Neuman Melissa, Kawachi Ichiro, Gortmaker Steven, Subramanian Sv
Department of Social and Behavioral Sciences, Harvard School of Public Health, Boston, Massachusetts, United States of America.
PLoS One. 2014 Jun 11;9(6):e99327. doi: 10.1371/journal.pone.0099327. eCollection 2014.
Increases in body mass index (BMI) and the prevalence of overweight in low- and middle income countries (LMICs) are often ascribed to changes in global trade patterns or increases in national income. These changes are likely to affect populations within LMICs differently based on their place of residence or socioeconomic status (SES).
Using nationally representative survey data from 38 countries and national economic indicators from the World Bank and other international organizations, we estimated ecological and multilevel models to assess the association between national levels of gross domestic product (GDP), foreign direct investment (FDI), and mean tariffs and BMI.
We used linear regression to estimate the ecological association between average annual change in economic indicators and BMI, and multilevel linear or ordered multinomial models to estimate associations between national economic indicators and individual BMI or over- and underweight. We also included cross-level interaction terms to highlight differences in the association of BMI with national economic indicators by type of residence or socioeconomic status (SES).
There was a positive but non-significant association of GDP and mean BMI. This positive association of GDP and BMI was greater among rural residents and the poor. There were no significant ecological associations between measures of trade openness and mean BMI, but FDI was positively associated with BMI among the poorest respondents and in rural areas and tariff levels were negatively associated with BMI among poor and rural respondents.
Measures of national income and trade openness have different associations with the BMI across populations within developing countries. These divergent findings underscore the complexity of the effects of development on health and the importance of considering how the health effects of "globalizing" economic and cultural trends are modified by individual-level wealth and residence.
低收入和中等收入国家(LMICs)的体重指数(BMI)增加以及超重患病率上升,通常归因于全球贸易模式的变化或国民收入的增加。基于居住地点或社会经济地位(SES),这些变化可能对低收入和中等收入国家的人群产生不同影响。
利用来自38个国家的具有全国代表性的调查数据以及世界银行和其他国际组织的国家经济指标,我们估计了生态模型和多层次模型,以评估国内生产总值(GDP)、外国直接投资(FDI)的国家水平以及平均关税与BMI之间的关联。
我们使用线性回归来估计经济指标的年均变化与BMI之间的生态关联,并使用多层次线性或有序多项模型来估计国家经济指标与个体BMI或超重和体重不足之间的关联。我们还纳入了跨层次交互项,以突出BMI与国家经济指标的关联在居住类型或社会经济地位(SES)方面的差异。
GDP与平均BMI之间存在正相关但不显著。GDP与BMI之间的这种正相关在农村居民和贫困人口中更大。贸易开放度指标与平均BMI之间没有显著的生态关联,但外国直接投资与最贫困受访者以及农村地区的BMI呈正相关,而关税水平与贫困和农村受访者的BMI呈负相关。
国民收入和贸易开放度指标与发展中国家不同人群的BMI存在不同关联。这些不同的研究结果强调了发展对健康影响的复杂性,以及考虑个人层面的财富和居住情况如何改变“全球化”经济和文化趋势对健康影响的重要性。