重复测量的两种截然相反的健康消费可能性:含糖饮料和100%果汁

Faruk URAK
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引用次数: 0

摘要

对含糖果汁和100%果汁饮料消费量的测量通常是不完整的,而且往往以营养为重点,特别是在土耳其等发展中国家,公众对与过量食用SSB有关的健康风险的认识和认识有限,100%果汁摄入量的刺激水平也很低。在本研究中,在土耳其家庭异质性的背景下,使用随机效应双变量probit模型确定了个人和家庭的社会人口统计学、经济和生活方式特征对纯果汁(100% FJ)和含糖饮料(SSB)的不同消费概率的影响。从二元随机效应概率模型中推导出不同的概率,从而获得更丰富的信息来源。应用的模型与数据的相容性较好,检验的相关系数均有统计学意义。虽然大多数变量在统计上是显著的,但根据回归效应,在含糖饮用者中饮用100%果汁的概率被发现大于或小于从人群中随机选择的个体饮用100%果汁的概率(例如,边际概率)。在这种情况下,我们可以预期,不同人群参与的不同干预健康计划的实施将极大地促进理想结果的发展。此外,还提出了考虑到非常重要的变量的影响的政策建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Two Polar Opposite Health Consumption Possibilities For Repeated Measures: Sugar-Sweetened Drinks And 100% Fruit Juices
Measurement of consumption of sugar-sweetened and 100% fruit juice drinks is typically patchy and often nutritionally focused, particularly in developing countries such as Turkey, with limited public perception and awareness of the health risks associated with excessive SSB consumption, and a low stimulus level of 100% fruit juice intake. In the study, the effects of socio-demographic, economic, and lifestyle characteristics of individuals and households on their different consumption probabilities of pure fruit juice (100% FJ) and sugar-sweetened beverages (SSB) were determined using the random-effects bivariate probit model in the context of family heterogeneity in Turkey. A richer source of information was elicited by deriving different probabilities from the bivariate random effects probit model. The applied model was found to be more compatible with the data and all the correlation coefficients examined were statistically significant. While most of the variables were statistically significant, according to the regressor effect, the probability of consuming 100% fruit juice among sugar-sweetened intakers was found to be greater or less than the probability of consuming 100% fruit juice of a randomly selected individual from the population (e.g., marginal probability). In this context, we can expect that the implementation of distinct intervention health programs that will involve different population segments will contribute greatly to the development of ideal outcomes. In addition, policy recommendations were presented considering the effects of very important variables.
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