Discretizing continuous variables in nutrition and obesity research: a practice that needs to be cut short.

IF 4.6 2区 医学 Q1 ENDOCRINOLOGY & METABOLISM
Osvaldo F Morera, Mosi I Dane'el, Brandt A Smith, Alisha H Redelfs, Sarah L Ruiz, Kristopher J Preacher, Leah D Whigham
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Abstract

Background/objectives: Nutrition and obesity researchers often dichotomize or discretize continuous independent variables to conduct an analysis of variance to examine group differences. We describe consequences associated with dichotomizing and discretizing continuous variables using two cross-sectional studies related to nutrition.

Subjects/methods: Study 1 investigated the effects of health literacy and nutrition knowledge on nutrition label accuracy (n = 612). Study 2 investigated the effects of cognitive restraint and BMI on fruit and vegetable (F/V) intake (n = 586). We compare analytic approaches where continuous independent variables were either discretized/dichotomized or analyzed as continuous variables.

Results: In Study 1, dichotomization of health literacy and nutrition knowledge for 2 × 2 ANOVA revealed health literacy had an effect on nutrition label accuracy. Nutrition knowledge has an effect on nutrition label accuracy, but the health literacy by nutrition knowledge interaction was not significant. When analyzed using regression, the nutrition knowledge effect was significant. The simple effect of health literacy was also significant when health literacy equals zero. Finally, the quadratic effect of health literacy was negative and significant. In Study 2, dichotomization and discretization of cognitive restraint and BMI were used for three ANOVAs, which discretized BMI in three ways. For all ANOVAs, the BMI main effect for predicting fruit and vegetable intake was significant, the interaction between BMI and cognitive restraint was non-significant, and cognitive restraint was only significant when both variables were dichotomized. When analyzed using regression, the continuous mean-centered variables, and their interaction each significantly predicted F/V intake.

Conclusions: Dichotomizing continuous independent variables resulted in distortions of effect sizes across studies, an inability to assess the quadratic effect of health literacy, and an inability to detect the moderating effect of BMI. We discourage researchers from dichotomizing and discretizing continuous independent variables and instead use multiple regression to examine relationships between continuous independent and dependent variables.

Abstract Image

对营养和肥胖研究中的连续变量进行离散化:这是一种需要缩短的做法。
背景/目的:营养和肥胖研究人员经常对连续自变量进行二分或离散化,以进行方差分析来检验群体差异。我们使用两项与营养相关的横断面研究来描述与连续变量的二分法和离散化相关的后果。受试者/方法:研究1调查了健康素养和营养知识对营养标签准确性的影响(n = 612)。研究2调查了认知抑制和BMI对水果和蔬菜(F/V)摄入量(n = 586)。我们比较了将连续自变量离散化/二分化或作为连续变量进行分析的分析方法。结果:在研究1中,2名儿童的健康素养和营养知识的二分法 × 2方差分析显示健康素养对营养标签的准确性有影响。营养知识对营养标签准确性有影响,但营养知识交互作用下的健康素养不显著。当使用回归分析时,营养知识效应是显著的。当健康素养等于零时,健康素养的简单影响也很显著。最后,健康素养的二次效应是负面且显著的。在研究2中,认知约束和BMI的二分法和离散化被用于三个ANOVA,其以三种方式离散化BMI。对于所有方差分析,BMI对预测水果和蔬菜摄入量的主要影响是显著的,BMI和认知约束之间的相互作用是不显著的,只有当两个变量都被二分时,认知约束才是显著的。当使用回归分析时,以平均值为中心的连续变量及其相互作用都能显著预测F/V摄入量。结论:将连续自变量二分导致研究中效应大小的扭曲,无法评估健康素养的二次效应,也无法检测BMI的调节作用。我们不鼓励研究人员对连续自变量进行二分和离散化,而是使用多元回归来检验连续自变量和因变量之间的关系。
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来源期刊
Nutrition & Diabetes
Nutrition & Diabetes ENDOCRINOLOGY & METABOLISM-NUTRITION & DIETETICS
CiteScore
9.20
自引率
0.00%
发文量
50
审稿时长
>12 weeks
期刊介绍: Nutrition & Diabetes is a peer-reviewed, online, open access journal bringing to the fore outstanding research in the areas of nutrition and chronic disease, including diabetes, from the molecular to the population level.
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