Centre of Epidemiology and Biostatistics, Room 8.49, Worsley Building, University of Leeds, Leeds LS2 9JT, UK.
Arch Dis Child. 2010 Feb;95(2):94-9. doi: 10.1136/adc.2009.160267. Epub 2009 Nov 27.
The aim of this paper was to investigate variations in childhood obesity globally and spatially at the micro-level across Leeds.
Body mass index data from three sources were used. Children were aged 3-13 years. Obesity was defined as above the 98th centile (British reference dataset). The data were analysed by age group and gender, then tested for significant micro-level hot spots of childhood obesity using a spatial scan statistic and a two-level multilevel model.
Older children (13 years) were 2.5 times (95% CI 2.1 to 3.1) more likely to be obese than younger children (3 years). Childhood obesity was significantly associated with deprived and affluent areas. 'Blue collar communities,' 'Constrained by circumstances' and 'Multicultural' had significantly higher (relative risk (RR): 1.1, 1.2, 1.2; 95% CI 1.0 to 1.2, 1.1 to 1.2, 1.1 to 1.3, respectively) obesity levels, and 'Typical traits' and 'Prospering suburbs' had significantly lower (RR: 0.9, 0.8; 95% CI 0.8 to 1.0, 0.7 to 0.9, respectively) obesity levels. In the unadjusted model, obesity 'hot spots' were found in deprived (RR 1.5) and affluent (RR 6.1) areas. After adjusting for demographic covariates, hot spots were found only in affluent areas (RR 1.6 to 1.9), and cold spots in affluent (RR 1.3 to 4.4) and deprived (RR up to 1.1) areas.
These results suggest there is either a spread of obesity across socio-economic groups and/or something special about the high-/low-prevalence areas that affects the likelihood of obesity. The microlevel spatial analyses displayed the variations in obesity across Leeds thoroughly, identifying high-risk populations.
本文旨在研究全球范围内儿童肥胖的变化,并在利兹市的微观层面上对其进行空间分析。
使用了三种来源的体重指数数据。儿童年龄为 3-13 岁。肥胖定义为超过第 98 百分位数(英国参考数据集)。根据年龄组和性别对数据进行分析,然后使用空间扫描统计和两级多水平模型检验儿童肥胖的微观热点。
13 岁的大龄儿童肥胖的可能性是 3 岁儿童的 2.5 倍(95%置信区间 2.1 至 3.1)。儿童肥胖与贫困和富裕地区显著相关。“蓝领社区”、“受环境限制”和“多元文化”的肥胖水平显著较高(相对风险 (RR):1.1、1.2、1.2;95%置信区间 1.0 至 1.2、1.1 至 1.2、1.1 至 1.3),而“典型特征”和“繁荣郊区”的肥胖水平显著较低(RR:0.9、0.8;95%置信区间 0.8 至 1.0、0.7 至 0.9)。在未调整模型中,在贫困(RR 1.5)和富裕(RR 6.1)地区发现了肥胖“热点”。在调整人口统计学协变量后,仅在富裕地区发现了热点(RR 1.6 至 1.9),而在富裕(RR 1.3 至 4.4)和贫困(RR 最高 1.1)地区发现了冷点。
这些结果表明,肥胖在社会经济群体中的传播程度有所不同,或者高/低患病率地区存在某些特殊因素影响肥胖的可能性。微观空间分析彻底显示了利兹市肥胖的变化,确定了高危人群。