Characterizing the Distribution of Macronutrient Intake among U.S. Adults: A Quantile Regression Approach
用分位数回归分析美国成年人宏量营养素摄入分布，发现年龄、教育和收入对高摄入水平（过量风险高）的影响大于低摄入水平。
Abstract Since the risk of dietary inadequacy or excess is greater at the tails of the nutrient intake distributions than at the mean, marginal effects of explanatory variables estimated at the conditional mean using ordinary least squares may be of limited value in characterizing these distributions. Quantile regression is effective in this situation since it can estimate conditional functions at any part of the distribution. Quantile regression results suggest that age, education, and income have a larger influence at intake levels where the risk of excess is greater compared with intake levels where the risk of excess is lower.