多水平模型在中国人群肥胖的省级社会影响因素分析中的应用

目的 采用多水平模型的方法探索中国人群省级水平社会因素对个体肥胖患病的影响。方法 采用多水平建模的方法，利用2007年慢性病与危险因素监测18~69岁人群数据作为研究结局和个体水平因素，收集国家统计局2007年分省年度数据，通过因子分析方法获得省级社会发展综合指标，分析其与个体体质指数（body mass index，BMI）、肥胖和中心性肥胖的关联关系。结果 2007年，全国范围内18～69岁人群的BMI平均值为（23.27±3.37）kg/m2，肥胖率为8.49%，中心性肥胖率为30.92%。从7个与社会经济、医疗卫生资源、生活环境有关的省级社会因素提取出2个省级水平因子作为各省社会发展综合指标，发现代表居民消费水平和医疗卫生资源充足程度的省级因子与个体BMI、肥胖、中心性肥胖的关联均无统计学意义（均有P>0.05），而代表社会经济综合发展程度的省级因子与个体BMI（OR=1.09，95% CI:1.04～1.10）、肥胖（OR=1.17，95% CI:1.07～1.28）、中心性肥胖（OR=1.19，95% CI:1.10～1.30）有正向的关联关系。结论 在中国，社会经济综合发展程度较好的地区，个体发生肥胖的风险可能较大。利用多水平模型探索影响个体肥胖等慢性病的地区社会因素，可为卫生政策制定者提供科学证据，引导卫生资源合理分配，具有重要公共卫生意义。

Application of multilevel models in analyzing on province-level social determinants of obesity in China

Objective To explore province-level social determinants of obesity in Chinese population, using multilevel analysis. Methods Information of individual outcomes and individual-level variables was acquired from data of Chronic Disease Risk Factor Surveillance in China, 2007, while province-level factors were extracted from 7 social indicators, which were obtained from data of National Bureau of Statistics, using factor analysis method. Then, multilevel models were built to calculate the correlations of province-level factors with body mass index (BMI), obesity and central obesity. Results Among the nationwide population aged 18-69 years in 2007, mean BMI level was (23.27±3.37) kg/m2, rate of obesity and central obesity was 8.49% and 30.92%, respectively. Two province-level factors were extracted from 7 social indicators, and factor 2, which represented the provincial social and economic comprehensive development level, was found positively correlated with BMI (OR=1.09, 95% CI:1.04-1.10), obesity (OR=1.17, 95% CI:1.07-1.28) and central obesity (OR=1.19, 95% CI:1.10-1.30), while factor 1, which represented the provincial level of residents' consumption and health service, wasn't found statistically correlated with these three outcomes(all P>0.05). Conclusions In China, higher provincial social-economic comprehensive development level might be a risk factor for individual obesity, especially central obesity, which indicated that limited resources for obesity prevention and control may need to be allocated to provinces or regions with higher economic development level. In conclusion, in order to provide more evidence on improving the efficiency of non-communicable diseases (NCDs) prevention and control and help the Chinese policy makers to allocate health resources more reasonably, multilevel models could be used to perform researches on area-level social-economic influencers of NCDs.