Analysis and Comparison of Complex National Dietary Surveys by Statistical and Machine Learning: Methods and Applications in Nutritional Epidemiology
A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition Methodology & Assessment".
Deadline for manuscript submissions: closed (31 October 2020) | Viewed by 13445
Special Issue Editor
Interests: Chrononutritional epidemiology; dietary patterns; nutrition surveys; statistical methods; epidemiology of diabetes type II; obesity; food choice; genetic epidemiology
Special Issue Information
Dear Colleagues,
National dietary surveys produced by many countries have an important role in monitoring the nutritional status of populations across the world. Methodological challenges are often faced in the design and analysis of such surveys and with regard to their comparability across countries/regions/populations. Challenges about the design particularly concern low-middle income countries where limited resources, facilities and infrastructures may make it difficult to collect enough information to monitor the nutritional status of their populations and inform public health policies accordingly. In most countries, further challenges arise at the stage of data analyses, where the complex survey design is still often ignored while modern causal inference developments are not yet widely applied. Moreover, public health policies and/or comparison across countries or regions need to be based on synthesis of the data that might require dimension reduction of large datasets and dietary pattern exploration by statistical multivariate methods and machine learning techniques. This special issue is meant to deal with all the above mentioned issues and welcomes papers particularly on:
-Methods to identify dietary behaviour/nutritional patterns by multivariate statistical methods and/or machine learning methods with public health applications, e.g. to the comparisons of patterns across different countries/regions/populations or across time;
-Methods to predict or explain health outcomes based on dietary patterns derived from national nutrition survey data;
-Application of causal inference methodology to answer substantive nutrition questions from complex survey data from one or several countries/regions/populations.Dr. Luigi Palla
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Nutrients is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Complex survey design
- Dietary patterns
- Dietary indices
- Chrononutrition
- Cross-country diet comparison
- Machine learning
- Nutrition policies
