1 University at Albany-State University of New York, Albany, NY, USA.
2 Institut Teknologi Bandung, Bandung, Indonesia.
Health Educ Behav. 2018 Aug;45(4):480-491. doi: 10.1177/1090198117742440. Epub 2017 Dec 26.
One third of school-aged children in New York State (NYS) are overweight or obese, with large geographic disparities across local regions. We used NYS student obesity surveillance data to assess whether these geographical variations are attributable to the built environment.
We combined NYS Student Weight Status Category Reporting System 2010-2012 data with other government publicly available data. Ordinary least squares regression models identified key determinants of school district-level student obesity rates for elementary and middle/high schools. Geographical weighted regression models explored spatial variations in local coefficients of the built environment predictors.
From ordinary least squares models, higher farmers' market density was only significantly associated with lower obesity rates among elementary school students (b = -0.116; p < .01). Higher fast-food restaurant density was significantly associated with higher obesity rates (b = 0.014; p < .05), and higher land use mix was only significantly associated with lower obesity rates (b = -0.054; p < .01) among middle/high school students. In geographical weighted regression analyses, the inverse association between market density and obesity rates among elementary school students was more pronounced in the eastern portion of the state. The relationship between higher fast-food restaurant density and higher obesity rates among middle/high school students was found in the southeastern portion of the state.
Different patterns of food consumption may explain varying determinants of obesity between younger and older students. Regional variations in local associations between the built environment variables and obesity may suggest differences in how healthy food sources are accessed locally.
纽约州（NYS）三分之一的学龄儿童超重或肥胖，当地各地区存在较大的地理差异。我们利用 NYS 学生肥胖监测数据来评估这些地理差异是否归因于建筑环境。
我们将 NYS 学生体重状况分类报告系统 2010-2012 年的数据与其他政府公开数据相结合。普通最小二乘法回归模型确定了小学和初中/高中学区学生肥胖率的主要决定因素。地理加权回归模型探讨了建筑环境预测因子的局部系数的空间变化。
从普通最小二乘法模型来看，农贸市场密度较高仅与小学生肥胖率较低显著相关（b = -0.116；p <.01）。快餐店密度较高与肥胖率较高显著相关（b = 0.014；p <.05），土地利用混合度较高仅与初中生肥胖率较低显著相关（b = -0.054；p <.01）。在地理加权回归分析中，农贸市场密度与小学生肥胖率之间的反比关系在该州东部更为明显。在该州东南部，快餐店密度较高与中学生肥胖率较高之间存在关系。
不同的食物消费模式可能解释了小学生和中学生肥胖的决定因素的差异。建筑环境变量与肥胖之间的局部关联在不同地区的差异可能表明当地获得健康食物来源的方式存在差异。
