A structural equation modeling approach for the association of a healthy eating index with metabolic syndrome and cardio-metabolic risk factors among obese individuals
Numerous studies have evaluated the association between dietary factors and cardiovascular risk among patients with chronic disease. It is worthwhile to assess these associations in a combination model rather than in an isolated form. In the current study, we aimed to use structural equation modelin...
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| Veröffentlicht in: | PloS one 2019-07, Vol.14 (7), p.e0219193-e0219193 |
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| creator | Khodarahmi, Mahdieh Asghari-Jafarabadi, Mohammad Abbasalizad Farhangi, Mahdieh |
| description | Numerous studies have evaluated the association between dietary factors and cardiovascular risk among patients with chronic disease. It is worthwhile to assess these associations in a combination model rather than in an isolated form. In the current study, we aimed to use structural equation modeling (SEM) to assess the association of adherence to a healthy eating index (HEI)-2015 with socio-demographic factors, psychological characteristics, metabolic syndrome (MetS) and other cardio-metabolic risk factors among obese individuals.
This cross-sectional study was conducted among 188 healthy obese adults (96 males and 92 females) aged 20-50 years in Tabriz. A validated semi-quantitative food frequency questionnaire (FFQ) was used to record dietary intake and to estimate HEI-2015. Anthropometric parameters, blood pressure and biochemical measurements were evaluated according to standard protocols. Interrelationships among socio-demographic parameters and HEI with cardio-metabolic risk factors were analyzed using SEM.
The results of SEM analysis revealed that HEI mediated the association between age and several cardio-metabolic risk factors including fat mass (FM), fat free mass (FFM), systolic blood pressure (SBP) and high-density lipoprotein (HDL) (p < 0.05). Moreover, adherence to Dietary Guidelines for Americans (DGA) appears to mediate association between gender and waist circumference (B = -9.78), SBP (B = -4.83), triglyceride (B = -13.01) and HDL (B = 4.31). HEI also mediated indirect negative effects of socioeconomic status on FM (B = -0.56), FFM (B = -0.25), SBP (B = -0.55) and diastolic blood pressure (DBP) (B = -0.3). Additionally, depression and age had indirect unfavorable effects on some insulin resistance indices such as homeostasis model assessment of insulin resistance (B = 0.07; p |
| doi_str_mv | 10.1371/journal.pone.0219193 |
| format | Article |
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This cross-sectional study was conducted among 188 healthy obese adults (96 males and 92 females) aged 20-50 years in Tabriz. A validated semi-quantitative food frequency questionnaire (FFQ) was used to record dietary intake and to estimate HEI-2015. Anthropometric parameters, blood pressure and biochemical measurements were evaluated according to standard protocols. Interrelationships among socio-demographic parameters and HEI with cardio-metabolic risk factors were analyzed using SEM.
The results of SEM analysis revealed that HEI mediated the association between age and several cardio-metabolic risk factors including fat mass (FM), fat free mass (FFM), systolic blood pressure (SBP) and high-density lipoprotein (HDL) (p < 0.05). Moreover, adherence to Dietary Guidelines for Americans (DGA) appears to mediate association between gender and waist circumference (B = -9.78), SBP (B = -4.83), triglyceride (B = -13.01) and HDL (B = 4.31). HEI also mediated indirect negative effects of socioeconomic status on FM (B = -0.56), FFM (B = -0.25), SBP (B = -0.55) and diastolic blood pressure (DBP) (B = -0.3). Additionally, depression and age had indirect unfavorable effects on some insulin resistance indices such as homeostasis model assessment of insulin resistance (B = 0.07; p<0.05, for age) and quantitative insulin sensitivity check index (p<0.05, for age and depression) via HEI. High adherence to HEI was found to be inversely associated with MetS risk (p<0.05).
Adherence to HEI-2015 seems to mediate the effect of socio-demographic parameters and mental health on cardio-metabolic risk factors as well as MetS risk. Further studies are needed to confirm these findings.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0219193</identifier><identifier>PMID: 31260504</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Age ; Anthropometry ; Biology and Life Sciences ; Blood pressure ; Body fat ; Cardiovascular diseases ; Cardiovascular Diseases - epidemiology ; Cardiovascular Diseases - etiology ; Cardiovascular Diseases - prevention & control ; Chronic diseases ; Chronic illnesses ; Cross-Sectional Studies ; Demographic aspects ; Demographics ; Diet ; Diet, Healthy - standards ; Diet, Healthy - statistics & numerical data ; Dietary intake ; Feeding Behavior ; Female ; Females ; Food and nutrition ; Food habits ; Health aspects ; Health risks ; High density lipoprotein ; Homeostasis ; Humans ; Insulin ; Insulin resistance ; Latent Class Analysis ; Male ; Males ; Mathematical models ; Medical research ; Medicine and Health Sciences ; Mental depression ; Mental disorders ; Mental health ; Metabolic diseases ; Metabolic disorders ; Metabolic syndrome ; Metabolic Syndrome - epidemiology ; Metabolic Syndrome - etiology ; Metabolic Syndrome - prevention & control ; Middle Aged ; Modelling ; Models, Biological ; Nutrition Policy ; Nutrition research ; Nutritional requirements ; Obesity ; Obesity - complications ; Obesity - diet therapy ; Obesity - metabolism ; Overweight persons ; Parameter estimation ; Patient Compliance - statistics & numerical data ; Psychological aspects ; Risk analysis ; Risk assessment ; Risk Assessment - methods ; Risk Factors ; Social class ; Socioeconomic Factors ; Socioeconomics ; Structural equation modeling ; Surveys and Questionnaires - statistics & numerical data ; Systematic review ; Triglycerides ; Type 2 diabetes ; Young Adult</subject><ispartof>PloS one, 2019-07, Vol.14 (7), p.e0219193-e0219193</ispartof><rights>COPYRIGHT 2019 Public Library of Science</rights><rights>2019 Khodarahmi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2019 Khodarahmi et al 2019 Khodarahmi et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-772e904a845e72f85cdc9c33c8c986293223469f3fbc98285ec7044f6ace55be3</citedby><cites>FETCH-LOGICAL-c692t-772e904a845e72f85cdc9c33c8c986293223469f3fbc98285ec7044f6ace55be3</cites><orcidid>0000-0002-7036-6900</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602284/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC6602284/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31260504$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Busija, Lucy</contributor><creatorcontrib>Khodarahmi, Mahdieh</creatorcontrib><creatorcontrib>Asghari-Jafarabadi, Mohammad</creatorcontrib><creatorcontrib>Abbasalizad Farhangi, Mahdieh</creatorcontrib><title>A structural equation modeling approach for the association of a healthy eating index with metabolic syndrome and cardio-metabolic risk factors among obese individuals</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Numerous studies have evaluated the association between dietary factors and cardiovascular risk among patients with chronic disease. It is worthwhile to assess these associations in a combination model rather than in an isolated form. In the current study, we aimed to use structural equation modeling (SEM) to assess the association of adherence to a healthy eating index (HEI)-2015 with socio-demographic factors, psychological characteristics, metabolic syndrome (MetS) and other cardio-metabolic risk factors among obese individuals.
This cross-sectional study was conducted among 188 healthy obese adults (96 males and 92 females) aged 20-50 years in Tabriz. A validated semi-quantitative food frequency questionnaire (FFQ) was used to record dietary intake and to estimate HEI-2015. Anthropometric parameters, blood pressure and biochemical measurements were evaluated according to standard protocols. Interrelationships among socio-demographic parameters and HEI with cardio-metabolic risk factors were analyzed using SEM.
The results of SEM analysis revealed that HEI mediated the association between age and several cardio-metabolic risk factors including fat mass (FM), fat free mass (FFM), systolic blood pressure (SBP) and high-density lipoprotein (HDL) (p < 0.05). Moreover, adherence to Dietary Guidelines for Americans (DGA) appears to mediate association between gender and waist circumference (B = -9.78), SBP (B = -4.83), triglyceride (B = -13.01) and HDL (B = 4.31). HEI also mediated indirect negative effects of socioeconomic status on FM (B = -0.56), FFM (B = -0.25), SBP (B = -0.55) and diastolic blood pressure (DBP) (B = -0.3). Additionally, depression and age had indirect unfavorable effects on some insulin resistance indices such as homeostasis model assessment of insulin resistance (B = 0.07; p<0.05, for age) and quantitative insulin sensitivity check index (p<0.05, for age and depression) via HEI. High adherence to HEI was found to be inversely associated with MetS risk (p<0.05).
Adherence to HEI-2015 seems to mediate the effect of socio-demographic parameters and mental health on cardio-metabolic risk factors as well as MetS risk. Further studies are needed to confirm these findings.</description><subject>Adult</subject><subject>Age</subject><subject>Anthropometry</subject><subject>Biology and Life Sciences</subject><subject>Blood pressure</subject><subject>Body fat</subject><subject>Cardiovascular diseases</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>Cardiovascular Diseases - etiology</subject><subject>Cardiovascular Diseases - prevention & control</subject><subject>Chronic diseases</subject><subject>Chronic illnesses</subject><subject>Cross-Sectional Studies</subject><subject>Demographic aspects</subject><subject>Demographics</subject><subject>Diet</subject><subject>Diet, Healthy - standards</subject><subject>Diet, Healthy - statistics & numerical data</subject><subject>Dietary intake</subject><subject>Feeding Behavior</subject><subject>Female</subject><subject>Females</subject><subject>Food and nutrition</subject><subject>Food habits</subject><subject>Health aspects</subject><subject>Health risks</subject><subject>High density lipoprotein</subject><subject>Homeostasis</subject><subject>Humans</subject><subject>Insulin</subject><subject>Insulin resistance</subject><subject>Latent Class Analysis</subject><subject>Male</subject><subject>Males</subject><subject>Mathematical models</subject><subject>Medical research</subject><subject>Medicine and Health Sciences</subject><subject>Mental depression</subject><subject>Mental disorders</subject><subject>Mental health</subject><subject>Metabolic diseases</subject><subject>Metabolic disorders</subject><subject>Metabolic syndrome</subject><subject>Metabolic Syndrome - epidemiology</subject><subject>Metabolic Syndrome - etiology</subject><subject>Metabolic Syndrome - prevention & control</subject><subject>Middle Aged</subject><subject>Modelling</subject><subject>Models, Biological</subject><subject>Nutrition Policy</subject><subject>Nutrition research</subject><subject>Nutritional requirements</subject><subject>Obesity</subject><subject>Obesity - complications</subject><subject>Obesity - diet therapy</subject><subject>Obesity - metabolism</subject><subject>Overweight persons</subject><subject>Parameter estimation</subject><subject>Patient Compliance - statistics & numerical data</subject><subject>Psychological aspects</subject><subject>Risk analysis</subject><subject>Risk assessment</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Social class</subject><subject>Socioeconomic Factors</subject><subject>Socioeconomics</subject><subject>Structural equation modeling</subject><subject>Surveys and Questionnaires - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Khodarahmi, Mahdieh</au><au>Asghari-Jafarabadi, Mohammad</au><au>Abbasalizad Farhangi, Mahdieh</au><au>Busija, Lucy</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A structural equation modeling approach for the association of a healthy eating index with metabolic syndrome and cardio-metabolic risk factors among obese individuals</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2019-07-01</date><risdate>2019</risdate><volume>14</volume><issue>7</issue><spage>e0219193</spage><epage>e0219193</epage><pages>e0219193-e0219193</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Numerous studies have evaluated the association between dietary factors and cardiovascular risk among patients with chronic disease. It is worthwhile to assess these associations in a combination model rather than in an isolated form. In the current study, we aimed to use structural equation modeling (SEM) to assess the association of adherence to a healthy eating index (HEI)-2015 with socio-demographic factors, psychological characteristics, metabolic syndrome (MetS) and other cardio-metabolic risk factors among obese individuals.
This cross-sectional study was conducted among 188 healthy obese adults (96 males and 92 females) aged 20-50 years in Tabriz. A validated semi-quantitative food frequency questionnaire (FFQ) was used to record dietary intake and to estimate HEI-2015. Anthropometric parameters, blood pressure and biochemical measurements were evaluated according to standard protocols. Interrelationships among socio-demographic parameters and HEI with cardio-metabolic risk factors were analyzed using SEM.
The results of SEM analysis revealed that HEI mediated the association between age and several cardio-metabolic risk factors including fat mass (FM), fat free mass (FFM), systolic blood pressure (SBP) and high-density lipoprotein (HDL) (p < 0.05). Moreover, adherence to Dietary Guidelines for Americans (DGA) appears to mediate association between gender and waist circumference (B = -9.78), SBP (B = -4.83), triglyceride (B = -13.01) and HDL (B = 4.31). HEI also mediated indirect negative effects of socioeconomic status on FM (B = -0.56), FFM (B = -0.25), SBP (B = -0.55) and diastolic blood pressure (DBP) (B = -0.3). Additionally, depression and age had indirect unfavorable effects on some insulin resistance indices such as homeostasis model assessment of insulin resistance (B = 0.07; p<0.05, for age) and quantitative insulin sensitivity check index (p<0.05, for age and depression) via HEI. High adherence to HEI was found to be inversely associated with MetS risk (p<0.05).
Adherence to HEI-2015 seems to mediate the effect of socio-demographic parameters and mental health on cardio-metabolic risk factors as well as MetS risk. Further studies are needed to confirm these findings.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>31260504</pmid><doi>10.1371/journal.pone.0219193</doi><tpages>e0219193</tpages><orcidid>https://orcid.org/0000-0002-7036-6900</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2019-07, Vol.14 (7), p.e0219193-e0219193 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_2250751455 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; Public Library of Science (PLoS) Journals Open Access; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry |
| subjects | Adult Age Anthropometry Biology and Life Sciences Blood pressure Body fat Cardiovascular diseases Cardiovascular Diseases - epidemiology Cardiovascular Diseases - etiology Cardiovascular Diseases - prevention & control Chronic diseases Chronic illnesses Cross-Sectional Studies Demographic aspects Demographics Diet Diet, Healthy - standards Diet, Healthy - statistics & numerical data Dietary intake Feeding Behavior Female Females Food and nutrition Food habits Health aspects Health risks High density lipoprotein Homeostasis Humans Insulin Insulin resistance Latent Class Analysis Male Males Mathematical models Medical research Medicine and Health Sciences Mental depression Mental disorders Mental health Metabolic diseases Metabolic disorders Metabolic syndrome Metabolic Syndrome - epidemiology Metabolic Syndrome - etiology Metabolic Syndrome - prevention & control Middle Aged Modelling Models, Biological Nutrition Policy Nutrition research Nutritional requirements Obesity Obesity - complications Obesity - diet therapy Obesity - metabolism Overweight persons Parameter estimation Patient Compliance - statistics & numerical data Psychological aspects Risk analysis Risk assessment Risk Assessment - methods Risk Factors Social class Socioeconomic Factors Socioeconomics Structural equation modeling Surveys and Questionnaires - statistics & numerical data Systematic review Triglycerides Type 2 diabetes Young Adult |
| title | A structural equation modeling approach for the association of a healthy eating index with metabolic syndrome and cardio-metabolic risk factors among obese individuals |
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