Corsi Daniel J, Finlay Jocelyn E, Subramanian S V
Population Health Research Institute, McMaster University and Hamilton Health Sciences, Canada.
Soc Sci Med. 2012 Jul;75(2):311-22. doi: 10.1016/j.socscimed.2012.02.014. Epub 2012 Apr 10.
The extent to which body mass index (BMI) varies between small areas or neighborhoods in low- to middle-income countries (LMICs) remains unknown. Further, whether such variation is reflective of characteristics of individuals living in these neighborhoods is also not clear. We estimated the extent to which there is variation in BMI is attributable to neighborhoods in 57 LMICs. The data were from non-pregnant women of reproductive age (20-49 y) participating in Demographic and Health Surveys conducted in 57 countries between 1994 and 2008. Body mass index (BMI, weight [in kg] divided by height squared [in m(2)]) was used to assess weight status. Height and weight were measured objectively by trained field investigators. Age, household wealth, education were included as individual covariates and place of residence (urban or rural) as a neighborhood-level covariate. We conducted a multilevel analysis of 451,321 women (aged 20-49 y) from 32,814 neighborhoods and 57 countries. We used linear and multinomial models to partition the variation in BMI (in kg/m(2)), underweight (BMI <18.5 kg/m(2)) and overweight (BMI ≥25.0 kg/m(2)) at the level of neighborhoods and countries. We also explored the heterogeneity in neighborhood variation by socioeconomic status (SES). Of the total variation in BMI 17.6% was attributable to countries (Standard Deviation [SD] 2.0, 95% credible interval [CI] 1.7, 2.4) and 10.6% (SD 1.56, 95% CI 1.54, 1.58) was attributable to neighborhoods in age-adjusted models. Adjusting for individual- and neighborhood-level covariates reduced the SD attributable to countries and neighborhoods to 1.9, and 1.17, respectively. Between-country variation was 13.4% (SD 0.75, 95% CI 0.62-0.90) for underweight and 18.9% (SD 0.92, 95% CI 0.76-1.10) for overweight, and between-neighborhood variation was 7.7% (SD 0.57, 95% CI 0.55-0.58) for underweight and 7.1% (SD 0.56, 95% CI 0.55-0.58) for overweight in the fully-adjusted multinomial model. In country-specific models, the neighborhood variation in BMI ranged from 0.4 SD in Central African Republic to 2.7 SD in Sierra Leone in fully-adjusted models. Our results demonstrate a considerable range in neighborhood variation in BMI. In countries with greater neighborhood variation it is possible that BMI is being influenced by local conditions more than others with lesser neighborhood variation.
在低收入和中等收入国家（LMICs），小区域或社区之间的体重指数（BMI）差异程度仍不明确。此外，这种差异是否反映了生活在这些社区的个体特征也不清楚。我们估计了57个低收入和中等收入国家中，BMI差异可归因于社区的程度。数据来自1994年至2008年期间在57个国家参与人口与健康调查的育龄非孕妇（20 - 49岁）。体重指数（BMI，体重[千克]除以身高平方[米²]）用于评估体重状况。身高和体重由训练有素的现场调查人员客观测量。年龄、家庭财富、教育程度作为个体协变量，居住地（城市或农村）作为社区层面的协变量。我们对来自57个国家32,814个社区的451,321名女性（20 - 49岁）进行了多层次分析。我们使用线性和多项模型在社区和国家层面划分BMI（千克/米²）、体重过轻（BMI <18.5千克/米²）和超重（BMI≥25.0千克/米²）的差异。我们还按社会经济地位（SES）探讨了社区差异的异质性。在年龄调整模型中，BMI总差异的17.6%可归因于国家（标准差[SD] 2.0，95%可信区间[CI] 1.7, 2.4），10.6%（SD 1.56，95% CI 1.54, 1.58）可归因于社区。调整个体和社区层面的协变量后，可归因于国家和社区的标准差分别降至1.9和1.17。在完全调整的多项模型中，体重过轻的国家间差异为13.4%（SD 0.75，95% CI 0.62 - 0.90），超重为18.9%（SD （此处原文有误，应为0.92，95% CI 0.76 - 1.10））；体重过轻的社区间差异为7.7%（SD 0.57，95% CI 0.55 - 0.58），超重为7.1%（SD 0.56，95% CI 0.55 - 0.58）。在特定国家模型中，完全调整模型中BMI的社区差异范围从中非共和国的0.4 SD到塞拉利昂的2.7 SD。我们的结果表明BMI的社区差异范围相当大。在社区差异较大的国家，BMI受当地条件的影响可能比社区差异较小的国家更大。
