Recipient Organization
CONNECTING HEALTH INNOVATIONS, LLC
6049 ROBINWOOD RD
COLUMBIA,SC 29206
Performing Department
(N/A)
Non Technical Summary
Through this proposal we offer a literature-derived, population-based dietary inflammatory index (C-DII) developed to characterize children diets on a scale from maximally anti- to pro-inflammatory. Diet is a strong moderator of chronic systemic inflammation. This C-DII will be used as a basis to:• Direct school lunch programs towards foods that will reduce inflammatrion-associated health risks, such as obesity, while maintaining current school lunch program budgetary limitations. Anti-inflammatory diets include more options and thus may entail adding, not taking away, key food ingredients that reduce inflammation. Even a slight modification to a recipe may have a large impact on the inflammatory effects of a food item.• Develop and deliver food products that reduce inflammation. The team will work to identify a few key additional food items such as snack bars that taste great and reduce inflammation.• Help parents and children choose great-tasting, nutrient-dense and affordable foods that reduce obesity and inflammation.Dietary inflammation is at the heart of every major chronic health condition. Through diet, these conditions are completely preventable and reversible. School lunch programs are the largest single place where children obtain food. Addressing dietary inflammation within school cafeterias will create the largest potential impact on kids across our nation.The DII has been proven and documented as successful in adults. This SBIR proposal will modify a heavily researched and proven index for children.
Animal Health Component
(N/A)
Research Effort Categories
Basic
(N/A)
Applied
(N/A)
Developmental
100%
Goals / Objectives
The Dietary Inflammatory Index (DII) was developed and construct validated against inflammatory biomarkers specifically in adult populations.Additionally, the DII has been associated with a range of outcomes including various cancers, components of MetSyn, body habitus measures, asthma, bone mineral density, CVD, shiftwork, and mortality.However, these results are restricted to adult populations by nature of the calculation of the DII. An integral aspect of DII calculation is the standardization of the food parameters to a 'world' database.Therefore, its use among younger populations (e.g., 6-14 years) is limited. Several technical questions that need to be addressed to establish the technical feasibility of the DII among children include: 1) what datasets from around the world contain sufficient dietary information to create a 'world' standard database of food parameters for children, 2) do any of these datasets also contain inflammatory biomarkers, and 3) after creation of the standard database and calculation of the DII, does the DII predict inflammatory biomarkers (i.e., construct validation) among children. To address these questions, the following Specific Aims (SA) are being proposed:1. Create the 'world' standard database of food parameters among children and develop the C-DII. This would entail checking the literature to ensure that:there is no literature in children on diet and the six inflammatory markers we explored previously in adults (i.e., CRP, IL-1b, IL-4, IL-6, IL-10, TNF-α) that might result in a change to the article score, which forms an important foundation for computing the DII score; andwe will identify and acquire key datasets on diet in children from around the world. The absence of this information has been a major impediment for computing DII scores in children; so, this lies at the heart of what we intend to accomplish in creating the C-DII. It is encouraging to note that normalizing the DII in children will be facilitated by the fact that many countries conduct dietary surveys of youth .We will develop an overall global database, one that can be used across all age groups among children; we also will develop strata specific global database for different age groups because of the different dietary requirements among children in different strata. For this purpose we will develop a global database for three different age groups (<9, 9-12, >12 years), assuming sufficient world data is available for each age group.2. Examine the relationship between the C-DII and inflammatory biomarkers (e.g., CRP, IL-6, tumor necrosis factor (TNF)-α, and others depending on availability). This would entail identifying key datasets that contain both dietary information and inflammatory biomarkers among children by contacting current colleagues and by forming new collaborations from around the world. Considering this is a hypothesis-testing specific aim, we specifically hypothesize that:Children with more pro-inflammatory diets (i.e., higher C-DII scores) will have greater values of pro-inflammatory cytokines compared to children with lower C-DII scores.
Project Methods
The DII is comprised of various micro and macronutrients, as well as several individual food items, collectively known as food parameters (more negative scores represent more anti-inflammatory diets). The entire process of developing the DII is described elsewhere.Developing the DII involved reviewing and scoring nearly 2000 scientific articles representing cell culture and laboratory animal experiments, and a variety of human studies. From this careful review of the literature, 45 food parameters (consisting of micro and macronutrients, spices and whole foods) were identified as having a sufficiently robust literature relating to predict levels of six inflammatory markers (i.e., CRP, IL-1b, IL-4, IL-6, IL-10, TNF-α). Developing the DII also entailed creation of a world standard database that involved obtaining 11 data sets from around the world to which individuals' intakes of the 45 food parameters could be compared. Our goal here will be simply to assure that any adjustments needed on the basis of the age of the population of the human studies occurs and the DII scoring algorithm is modified accordingly. We understand that the limitation of the existing DII in children concerns the referent database. We know that there are manyyouth-oriented data sets (mainly from national / regional surveys) and that we will stratify results to create reference databases by age (e.g., ≤9 years, 9-12 years, >12 years). To calculate the C-DII, dietary data from participants within the study will be first linked to the previously described regionally representative world database that provided a robust estimate of a mean and standard deviation for each parameter. These then became the multipliers to express an individual's exposure relative to the "standard global mean" as a z-score. This score will be computed by subtracting the "standard global mean" from the amount reported and dividing this value by the "global standard deviation" of the world population. To minimize the effect of "right skewing", this value will be converted to a centered percentile score. For each individual food parameter, this score will then be multiplied by the respective food parameter effect score, derived from the previous literature review, in order to obtain a food parameter-specific DII score. All of the food parameter-specific DII scores will then then summed to create the overall DII score for every participant in the study,DII= b1*n1+b2*n2...........b45*n45, where b refers to the literature-derived inflammatory effects score for each of the evaluable food parameters and n refers to the food parameter-specific centered percentiles, which will be derived from any dietary data. Our Aim 1a will be directed at identifying if there are any data in children that would cause us to change the algorithm for article scoring.Constructing the "world database": Here we will first collect dietary data from various countries; in choosing these dietary data we will ensure a wide variation in the intake of these 45 food parameters that make up the DII; hence, we will try to include datasets from both developed countries and developing countries. We are in the process of collecting those datasets; we have contacted over 10 different studies all over the world including Africa, Asia and South America to gain their permission to use their data sets. We also will contact national and regional surveillance systems that routinely collect data on children's datary practices. The purpose of constructing this world database is to eliminate the role of units of measurement which are different for different food parameters. We have started contacting principal investigators of studies in different parts of the world involving dietary assessments in kids, we will continue this process. We will get appropriate approvals if required and follow the institutional procedures and receive various datasets. We will then calculate the means for each of the food parameters per 1000 kcal to account for variability of caloric intake. This will be followed by developing a composite database from all these datasets. This database will have means/1000 kcal of each of the 45 food parameters, unless we determine certain food parameters are not needed, for DII calculation. From the composite database we will develop a global database containing means and standard deviations for each food parameter across all the countries. We will ensure that we can account for age differences by having sufficient data within these age categories: ≤9 years, 9-12 years, >12 years. Once the world database is ready, we will then follow the steps similar to the adult DII.