Elsevier

Health & Place

Volume 17, Issue 1, January 2011, Pages 207-214
Health & Place

Childhood obesity and proximity to urban parks and recreational resources: A longitudinal cohort study

https://doi.org/10.1016/j.healthplace.2010.10.001Get rights and content

Abstract

The objective of the research was to assess how proximity to parks and recreational resources affects the development of childhood obesity through a longitudinal study. Data were collected on 3173 children aged 9–10 from 12 communities in Southern California in 1993 and 1996. Children were followed for eight years to collect longitudinal information, including objectively measured body mass index (BMI). Multilevel growth curve models were used to assess associations between attained BMI growth at age 18 and numerous environmental variables, including park space and recreational program access. For park acres within a 500 m distance of children’s homes, there were significant inverse associations with attained BMI at age 18. Effect sizes were larger for boys than for girls. Recreation programs within a 10 km buffer of children’s homes were significantly and inversely associated with achieved levels in BMI at age 18, with effect sizes for boys also larger than those for girls. We conclude that children with better access to parks and recreational resources are less likely to experience significant increases in attained BMI.

Introduction

Obesity is a serious and worsening public health problem. The occurrence of overweight risk and high body mass index (BMI) status in youth age 2–19 years increased to approximately 32% by 2003–2006, up from approximately 15% in the 1970s (Ogden et al., 2008). Obesity can be detrimental to children’s health, increasing risk of type 2 diabetes, cardiovascular disease, and additional physical or psychological problems (Dietz, 1998). Additionally, overweight children and adolescents are more likely to become overweight adults (Freedman et al., 2007). Many potential explanations exist addressing the root causes of the obesity problem. While genetic factors probably contribute (Stunkard, 1991), rapid increases in obesity suggest that individual behavior patterns including low levels of physical activity appear to powerfully influence obesity trends (Hill and Peters, 1998).

The urban built environment, including parks and other green space, and recreation programs that provide structured settings for exercise, might also shape opportunities for physical activity, affecting development of obesity. Research suggests that physical characteristics of the built environment surrounding a child’s neighborhood or school can significantly influence physical activity and thus health outcomes (Sallis et al., 1997, Cummins and Jackson, 2001, Godbey and Mowen, 2003, Ho et al., 2003, Godbey et al., 2005). Parks especially have been investigated (Bedimo-Rung et al., 2005), while recreational programming has been infrequently studied for either adults or children (Dahmann et al., 2010).

Leisure researchers established the benefits of parks from social, psychological, and environmental standpoints but recent public health studies focus on the role of parks in promoting physical activity (Sallis et al., 1992, Cummins and Jackson, 2001). Several studies have specifically examined relationships between parks and children’s physical activity (Sallis et al., 2000, Krizek et al., 2004). Many show that children with more access to parks and recreational facilities are more active than children with less access (Sallis et al., 1992, Gomez et al., 2004, Timperio et al., 2004). Measures used in such research include presence vs. absence of a park or recreation facility near the home, density of facilities, or total acreage of recreational land within a given radius of the home (Mota et al., 2005, Norman et al., 2006, Roenmich et al., 2006). A few studies (Sallis et al., 1999, Pate et al., 2002) using accelerometry to measure physical activity objectively, as opposed to self-report or direct observation that might be subject to bias (Davison and Lawson, 2006), reported no link between physical activity and environmental variables including access to parks.

Giles-Corti et al. (2005) outlined the importance of attractiveness and size of open space in addition to access and proximity. In a series of studies (Giles-Corti et al., 2003, Giles-Corti and Donovan, 2002), associations between environmental factors and physical activity were examined in a sample of adults aged 18–59 in Perth, Australia. Using cross-sectional surveys and a scan of environmental facilities, these studies adjusted for demographics and variations in the built environment (e.g. absence vs. presence of sidewalks, access to recreational facilities). They reported that parks were more likely to encourage physical activity if they were perceived as aesthetically pleasing (minor traffic, sidewalks, trees, retail shops).

Only a handful of studies have objectively measured environmental characteristics, such as parks or recreational resources, to understand their association with obesity in children or youth. Methodological issues of concern include the use of varying measurements and the limiting nature of the cross-sectional design. In a cross-sectional study, for example, Kligerman et al. (2007) used a 4-component neighborhood walkability index (that reflected the quality of pedestrian facilities, roadway conditions, land use patterns, and community support, security and comfort for walking), and access/proximity to recreation facilities as determinants of physical activity and obesity in adolescents as measured by BMI, finding that BMI was not significantly related to these environmental variables (Kligerman et al., 2007). Norman et al. (2006), employing similar measures, also reported a lack of significant relationships between BMI and the built environment variables, as did Liu et al. (2006) and Burdette and Whitaker (2003), using somewhat different built-environment measures. Gordon-Larsen et al. (2006), in contrast, used distance to the nearest physical activity facility in a sample of 7th–12th grade adolescents to determine relationships between recreational facility proximity and obesity, finding significant links between absence or reduced access to facilities, decreased physical activity, and increased obesity in low socio-economic status and high minority neighborhoods.

Publicly-provided recreational programming is among the least studied determinant of physical activity and childhood obesity. Dahmann et al. (2010), in a cross-sectional study, audited recreation programs from southern California municipalities, finding that areas with higher population density, lower incomes, and a greater share of minority residents had inferior access to public recreational programming; but this study did not relate the distribution of recreational resources to either physical activity or obesity.

To assess the influence of parks and recreation, it is also necessary to include control for built environment variables that may be associated with the BMI and recreation programs or parks. The literature points to a wide range of factors in the built environment that may influence cardio-metabolic outcomes including obesity (Leal and Chaix, 2010). Dietary intake has direct links to obesity and might be associated with the availability of food resources such as supermarkets, restaurants, and fast-food outlets, along with family influences that may themselves be grounded in class, race/ethnicity, and cultural background (Charreire et al., 2010). Built environmental characteristics related to pollution exposure can be directly linked to the onset of acute and chronic health conditions such as asthma that limit physical activity (Jerrett et al., 2009, McConnell et al., 2010). Recent studies have also identified traffic density as a potential risk factor for obesity formation in children (Jerrett et al., 2010). Finally, the social conditions, such as poverty and unemployment, as well as crime, may also negatively influence park use and recreational program utilization and be related to obesity (Dahmann et al., 2010). In assessing the influence of parks and recreational programming, these variables must be taken into account in the modeling strategy.

Section snippets

Methods

We hypothesize that parklands and recreation programs are related to longitudinal obesity outcomes in children. To test this hypothesis, we developed a comprehensive inventory of recreation programming for a large cohort of children as well as an extensive array of other built environment, household, and individual variables that may confound associations between parks or recreational programming and BMI growth in children. We utilized multilevel growth curves to assess the associations between

Results

The cohort included 3173 children after data cleaning and elimination of outliers and missing values. Table 1 shows their BMI z-scores based on the Center for Disease Control classifications, showing variations across race, ethnicity, and gender.

The number of recreation programs accessible within 5 and 10 km buffers varied markedly from place to place. Access of children to programs within 5 km of their home was so limited that we focused exclusively on accessibility within 10 km (Fig. 4) for

Discussion and conclusions

The longitudinal analysis reveals the significant effect of parkland and publicly-provided recreation programs on attained BMI in a large cohort of children living in the 12 Southern California communities. Our research found almost 20% of these children had no access to recreation programs within 10 km, and over a third had no access within 5 km. Many children had very poor access to local parkland; over half had no park within 500 m of their homes.

This study breaks new ground, being the first to

Acknowledgements

This study was supported by NCI Centers for Transdisciplinary Research on Energetics and Cancer (TREC) (U54 CA 116848), the Robert Wood Johnson Foundation Grant (57279), the National Institute of Environmental Health Sciences (5P30 ES007048, 5P01ES011627, R01 ES016535), the National Institute of Health Grant (5R01CA123243-03), the US Environmental Protection Agency (R831845), and the Hastings Foundation. We acknowledge Mr. Bernardo Beckerman for assistance in preparing the geographic data and

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