Ontology type: schema:MedicalStudy
2008-2023
ABSTRACTDietary intervention and other strategies to prevent unhealthy weight gain and the development of obesity should be based on knowledge of dietary, physiological, genetic and behavioral determinants and their contributing interactions. Identifying these determinants is difficult because physiological susceptibility to specific dietary and behavioral factors implicated in unhealthy weight gain differs between populations and individuals within the populations. The research challenge is identifying specific determinants in a free-living, adult population. Understanding the interaction between diet and the underlying susceptibility factors such as physiologic, genetic and epigenetic, and behavioral factors mandate an integrated approach. This integrated approach should include understanding the interplay of physiological factors (genetics, epigenetics, taste preferences, susceptibility to energy excess, etc.) and behavioral factors (food cravings, restraint, disinhibition, physical activity) as each of these domains is a potential driving force in energy expenditure, food preference, dietary choices, and food intake. Which of these factor(s) is most important? The investigators propose that by examining dietary, physiological, genetic, and behavioral factors in an integrated fashion we will gain insight into the obesity epidemic and identify the most important determinants of weight gain. As a secondary aim, the investigators will identify a single parsimonious collection of factors and develop strategies to mitigate the risks of developing obesity. Detailed Description This is a prospective, longitudinal, clinical study using an epidemiological approach. The sample consists of 90 free-living participants aged 20-35 years. The participants will undergo a series of assessments in the domains of diet, physiological factors, and behavioral factors at baseline and every 12 months for 2 years. OBJECTIVES 1. Identify dietary, physiological, genetic and behavioral determinants of unhealthy weight gain in healthy, young, ethnically-mixed men and women. 2. Identify relationships between genetic measures of taste perception and the determinants of unhealthy weight gain in the said population. 3. Identify relationships among the determinants of unhealthy weight gain that contribute to an individual's susceptibility to obesity. More... »
URL
JSON-LD is the canonical representation for SciGraph data.
TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT
[
{
"@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json",
"about": [
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/3136",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"type": "DefinedTerm"
},
{
"id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/3177",
"inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/",
"type": "DefinedTerm"
}
],
"description": "Dietary intervention and other strategies to prevent unhealthy weight gain and the development of obesity should be based on knowledge of dietary, physiological, genetic and behavioral determinants and their contributing interactions. Identifying these determinants is difficult because physiological susceptibility to specific dietary and behavioral factors implicated in unhealthy weight gain differs between populations and individuals within the populations. The research challenge is identifying specific determinants in a free-living, adult population. Understanding the interaction between diet and the underlying susceptibility factors such as physiologic, genetic and epigenetic, and behavioral factors mandate an integrated approach. This integrated approach should include understanding the interplay of physiological factors (genetics, epigenetics, taste preferences, susceptibility to energy excess, etc.) and behavioral factors (food cravings, restraint, disinhibition, physical activity) as each of these domains is a potential driving force in energy expenditure, food preference, dietary choices, and food intake. Which of these factor(s) is most important? The investigators propose that by examining dietary, physiological, genetic, and behavioral factors in an integrated fashion we will gain insight into the obesity epidemic and identify the most important determinants of weight gain. As a secondary aim, the investigators will identify a single parsimonious collection of factors and develop strategies to mitigate the risks of developing obesity.\n\nDetailed Description\nThis is a prospective, longitudinal, clinical study using an epidemiological approach. The sample consists of 90 free-living participants aged 20-35 years. The participants will undergo a series of assessments in the domains of diet, physiological factors, and behavioral factors at baseline and every 12 months for 2 years. OBJECTIVES 1. Identify dietary, physiological, genetic and behavioral determinants of unhealthy weight gain in healthy, young, ethnically-mixed men and women. 2. Identify relationships between genetic measures of taste perception and the determinants of unhealthy weight gain in the said population. 3. Identify relationships among the determinants of unhealthy weight gain that contribute to an individual's susceptibility to obesity.",
"endDate": "2023-08-01T00:00:00Z",
"id": "sg:clinicaltrial.NCT00945633",
"keywords": [
"predictor",
"Young",
"mixed population",
"dietary intervention",
"weight gain",
"development",
"obesity",
"behavioral determinant",
"determinant",
"susceptibility",
"behavioral factor",
"population",
"individual",
"research challenge",
"specific determinant",
"free-living",
"adult population",
"diet",
"susceptibility factor",
"integrated approach",
"interplay",
"physiological factor",
"genetics",
"Epigenomics",
"taste preference",
"energy",
"food craving",
"restraint",
"disinhibition",
"Motor Activity",
"domain",
"Energy Metabolism",
"food preference",
"dietary choice",
"Eating",
"integrated fashion",
"important determinant",
"secondary aim",
"collection",
"risk",
"clinical study",
"epidemiological approach",
"sample",
"assessment",
"baseline",
"objective 1",
"Identify",
"men",
"woman",
"taste perception"
],
"name": "Dietary, Physiological, Genetic, and Behavioral Predictors of Health in a Young, Ethnically-Mixed Population",
"sameAs": [
"https://app.dimensions.ai/details/clinical_trial/NCT00945633"
],
"sdDataset": "clinical_trials",
"sdDatePublished": "2019-03-07T15:23",
"sdLicense": "https://scigraph.springernature.com/explorer/license/",
"sdPublisher": {
"name": "Springer Nature - SN SciGraph project",
"type": "Organization"
},
"sdSource": "file:///pack/app/us_ct_data_00007.json",
"sponsor": [
{
"id": "https://www.grid.ac/institutes/grid.250514.7",
"type": "Organization"
}
],
"startDate": "2008-06-01T00:00:00Z",
"subjectOf": [
{
"id": "https://doi.org/10.1002/oby.21567",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1004549121"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1139/h2012-097",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1013123635"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/ijo.2013.153",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1019474055",
"https://doi.org/10.1038/ijo.2013.153"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.3945/ajcn.113.079566",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1030346154"
],
"type": "CreativeWork"
},
{
"id": "sg:pub.10.1038/srep01182",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1048687646",
"https://doi.org/10.1038/srep01182"
],
"type": "CreativeWork"
},
{
"id": "https://doi.org/10.1016/j.appet.2013.03.005",
"sameAs": [
"https://app.dimensions.ai/details/publication/pub.1050245542"
],
"type": "CreativeWork"
}
],
"type": "MedicalStudy",
"url": "https://clinicaltrials.gov/show/NCT00945633"
}
]
Download the RDF metadata as: json-ld nt turtle xml License info
JSON-LD is a popular format for linked data which is fully compatible with JSON.
curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/clinicaltrial.NCT00945633'
N-Triples is a line-based linked data format ideal for batch operations.
curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/clinicaltrial.NCT00945633'
Turtle is a human-readable linked data format.
curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/clinicaltrial.NCT00945633'
RDF/XML is a standard XML format for linked data.
curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/clinicaltrial.NCT00945633'
This table displays all metadata directly associated to this object as RDF triples.
92 TRIPLES
16 PREDICATES
72 URIs
59 LITERALS
1 BLANK NODES
Subject | Predicate | Object | |
---|---|---|---|
1 | sg:clinicaltrial.NCT00945633 | schema:about | anzsrc-for:3136 |
2 | ″ | ″ | anzsrc-for:3177 |
3 | ″ | schema:description | Dietary intervention and other strategies to prevent unhealthy weight gain and the development of obesity should be based on knowledge of dietary, physiological, genetic and behavioral determinants and their contributing interactions. Identifying these determinants is difficult because physiological susceptibility to specific dietary and behavioral factors implicated in unhealthy weight gain differs between populations and individuals within the populations. The research challenge is identifying specific determinants in a free-living, adult population. Understanding the interaction between diet and the underlying susceptibility factors such as physiologic, genetic and epigenetic, and behavioral factors mandate an integrated approach. This integrated approach should include understanding the interplay of physiological factors (genetics, epigenetics, taste preferences, susceptibility to energy excess, etc.) and behavioral factors (food cravings, restraint, disinhibition, physical activity) as each of these domains is a potential driving force in energy expenditure, food preference, dietary choices, and food intake. Which of these factor(s) is most important? The investigators propose that by examining dietary, physiological, genetic, and behavioral factors in an integrated fashion we will gain insight into the obesity epidemic and identify the most important determinants of weight gain. As a secondary aim, the investigators will identify a single parsimonious collection of factors and develop strategies to mitigate the risks of developing obesity. Detailed Description This is a prospective, longitudinal, clinical study using an epidemiological approach. The sample consists of 90 free-living participants aged 20-35 years. The participants will undergo a series of assessments in the domains of diet, physiological factors, and behavioral factors at baseline and every 12 months for 2 years. OBJECTIVES 1. Identify dietary, physiological, genetic and behavioral determinants of unhealthy weight gain in healthy, young, ethnically-mixed men and women. 2. Identify relationships between genetic measures of taste perception and the determinants of unhealthy weight gain in the said population. 3. Identify relationships among the determinants of unhealthy weight gain that contribute to an individual's susceptibility to obesity. |
4 | ″ | schema:endDate | 2023-08-01T00:00:00Z |
5 | ″ | schema:keywords | Eating |
6 | ″ | ″ | Energy Metabolism |
7 | ″ | ″ | Epigenomics |
8 | ″ | ″ | Identify |
9 | ″ | ″ | Motor Activity |
10 | ″ | ″ | Young |
11 | ″ | ″ | adult population |
12 | ″ | ″ | assessment |
13 | ″ | ″ | baseline |
14 | ″ | ″ | behavioral determinant |
15 | ″ | ″ | behavioral factor |
16 | ″ | ″ | clinical study |
17 | ″ | ″ | collection |
18 | ″ | ″ | determinant |
19 | ″ | ″ | development |
20 | ″ | ″ | diet |
21 | ″ | ″ | dietary choice |
22 | ″ | ″ | dietary intervention |
23 | ″ | ″ | disinhibition |
24 | ″ | ″ | domain |
25 | ″ | ″ | energy |
26 | ″ | ″ | epidemiological approach |
27 | ″ | ″ | food craving |
28 | ″ | ″ | food preference |
29 | ″ | ″ | free-living |
30 | ″ | ″ | genetics |
31 | ″ | ″ | important determinant |
32 | ″ | ″ | individual |
33 | ″ | ″ | integrated approach |
34 | ″ | ″ | integrated fashion |
35 | ″ | ″ | interplay |
36 | ″ | ″ | men |
37 | ″ | ″ | mixed population |
38 | ″ | ″ | obesity |
39 | ″ | ″ | objective 1 |
40 | ″ | ″ | physiological factor |
41 | ″ | ″ | population |
42 | ″ | ″ | predictor |
43 | ″ | ″ | research challenge |
44 | ″ | ″ | restraint |
45 | ″ | ″ | risk |
46 | ″ | ″ | sample |
47 | ″ | ″ | secondary aim |
48 | ″ | ″ | specific determinant |
49 | ″ | ″ | susceptibility |
50 | ″ | ″ | susceptibility factor |
51 | ″ | ″ | taste perception |
52 | ″ | ″ | taste preference |
53 | ″ | ″ | weight gain |
54 | ″ | ″ | woman |
55 | ″ | schema:name | Dietary, Physiological, Genetic, and Behavioral Predictors of Health in a Young, Ethnically-Mixed Population |
56 | ″ | schema:sameAs | https://app.dimensions.ai/details/clinical_trial/NCT00945633 |
57 | ″ | schema:sdDatePublished | 2019-03-07T15:23 |
58 | ″ | schema:sdLicense | https://scigraph.springernature.com/explorer/license/ |
59 | ″ | schema:sdPublisher | N4dd64cd25c3c4d9c9acc289c572b8f56 |
60 | ″ | schema:sponsor | https://www.grid.ac/institutes/grid.250514.7 |
61 | ″ | schema:startDate | 2008-06-01T00:00:00Z |
62 | ″ | schema:subjectOf | sg:pub.10.1038/ijo.2013.153 |
63 | ″ | ″ | sg:pub.10.1038/srep01182 |
64 | ″ | ″ | https://doi.org/10.1002/oby.21567 |
65 | ″ | ″ | https://doi.org/10.1016/j.appet.2013.03.005 |
66 | ″ | ″ | https://doi.org/10.1139/h2012-097 |
67 | ″ | ″ | https://doi.org/10.3945/ajcn.113.079566 |
68 | ″ | schema:url | https://clinicaltrials.gov/show/NCT00945633 |
69 | ″ | sgo:license | sg:explorer/license/ |
70 | ″ | sgo:sdDataset | clinical_trials |
71 | ″ | rdf:type | schema:MedicalStudy |
72 | N4dd64cd25c3c4d9c9acc289c572b8f56 | schema:name | Springer Nature - SN SciGraph project |
73 | ″ | rdf:type | schema:Organization |
74 | anzsrc-for:3136 | schema:inDefinedTermSet | anzsrc-for: |
75 | ″ | rdf:type | schema:DefinedTerm |
76 | anzsrc-for:3177 | schema:inDefinedTermSet | anzsrc-for: |
77 | ″ | rdf:type | schema:DefinedTerm |
78 | sg:pub.10.1038/ijo.2013.153 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1019474055 |
79 | ″ | ″ | https://doi.org/10.1038/ijo.2013.153 |
80 | ″ | rdf:type | schema:CreativeWork |
81 | sg:pub.10.1038/srep01182 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1048687646 |
82 | ″ | ″ | https://doi.org/10.1038/srep01182 |
83 | ″ | rdf:type | schema:CreativeWork |
84 | https://doi.org/10.1002/oby.21567 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1004549121 |
85 | ″ | rdf:type | schema:CreativeWork |
86 | https://doi.org/10.1016/j.appet.2013.03.005 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1050245542 |
87 | ″ | rdf:type | schema:CreativeWork |
88 | https://doi.org/10.1139/h2012-097 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1013123635 |
89 | ″ | rdf:type | schema:CreativeWork |
90 | https://doi.org/10.3945/ajcn.113.079566 | schema:sameAs | https://app.dimensions.ai/details/publication/pub.1030346154 |
91 | ″ | rdf:type | schema:CreativeWork |
92 | https://www.grid.ac/institutes/grid.250514.7 | ″ | schema:Organization |