Developing a Dietary Lifestyle Ontology (DILON) to Improve the Interoperability of Dietary Data (Preprint)

2021 ◽  
Author(s):  
Hyeoneui Kim ◽  
Jinsun Jung ◽  
Jisung Choi
Keyword(s):  
Dietary Habits ◽  
Dietary Assessment ◽  
Dietary Habit ◽  
Assessment Data ◽  
Common Data Elements ◽  
Metadata Annotation ◽  
Data Elements ◽  
Concept Classes ◽  
Colloquial Style ◽  
Dietary Data

BACKGROUND Dietary habits offer crucial information on one's health and form a considerable part of the Patient-Generated Health Data (PGHD). Dietary data are collected through various channels and formats; thus, interoperability is a significant challenge to reusing the data. The vast scope of dietary concepts and colloquial style of expression add difficulty to the standardization task. Common Data Elements (CDE) with metadata annotation and ontological structuring of dietary concepts address the interoperability issues of dietary data to some extent. However, challenges remaining in making culture-specific dietary habits and questionnaire-based dietary assessment data interoperable require additional efforts. OBJECTIVE The main goal of this study was to address the interoperability challenge in dietary concepts by combining ontological curation of dietary concepts and metadata annotation of questionnaire-based dietary data. Specifically, this study aimed to develop a Dietary Lifestyle Ontology (DILON) and demonstrated the improved interoperability of questionnaire-based dietary data by annotating its main semantics with DILON. METHODS By analyzing 1158 dietary assessment data elements (367 in Korean and 791 in English), 515 dietary concepts were extracted and used to construct DILON. To demonstrate the utility of DILON in improving the interoperability of multi-cultural questionnaire-based dietary data, ten Competency Questions (CQs) were developed that identified data elements that share the same dietary topics and measurement qualities. As the test cases, 68 dietary habit data elements from Korean and English questionnaires were instantiated and annotated with the dietary concepts in DILON. The competency questions were translated into Semantic Query-enhanced Web Rule Language (SQWRL), and the query results were reviewed for accuracy. RESULTS DILON was built with 260 concept classes and 486 instances and successfully validated with ontology validation tools. A small overlap (72 concepts) in the concepts extracted from the questionnaires in two languages indicates the need to pay closer attention to representing culture-specific dietary concepts. The SQWRL queries reflecting the 10 CQs yielded the correct results. CONCLUSIONS Ensuring the interoperability of dietary lifestyle data is a demanding task due to its vast scope and variations in expression. This study demonstrated that, when combined with common data elements and semantic metadata annotation, ontology can effectively mediate the interoperability of dietary data generated in different cultural contexts and expressed in various styles.

scholarly journals Global Dietary Surveillance: Data Gaps and Challenges

2018 ◽  
Vol 39 (2) ◽  
pp. 175-205 ◽  
Author(s):  
Renata Micha ◽  
Jennifer Coates ◽  
Catherine Leclercq ◽  
U. Ruth Charrondiere ◽  
Dariush Mozaffarian
Keyword(s):  
Dietary Habits ◽  
Survey Design ◽  
Dietary Assessment ◽  
Data Availability ◽  
Dietary Biomarkers ◽  
Individual Level ◽  
Data Gaps ◽  
Nationally Representative ◽  
Dietary Surveillance ◽  
Dietary Data

Background: Detailed information on global individual-level consumption patterns is imperative for informed policy making. However, such data are dispersed and incomplete. Objective: To review and discuss the methodologies, observed data availability, challenges, and opportunities pertaining to global dietary surveillance. Methods: This investigation provides an extensive review of global dietary assessment methodologies and challenges, including at the survey level, the dietary collection and assessment level, and the dietary data processing and analysis level. The focus is on nationally representative individual-level data, and additional types of dietary data, such as dietary biomarkers, household assessment, and food availability, are reviewed as alternatives. Practical guidance is provided to inform key decisions when designing dietary surveys and collecting, analyzing, and using dietary data. This article further identifies and describes existing global and regional dietary initiatives/data sets. Results: Harmonized and standardized primary individual-level dietary data collection, processing, and analysis worldwide are currently not available. Evaluation and decision-making should be based on best available data, that is, secondary nonharmonized yet to the extent possible, standardized individual-level dietary data. Existing initiatives differ substantially in methodologies, including survey design/representativeness, coverage, diet assessment, and dietary metric standardization and processing. Data gaps have been identified that were more profound for certain countries, certain dietary indicators across countries, population subgroups, representativeness, or time periods. Conclusions: Optimizing worldwide dietary habits to improve population health requires systematically identified and evaluated data on a continuing basis. Leveraging existing available dietary data and efforts is an indispensable prerequisite for informed priority setting targeting the intersections between diet and disease.

scholarly journals TBI surveillance using the common data elements for traumatic brain injury: a population study

2013 ◽  
Vol 6 (1) ◽  
Author(s):  
Latha Ganti Stead ◽  
◽  
Aakash N Bodhit ◽  
Pratik Shashikant Patel ◽  
Yasamin Daneshvar ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Population Study ◽  
Common Data Elements ◽  
The Common ◽  
Data Elements

scholarly journals Energy, macronutrient and fatty acid intake of French elderly community dwellers and association with socio-demographic characteristics: data from the Bordeaux sample of the Three-City Study

2007 ◽  
Vol 98 (5) ◽  
pp. 1046-1057 ◽  
Author(s):  
Catherine Féart ◽  
Marthe A. Jutand ◽  
Sophie Larrieu ◽  
Luc Letenneur ◽  
Cécile Delcourt ◽  
...  
Keyword(s):  
Fatty Acid ◽  
Dietary Intake ◽  
Low Income ◽  
Educational Level ◽  
Dietary Habits ◽  
Dietary Assessment ◽  
The Elderly ◽  
Demographic Characteristics ◽  
Age Related ◽  
Total Fat

Few data are available regarding dietary habits of the elderly, in particular about fatty acid consumption, whereas these are major risk or protective factors of several age-related diseases. The aim of the present study was to characterise the dietary intake of a French elderly population in terms of energy, macronutrients and fatty acids based on their socio-demographic characteristics. The study population (age range 67·7–94·9 years) consisted of 1786 subjects from Bordeaux (France), included in the Three-City cohort. Dietary assessment was performed by a 24 h recall, allowing the estimation of energy, protein, carbohydrate, total fat, SFA, MUFA and PUFA intakes. Socio-demographic characteristics (age, sex, marital status, educational level and income), practice of sports and BMI were registered. Total energy intake (EI) was lower in women and in older participants ( ≥ 85 years) but higher in single subjects. Higher EI was associated with higher income, but not with educational level. Mean contribution of macronutrients to EI (protein 18 %, carbohydrate 46 % and total fat 31 %) was higher in women than men, except for alcohol. The oldest individuals consumed less protein and more mono- and disaccharides. Excess saturated fat intake (43 % of total fat), associated with a relative deficit in MUFA consumption (36 % of total fat), was observed. The mean 18 : 2n-6 : 18 : 3n-3 ratio was 9.9 and decreased with higher educational level. The present results suggest that being female, older age, being widowed and low income level could be considered as risk factors of inadequate dietary intake.

Abstract TP374: Data Linkage is Effective for Improving the Available Data for Stroke: An Example from the Australian Stroke Clinical Registry.

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Monique F Kilkenny ◽  
Helen M Dewey ◽  
Natasha A Lannin ◽  
Vijaya Sundararajan ◽  
Joyce Lim ◽  
...  
Keyword(s):  
Hospital Discharge ◽  
Hospital Discharge Data ◽  
Hospital Data ◽  
High Quality ◽  
Clinical Registry ◽  
Large Hospital ◽  
Common Data Elements ◽  
Discharge Data ◽  
Data Elements ◽  
Data Collections

Introduction: Multiple data collections can be a burden for clinicians. In 2009, the Australian Stroke Clinical Registry (AuSCR) was established by non-government and research organizations to provide quality of care data unavailable for acute stroke admissions. We show here the reliability of linking complimentary registry data with routinely collected hospital discharge data submitted to governmental bodies. Hypothesis: A high quality linkage with a > 90% rate is possible, but requires multiple personal identifiers common to each dataset. Methods: AuSCR identifying variables included date of birth (DoB), Medicare number, first name, surname, postcode, gender, hospital record number, hospital name and admission date. The Victorian Department of Health emergency department (ED) and hospital discharge linked dataset has most of these, with first name truncated to the first 3 digits, but no surname. Common data elements of AuSCR patients registered at a large hospital in Melbourne, Victoria (Australia) between 15 June 2009 and 31 December 2010 were submitted to undergo stepwise deterministic linkage. Results: The Victorian AuSCR sample had 818 records from 788 individuals. Three steps with 1) Medicare number, postcode, gender and DoB (80% matched); 2) hospital number/admit date; and 3) ED number/visit date were required to link AuSCR data with the ED and hospital discharge data. These led to an overall high quality linkage of >99% (782/788) of AuSCR patients, including 731/788 for ED records and 736/788 for hospital records. Conclusion: Multiple personal identifiers from registries are required to achieve reliable linkage to routinely collected hospital data. Benefits of these linked data include the ability to investigate a broader range of research questions than with a single dataset. Characters with spaces= 1941 (limit is 1950)

scholarly journals Preclinical common data elements (CDEs) for epilepsy: A joint ILAE/AES and NINDS translational initiative

2018 ◽  
Vol 3 ◽  
pp. 9-12 ◽  
Author(s):  
Helen E. Scharfman ◽  
Aristea S. Galanopoulou ◽  
Jacqueline A. French ◽  
Asla Pitkänen ◽  
Vicky Whittemore ◽  
...  
Keyword(s):  
Common Data Elements ◽  
Data Elements

scholarly journals Postmarketing Safety Study Tool: A Web Based, Dynamic, and Interoperable System for Postmarketing Drug Surveillance Studies

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
A. Anil Sinaci ◽  
Gokce B. Laleci Erturkmen ◽  
Suat Gonul ◽  
Mustafa Yuksel ◽  
Paolo Invernizzi ◽  
...  
Keyword(s):  
Clinical Research ◽  
Real Life ◽  
Critical Factor ◽  
Drug Surveillance ◽  
Safety Study ◽  
Data Interoperability ◽  
Common Data Elements ◽  
Lombardy Region ◽  
Research Activities ◽  
Data Elements

Postmarketing drug surveillance is a crucial aspect of the clinical research activities in pharmacovigilance and pharmacoepidemiology. Successful utilization of available Electronic Health Record (EHR) data can complement and strengthen postmarketing safety studies. In terms of the secondary use of EHRs, access and analysis of patient data across different domains are a critical factor; we address this data interoperability problem between EHR systems and clinical research systems in this paper. We demonstrate that this problem can be solved in an upper level with the use of common data elements in a standardized fashion so that clinical researchers can work with different EHR systems independently of the underlying information model. Postmarketing Safety Study Tool lets the clinical researchers extract data from different EHR systems by designing data collection set schemas through common data elements. The tool interacts with a semantic metadata registry through IHE data element exchange profile. Postmarketing Safety Study Tool and its supporting components have been implemented and deployed on the central data warehouse of the Lombardy region, Italy, which contains anonymized records of about 16 million patients with over 10-year longitudinal data on average. Clinical researchers in Roche validate the tool with real life use cases.

Dietary habit and other lifestyles and serum lipid profile of type 2 diabetes patients

2016 ◽  
Vol 46 (2) ◽  
pp. 161-170 ◽  
Author(s):  
Prince Chikwere ◽  
Reginald Adjetey Annan
Keyword(s):  
Type 2 Diabetes ◽  
Lipid Profile ◽  
Dietary Pattern ◽  
Dietary Habits ◽  
Activity Level ◽  
Dietary Habit ◽  
Content Type ◽  
Lifestyle Patterns ◽  
Diabetes Patients

Purpose – The purpose of this paper was to review evidence spanning the relation of dietary habits and other lifestyles to the lipid profile of type 2 diabetes patients. Design/methodology/approach – Search was done in PubMed, Biomed, Cochrane and Nutrition and Metabolism databases from 20 to 29 June 2013 for studies published on dietary intakes and lifestyle effect on lipid profile of type 2 diabetes patients. Findings – A total of 54 studies met the inclusion criteria for this review. These included observational, randomized control trials, prospective, cross-sectional and retrospective studies. Studies obtained covered macronutrients, micronutrients, dietary pattern, specific foods and lifestyle (alcohol intake, smoking, physical activity level and fasting). Research limitations/implications – The review did not consider unpublished articles/findings, and only studies in the English language and on humans were considered. Practical implications – The results of the review evidenced limited data on the lifestyle pattern of type 2 diabetes patients. Social implications – Dietary habits and other lifestyle patterns for a good lipid profile among type 2 diabetes patients have not been established. Originality/value – The review demonstrates the need for studies in dietary pattern and other lifestyle patterns in relation to lipid profile of type 2 diabetes patients.

scholarly journals A cross-sectional assessment of food- and nutrient-based standards applied to British schoolchildren’s packed lunches

2016 ◽  
Vol 20 (3) ◽  
pp. 565-570 ◽  
Author(s):  
Charlotte EL Evans ◽  
Janet E Cade
Keyword(s):  
Primary Schools ◽  
Assessment Tool ◽  
Dietary Assessment ◽  
Quality Score ◽  
Food Groups ◽  
Multilevel Regression ◽  
Optimal Model ◽  
Cross Sectional ◽  
The Uk ◽  
Dietary Data

AbstractObjectiveIn England, standards for school meals included both foods and nutrients until 2015. School policies for packed lunches are generally food based; research is needed to determine whether these are adequate or whether a small number of nutrients would potentially improve their quality.DesignFrom dietary data obtained using a weighed dietary assessment tool, a diet quality score (DQS) for packed lunches was calculated using the number of standards met out of twenty-one (eight foods and thirteen nutrients). Multilevel regression analysis determined the foods and nutrients contributing to variation in the DQS.SettingEighty-nine primary schools across the four regions of the UK (England, Wales, Scotland and Northern Ireland).SubjectsBritish schoolchildren (n 1294), aged 8–9 years, taking a packed lunch.ResultsThe optimal model included all eight foods and seven of the thirteen nutrients, explaining 72 % of the variance in DQS. Folate, Fe and vitamin C, together with the eight food groups, explained 70 % of DQS variation.ConclusionsIdeally, policies for school packed lunches should include food-based standards plus recommendations based on a small number of nutrients.

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