背景(考古学)
心理学
逻辑回归
课程
人口
环境卫生
读写能力
发展心理学
健康素养
医学
人口学
老年学
地理
医疗保健
教育学
社会学
经济
考古
内科学
经济增长
作者
Azam Doustmohammadian,Nastaran Keshavarz Mohammadi,Nasrin Omidvar,Maryam Amini,Morteza Abdollahi,Hassan Eini-Zinab,Zeinab Amirhamidi,Saeed Esfandiari,Don Nutbeam
标识
DOI:10.1093/heapro/day050
摘要
Summary This study used a locally designed and validated questionnaire to describe the distribution of food and nutrition literacy (FNLIT) in a cross-sectional sample of 803 students aged 10–12 years from elementary schools in Tehran city, Iran. Logistic regression was used to assess the extent to which various independent covariates were associated with low FNLIT. The data were used to identify significant differences using a range of social and cultural variables relevant to the context of school students in Iran. The results of the study showed that although the total FNLIT level was good, this headline finding masked important differences in the sub-domains. More than half of the children (69%) had high levels of FNLIT in the cognitive domain, but in the skills domain, very few (3%) scored highly. The study also identified some associations between the total FNLIT and its subscales and sociodemographic variables including gender, parent’s education and age, birth order. These results highlighted groups within the school population who were at higher risk of having lower FNLIT levels. They also indicate that girls feel more able to exert choice and control over food and nutrition decisions than boys are but may be less able to do so in practice. Overall, these results are a general reminder to schools of the different learning needs of children from different family backgrounds. The article highlights the need for continuous improvement in the health education curriculum of schools in Iran, particularly highlighting the importance of giving greater attention to the development of practical food and nutrition skills alongside more traditional food and nutrition knowledge. Additional studies (with long-term follow-up) are needed to more fully assess and understand the predictors of FNLIT.
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