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Explained and unexplained regional variation in canadian obesity prevalence.

机译:解释和无法解释的加拿大肥胖患病率区域差异。

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The objective of our study was to examine sociodemographic and behavioral variables underlying the geographic variation of obesity in Canada. We aimed to quantify the share of regional variation in average BMI attributable to commonly cited determinants of obesity and the remaining share, which is attributable to the idiosyncrasies of the regional environment ("regional effects"). Using data from the Canadian Community Health Survey (CCHS) (2004), ordinary least squares (OLS) regression, and Blinder-Oaxaca decomposition to decompose the difference in mean BMI between regions, we quantify two parts of the difference: a share explained by different levels of the covariates and a share explained by those covariates having different effects on BMI in the different regions, using the Atlantic provinces as the reference group. We observed that some differences (e.g., average BMI for males in Quebec compared to the Atlantic provinces) are mostly explained by the different levels of socio-demographic and behavioral covariates, while others (e.g., average BMI for females in Quebec compared to the Atlantic provinces) are mostly explained by the different effects of the covariates on BMI. In the latter scenario, even if covariates were made to be identical in the different regions, the difference in average BMI would persist. Thus, targeting covariates in different regions through plans like physical activity or nutrition policy, income equalization, or education subsidies will have ambiguous effects for addressing disparate obesity levels, being plausible policy options in some regions but less so in others. Future research and policy would benefit from identifying these region-specific attributes that have local implications for BMI.
机译:我们研究的目的是研究加拿大肥胖的地理变异背后的社会人口统计学和行为变量。我们的目标是量化可归因于通常提到的肥胖决定因素的平均BMI中区域差异的份额,以及剩余的份额,这可归因于区域环境的特质(“区域效应”)。使用加拿大社区健康调查(CCHS)(2004),普通最小二乘(OLS)回归和Blinder-Oaxaca分解的数据分解区域之间的平均BMI差异,我们对差异的两个部分进行了量化:使用大西洋省作为参照组,不同水平的协变量以及由这些协变量解释的份额对不同地区的BMI有不同的影响。我们观察到,某些差异(例如,魁北克男性与大西洋省份的平均BMI)主要由社会人口统计学和行为协变量的不同水平来解释,而其他差异(例如,魁北克女性与大西洋地区的平均BMI相比)省份)的主要原因是协变量对BMI的不同影响。在后一种情况下,即使在不同区域使协变量相同,平均BMI的差异也将持续存在。因此,通过体育锻炼或营养政策,收入均等或教育补贴等计划来针对不同地区的协变量,将对解决不同的肥胖症水平产生歧义,这在某些地区是可行的政策选择,而在其他地区则不太可行。识别这些对BMI有局部影响的特定于地区的属性,将使未来的研究和政策受益。

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