The role of landscape spatial patterns on obesity in Hispanic children residing in inner-city neighborhoods

J Phys Act Health. 2014 Nov;11(8):1449-57. doi: 10.1123/jpah.2012-0503. Epub 2013 Dec 31.

Abstract

Background: Childhood obesity and its comorbidities have become major public health challenges in the US. While previous studies have investigated the roles of land uses and transportation infrastructure on obesity, limited research has examined the influence of landscape spatial patterns. The purpose of this study was to examine the association between landscape spatial patterns and obesity in Hispanic children.

Methods: Participants included 61 fourth- and fifth-grade Hispanic children from inner-city neighborhoods in Houston, TX. BMI z-scores were computed based on objectively-measured height and weight from each child. Parental and child surveys provided sociodemographic and physical activity data. Landscape indices were used to measure the quality of landscape spatial patterns surrounding each child's home by utilizing Geographic Information Systems and remote sensing analyses using aerial photo images.

Results: After controlling for sociodemographic factors, in the half-mile airline buffer, more tree patches and well-connected landscape patterns were negatively correlated with their BMI z-scores. Furthermore, larger sizes of urban forests and tree patches were negatively associated with children's BMI z-scores in the half-mile network buffer assessment.

Conclusions: This study suggests that urban greenery requires further attention in studies aimed at identifying environmental features that reduce childhood obesity.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Body Mass Index
  • Body Weight
  • Child
  • Environment*
  • Female
  • Geographic Information Systems
  • Hispanic or Latino / statistics & numerical data
  • Humans
  • Male
  • Obesity / epidemiology*
  • Poverty Areas*
  • Residence Characteristics*
  • Trees
  • Waist-Height Ratio
  • White People / statistics & numerical data