, 2011). They found that boys attending a school with a gymnasium had 0.39 times the risk of obesity compared to those attending a school without a gymnasium (AOR¼1.39, SE¼0.16) (Fernandes, M., personal communication, 2011). Similarly, girls attending a school with an adequate gymnasium were at 0.43 times the risk of obesity compared with those attending a school with an inadequate gymnasium (AOR¼1.43, SE¼0.18) (Fernandes, M., personal communication, 2011; Fernandes and Sturm, 2010). Kelly et al. (2010) identified a significant association between having access to a gym or field at school and lower BMI (adjusted mean difference¼  0.94, p ¼0.01) using multivariable regression, following adjustment for ethnicity, gender, environment and variables related to physical education (PE) (Table 1). Zhu et al. (2010) did not identify a significant association between BMI and whether the school had both indoor and outdoor facilities for physical activity (Table 1). However, elementary schools that had both indoor and outdoor facilities had a higher proportion of pupils achieving the BMIHFZ (Zhu et al., 2010). The Zhu et al. (2010) sample included children across the primary school age range, while the sample studied by Amigo et al. (2007) was aged between 7 and 8 years and both Fernandes and Sturm (2010) and Kelly et al. (2010) studied those aged 10 to 11 years (Table 1). The age difference between those studied by Amigo et al. (2007) and those studied by Fernandes and Sturm (2010) and Kelly et al. (2010) could explain the difference between their results, younger children may not be granted as much access to the gymnasium as older children due to concerns about safety. Kelly et al. (2010) did not report calculating BMI-SDS and did not adjust for socioeconomic status which may have resulted in the difference between their results and those reported by Fernandes and Sturm (2010). Rigorous studies which adequately adjust for factors such as ethnicity and socioeconomic status are required as the mixed results and limited number of studies prevent drawing any conclusions or recommendations on the association between gymnasia and overweight or obese children. 3.4.4. Other miscellaneous facilities Amigo et al. (2007) and Zhu et al. (2010) also examined other elements of the school physical activity-related built environment (Table 1). Both Amigo et al. (2007) and Zhu et al. (2010) investigated whether there was an association between schools having a playing field and BMI; neither identified a significant association. Zhu et al. (2010) also investigated whether the availability of a running track was associated with BMIHFZ achievement; no significant association was identified in elementary schools (Table 1). Amigo et al. (2007) also investigated the association between the availability of a covered playground or shower and BMI and found no evidence of significant associations (Table 1).

4. Discussion The aim of this systematic review was to examine the evidence around the potential influence of the school built environment upon childhood obesity. Unlike previous reviews our search strategy incorporated a wide variety of bibliographic databases to ensure that research from outside the medical field was identified and, where relevant, retrieved. However, a number of these retrieved studies did not incorporate an anthropometric outcome, which prevented inclusion in this review. The search strategy retrieved articles from developing and developed

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countries and, although the search was not restricted to a particular time period, all the included studies were published within the last 5 years (Table 1). The only intervention study identified made changes to the built environment as an adjunct to a behavior change intervention, while the five observational studies examined the following elements of the school built environment: playgrounds, gymnasia and other indoor facilities, playing fields, running tracks, showers and covered playgrounds. The results and study quality were mixed. Taking into consideration the limited number of studies no conclusions upon effects or associations between child weight status and school built environment can be made and subsequently neither can any recommendations for practice. The main conclusion of this review is that additional research is required to identify whether there is an association between the school built environment and overweight or obese children. A possible limitation of this review may be the requirement of 6 months follow-up and an anthropometric outcome as opposed to the mediating outcomes dietary intake or physical activity (Box 1). However, Fig. 1 demonstrates that very few articles were excluded due to their follow-up duration. The anthropometric outcome requirement led to the exclusion of studies such as Stratton and Mullan (2005) who examined the effect of playground markings upon physical activity. However, there have been reviews upon the association between the built environment and physical activity (Davison and Lawson, 2006) and therefore this review sought to examine whether the associations identified impacted sufficiently to affect weight status. A further possible limitation of this review may be how we defined ‘policies related to the built environment’. Studies examining policies related specifically to the school built environment were considered eligible for inclusion, however, no such studies were identified, whereas policies on physical activity with reference to the school built environment were considered ineligible. For example, a policy which states that football should only be played on the playing field would not be included, while a policy stating that pupils cannot access the school garden would have been considered eligible. This decision was taken as it was considered that the ineligible policies would be reviewed as physical activity policies. The studies identified within this review point to some potential topics for future research such as the association between playground and gymnasium or indoor facility adequacy and weight status and the use of the built environment to support behavior change interventions. Given that schools contain environments specifically designed for eating and physical activity which should be promoting healthy lifestyles, the lack of significant associations may either indicate ‘how’ children exposed to the environment needs to be considered more carefully or that the environment is not being utilized to its full potential. Undertaking consideration of the school built environment within the analysis grid for environments linked to obesity (ANGELO) framework (Swinburn et al., 1999), it is noted that no studies were identified that examined the cafeteria built environment or the availability of swimming pools. Studies that have examined the effect of painted markings on playgrounds were identified, however, the lack of an anthropometric outcome or sufficient follow-up prevented inclusion within this review (Stratton and Mullan, 2005). Another potential area of interest for future research is the relationship between children’s perceptions of the school built environment and overweight or obesity. In their systematic review Davison and Lawson (2006) identified associations between attributes of the physical environment and physical activity among children, such as the availability and adequacy of recreational facilities and road crossings. This research should

be extended to see whether the influence upon physical activity extends to improve weight status. However, as previously indicated the studies in this review, which assessed adequacy, used less rigorous methods overall to determine any association between the environment and children’s weight status (Amigo et al., 2007; Fernandes and Sturm, 2010; Ozdemir and Yilmaz, 2008). Subsequently, there is also a need to develop tools like those developed by Jones et al. (2010) which not only assess the features of the environment but also capture perceptions of the environment, which can be tested in multiple studies (Amigo et al., 2007; Feng et al., 2010; Fernandes and Sturm, 2010; Ozdemir and Yilmaz, 2008). The studies identified within this review highlight methodological points which should be considered when designing and undertaking future research in this area. The observational studies which identified significant associations between the school built environment and weight status utilized less complex or univariable analyses which may be misleading due to the lack of adjustment for potential confounders (Amigo et al., 2007; Kelly et al., 2010; Ozdemir and Yilmaz, 2008). While the studies that found fewer or no significant associations between the school built environment and BMI utilized multivariable modeling (Amigo et al., 2007; Fernandes and Sturm, 2010; Zhu et al., 2010). For example Amigo et al. (2007) noted that behavioral, biological and cultural factors predicted BMI rather than school characteristics, while Fernandes and Sturm (2010) identified that school facility provision differed by socio-demographics including socioeconomics. Socioeconomics could be confounding or modifying the association between the schools built environment and overweight and obesity. Gender, age, ethnicity and socioeconomic status should be accounted for in any future research, as the associations between these factors and obesity are well documented and they may be associated with the built environment. Similarly, Fernandes and Sturm (2010) and Zhu et al. (2010) who found few significant associations between school built environment and BMI adjusted for school location and climate, and variables related to the PE experience (e.g. teacher demographics, training and PE policy) (Fernandes and Sturm, 2010; Kelly et al., 2010; Zhu et al., 2010). These factors could influence children’s exposure to, or experience of, the built environment, and hence should be considered for inclusion within any future research. In undertaking multivariable analysis appropriate analytical techniques such as multilevel modeling should be used.

5. Conclusion Using an extensive search strategy and systematic review process this study aimed to build on previous work to provide an insight into the role of the school built environment upon childhood overweight and obesity (Dunton et al., 2009; Feng et al., 2010; Galvez et al., 2010; Papas et al., 2007). The review was designed to be able to incorporate the wide range of study designs likely to be used by researchers investigating the effects of the built environment. However, whilst previous reviews and reports have highlighted the built environment as potential risk factor for obesity, currently there is insufficient evidence to support modifying the built environment within schools as an intervention to prevent or reduce childhood overweight and obesity. More research is needed before definitive conclusions can be drawn. Improving and enhancing the built environment for physical activity is likely to be beneficial for health and wellbeing. However, research upon specific attributes of the school built environment may identify small adjustments like playground markings which can be implemented in these financially restricted times.

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Potential areas for future research highlighted within the review include the association between adequacy and acceptability of the school built environment and child weight status and using the school built environment to support obesity prevention interventions. More explicit reporting of how the built environment was evaluated would strengthen the research and may pinpoint specific elements of the built environment which could be examined in intervention studies (Dunton et al., 2009). Future research should include appropriate potential individual and contextual confounders within any analysis in particular ethnicity and socioeconomic status. Intervention studies, which have shown significant results upon outcomes such as physical activity, could have been further enhanced by evaluating the impact on weight status (Stratton and Mullan, 2005). A further possible development of the research field could come from natural experiments utilizing national programs which monitor BMI in schools, such as the NCMP (Butland et al., 2007; Feng et al., 2010; Ridler et al., 2009). Future research using appropriate methodologies and taking into consideration the points outlined within this review will be able to define the association between the school built environment and child weight status which may prove beneficial in the prevention of childhood overweight and obesity.

Acknowledgments The authors would like to thank the reviewers for their insightful comments, which have helped to improve the article. The authors also wish to acknowledge the contributions of Mary Reece, Kate Boddy and the Systematic Review group at the Peninsula College of Medicine and Dentistry. AJW is funded by a Medical Research Council Doctoral Training Grant and Sport and Health Sciences, University of Exeter. KMW and AJH were also partially supported by the National Institute for Health Research (NIHR) PenCLAHRC. The views expressed in this publication are those of the authors and not necessarily those of the National Health Service (NHS), the NIHR or the Department of Health.

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