Network Analysis of Demographics, Dietary Intake, and Comorbidity Interactions
The aim of this study was to elucidate the complex interrelationships among dietary intake, demographics, and the risk of comorbidities. We applied a Gaussian graphical model to calculate the dietary scores of the participants. The network structure of dietary intake, demographics, and comorbidities...
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| Veröffentlicht in: | Nutrients 2021-10, Vol.13 (10), p.3563 |
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| description | The aim of this study was to elucidate the complex interrelationships among dietary intake, demographics, and the risk of comorbidities. We applied a Gaussian graphical model to calculate the dietary scores of the participants. The network structure of dietary intake, demographics, and comorbidities was estimated in a mixed graphical model. The centrality indices of the nodes (strength (S), closeness (C), and betweenness (B)) were measured to identify the central node. Multinomial logistic regression was used to examine the association between the factors and comorbidities. Among 7423 participants, the strongest pairwise interactions were found between sex and smoking (1.56), sex and employment (0.66), sex and marital status (0.58), marital status and income (0.65), and age and employment (0.58). Among the factors in the network, sex played a central role (S = 4.63, C = 0.014, B = 41), followed by age (S = 2.81, C = 0.013, B = 18), smoking (S = 2.72, C = 0.013, B = 0), and employment (S = 2.17, C = 0.014, B = 22). While the odds of hypertension and diabetes were significantly higher among females than males, an inverse association was observed between high cholesterol and moderate chronic kidney disease. Among these factors, dietary intake was not a strongly interacting factor in the network, whereas age was consistently associated with the comorbidities of hypertension, high cholesterol, diabetes, and chronic kidney disease. |
| doi_str_mv | 10.3390/nu13103563 |
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We applied a Gaussian graphical model to calculate the dietary scores of the participants. The network structure of dietary intake, demographics, and comorbidities was estimated in a mixed graphical model. The centrality indices of the nodes (strength (S), closeness (C), and betweenness (B)) were measured to identify the central node. Multinomial logistic regression was used to examine the association between the factors and comorbidities. Among 7423 participants, the strongest pairwise interactions were found between sex and smoking (1.56), sex and employment (0.66), sex and marital status (0.58), marital status and income (0.65), and age and employment (0.58). Among the factors in the network, sex played a central role (S = 4.63, C = 0.014, B = 41), followed by age (S = 2.81, C = 0.013, B = 18), smoking (S = 2.72, C = 0.013, B = 0), and employment (S = 2.17, C = 0.014, B = 22). While the odds of hypertension and diabetes were significantly higher among females than males, an inverse association was observed between high cholesterol and moderate chronic kidney disease. Among these factors, dietary intake was not a strongly interacting factor in the network, whereas age was consistently associated with the comorbidities of hypertension, high cholesterol, diabetes, and chronic kidney disease.</description><identifier>ISSN: 2072-6643</identifier><identifier>EISSN: 2072-6643</identifier><identifier>DOI: 10.3390/nu13103563</identifier><identifier>PMID: 34684563</identifier><language>eng</language><publisher>Switzerland: MDPI AG</publisher><subject>Blood Glucose - metabolism ; Blood pressure ; Blood Pressure - physiology ; Body mass index ; Cholesterol ; Chronic illnesses ; Comorbidity ; Demographics ; Demography ; Diabetes ; Diabetes mellitus ; Diet ; Dietary intake ; Disease ; Eating ; Epidemiology ; Female ; Food ; Glomerular Filtration Rate ; Humans ; Hypertension ; Kidney diseases ; Kidneys ; Male ; Medical screening ; Middle Aged ; Network analysis ; Normal Distribution ; Nutrition research ; Questionnaires ; Sex ; Sex differences ; Smoking</subject><ispartof>Nutrients, 2021-10, Vol.13 (10), p.3563</ispartof><rights>2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). 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Lee, Jeonghee ; Kim, Jeongseon</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c406t-296776d87acfb4b3db888db468f734aef68bad38e32cccb1b3e7d4f652e864563</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Blood Glucose - metabolism</topic><topic>Blood pressure</topic><topic>Blood Pressure - physiology</topic><topic>Body mass index</topic><topic>Cholesterol</topic><topic>Chronic illnesses</topic><topic>Comorbidity</topic><topic>Demographics</topic><topic>Demography</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Diet</topic><topic>Dietary intake</topic><topic>Disease</topic><topic>Eating</topic><topic>Epidemiology</topic><topic>Female</topic><topic>Food</topic><topic>Glomerular Filtration Rate</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Kidney diseases</topic><topic>Kidneys</topic><topic>Male</topic><topic>Medical screening</topic><topic>Middle Aged</topic><topic>Network analysis</topic><topic>Normal Distribution</topic><topic>Nutrition research</topic><topic>Questionnaires</topic><topic>Sex</topic><topic>Sex differences</topic><topic>Smoking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hoang, Tung</creatorcontrib><creatorcontrib>Lee, Jeonghee</creatorcontrib><creatorcontrib>Kim, Jeongseon</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Physical Education Index</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nutrients</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hoang, Tung</au><au>Lee, Jeonghee</au><au>Kim, Jeongseon</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Network Analysis of Demographics, Dietary Intake, and Comorbidity Interactions</atitle><jtitle>Nutrients</jtitle><addtitle>Nutrients</addtitle><date>2021-10-12</date><risdate>2021</risdate><volume>13</volume><issue>10</issue><spage>3563</spage><pages>3563-</pages><issn>2072-6643</issn><eissn>2072-6643</eissn><abstract>The aim of this study was to elucidate the complex interrelationships among dietary intake, demographics, and the risk of comorbidities. 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| subjects | Blood Glucose - metabolism Blood pressure Blood Pressure - physiology Body mass index Cholesterol Chronic illnesses Comorbidity Demographics Demography Diabetes Diabetes mellitus Diet Dietary intake Disease Eating Epidemiology Female Food Glomerular Filtration Rate Humans Hypertension Kidney diseases Kidneys Male Medical screening Middle Aged Network analysis Normal Distribution Nutrition research Questionnaires Sex Sex differences Smoking |
| title | Network Analysis of Demographics, Dietary Intake, and Comorbidity Interactions |
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