Definition of nutritionally qualitative categorizing (proto)nutritypes and a pilot quantitative nutrimeter for mirroring nutritional well-being based on a quality of life health related questionnaire
Background: there are numerous approaches to assess nutritional status, which are putatively applied to nutritionally classify diseased people, but less information is available to study the role of environmental factors on nutritional well-being. A qualitative (nutritypes) and quantitative (nutrime...
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| Veröffentlicht in: | Nutrición hospitalaria : organo oficial de la Sociedad Española de Nutrición Parenteral y Enteral 2019-08, Vol.36 (4), p.862-874 |
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| container_title | Nutrición hospitalaria : organo oficial de la Sociedad Española de Nutrición Parenteral y Enteral |
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| creator | de Cuevillas, Begoña Álvarez Álvarez, Ismael Cuervo, Marta Fernández Montero, Alejandro Navas Carretero, Santiago Martínez, José Alfredo |
| description | Background: there are numerous approaches to assess nutritional status, which are putatively applied to nutritionally classify diseased people, but less information is available to study the role of environmental factors on nutritional well-being. A qualitative (nutritypes) and quantitative (nutrimeter) nutritional categorization based on dietary, lifestyle and disease criteria can be a useful nutritional approach to personalize health interventions and identify at risk individuals. Methods: cross-sectional study conducted on 102 patients (60 women), evaluating quality of life using the Short-Form 36 questionnaire (SF-36) and lifestyle factors with a general questionnaire, the Mediterranean Diet Adherence Screener (MEDAS) and the Global Physical Activity Questionnaire (GPAQ). A nutrimeter based on physical activity, fat mass, diet and diseases (hypertension, prediabetes, obesity and dyslipidemia) data was defined with an equation to quantitatively score the nutritive well-being of the participants, and classify them into two (proto)nutritypes. Results: participants were categorized into two groups (lower/higher global health) according to quality of life. Significant or marginal statistical differences in physical activity, fat mass, diet and disease were found (all p < 0.1). Two (proto)nutritypes were identified based on participant's age, sex, fat mass, physical activity, diet and diseases. Participants classified as high nutritional well-being nutritype showed higher values for physical, mental and global health dimensions. Age, fat mass, physical activity and diet, when categorized by the median, confirm that the designed nutritional well-being nutrimeter identified two (proto)nutritypes. Conclusions: the association between phenotypical (fat mass/diseases) and lifestyle factors (diet/physical activity) with quality of life allowed categorizing individuals with a nutritional quantitative score or nutrimeter according to their nutritional well-being and discriminate two qualitative (proto)nutritypes. |
| doi_str_mv | 10.20960/nh.02532 |
| format | Article |
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A qualitative (nutritypes) and quantitative (nutrimeter) nutritional categorization based on dietary, lifestyle and disease criteria can be a useful nutritional approach to personalize health interventions and identify at risk individuals. Methods: cross-sectional study conducted on 102 patients (60 women), evaluating quality of life using the Short-Form 36 questionnaire (SF-36) and lifestyle factors with a general questionnaire, the Mediterranean Diet Adherence Screener (MEDAS) and the Global Physical Activity Questionnaire (GPAQ). A nutrimeter based on physical activity, fat mass, diet and diseases (hypertension, prediabetes, obesity and dyslipidemia) data was defined with an equation to quantitatively score the nutritive well-being of the participants, and classify them into two (proto)nutritypes. Results: participants were categorized into two groups (lower/higher global health) according to quality of life. Significant or marginal statistical differences in physical activity, fat mass, diet and disease were found (all p < 0.1). Two (proto)nutritypes were identified based on participant's age, sex, fat mass, physical activity, diet and diseases. Participants classified as high nutritional well-being nutritype showed higher values for physical, mental and global health dimensions. Age, fat mass, physical activity and diet, when categorized by the median, confirm that the designed nutritional well-being nutrimeter identified two (proto)nutritypes. Conclusions: the association between phenotypical (fat mass/diseases) and lifestyle factors (diet/physical activity) with quality of life allowed categorizing individuals with a nutritional quantitative score or nutrimeter according to their nutritional well-being and discriminate two qualitative (proto)nutritypes.</description><identifier>ISSN: 0212-1611</identifier><identifier>ISSN: 1699-5198</identifier><identifier>EISSN: 1699-5198</identifier><identifier>DOI: 10.20960/nh.02532</identifier><identifier>PMID: 31282167</identifier><language>eng</language><publisher>Spain: Grupo Arán</publisher><subject>Adiposity ; Adult ; Age Factors ; Aged ; Body Mass Index ; Cross-Sectional Studies ; Diet, Mediterranean ; Exercise ; Feeding Behavior ; Female ; Health Status ; Humans ; Life Style ; Linear Models ; Lipids - blood ; Male ; Mental Health ; Middle Aged ; Nutrition & Dietetics ; Nutrition Surveys ; Nutritional Status ; Nutritive Value ; Obesity - diagnosis ; Quality of Life ; Surveys and Questionnaires ; Young Adult</subject><ispartof>Nutrición hospitalaria : organo oficial de la Sociedad Española de Nutrición Parenteral y Enteral, 2019-08, Vol.36 (4), p.862-874</ispartof><rights>This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-558a75747a0a34c66c517ac552eeda2ef6c8659fa648fefd6a7d7ad156cb73ba3</citedby><cites>FETCH-LOGICAL-c359t-558a75747a0a34c66c517ac552eeda2ef6c8659fa648fefd6a7d7ad156cb73ba3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,776,780,881,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31282167$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>de Cuevillas, Begoña</creatorcontrib><creatorcontrib>Álvarez Álvarez, Ismael</creatorcontrib><creatorcontrib>Cuervo, Marta</creatorcontrib><creatorcontrib>Fernández Montero, Alejandro</creatorcontrib><creatorcontrib>Navas Carretero, Santiago</creatorcontrib><creatorcontrib>Martínez, José Alfredo</creatorcontrib><title>Definition of nutritionally qualitative categorizing (proto)nutritypes and a pilot quantitative nutrimeter for mirroring nutritional well-being based on a quality of life health related questionnaire</title><title>Nutrición hospitalaria : organo oficial de la Sociedad Española de Nutrición Parenteral y Enteral</title><addtitle>Nutr Hosp</addtitle><description>Background: there are numerous approaches to assess nutritional status, which are putatively applied to nutritionally classify diseased people, but less information is available to study the role of environmental factors on nutritional well-being. A qualitative (nutritypes) and quantitative (nutrimeter) nutritional categorization based on dietary, lifestyle and disease criteria can be a useful nutritional approach to personalize health interventions and identify at risk individuals. Methods: cross-sectional study conducted on 102 patients (60 women), evaluating quality of life using the Short-Form 36 questionnaire (SF-36) and lifestyle factors with a general questionnaire, the Mediterranean Diet Adherence Screener (MEDAS) and the Global Physical Activity Questionnaire (GPAQ). A nutrimeter based on physical activity, fat mass, diet and diseases (hypertension, prediabetes, obesity and dyslipidemia) data was defined with an equation to quantitatively score the nutritive well-being of the participants, and classify them into two (proto)nutritypes. Results: participants were categorized into two groups (lower/higher global health) according to quality of life. Significant or marginal statistical differences in physical activity, fat mass, diet and disease were found (all p < 0.1). Two (proto)nutritypes were identified based on participant's age, sex, fat mass, physical activity, diet and diseases. Participants classified as high nutritional well-being nutritype showed higher values for physical, mental and global health dimensions. Age, fat mass, physical activity and diet, when categorized by the median, confirm that the designed nutritional well-being nutrimeter identified two (proto)nutritypes. Conclusions: the association between phenotypical (fat mass/diseases) and lifestyle factors (diet/physical activity) with quality of life allowed categorizing individuals with a nutritional quantitative score or nutrimeter according to their nutritional well-being and discriminate two qualitative (proto)nutritypes.</description><subject>Adiposity</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Body Mass Index</subject><subject>Cross-Sectional Studies</subject><subject>Diet, Mediterranean</subject><subject>Exercise</subject><subject>Feeding Behavior</subject><subject>Female</subject><subject>Health Status</subject><subject>Humans</subject><subject>Life Style</subject><subject>Linear Models</subject><subject>Lipids - blood</subject><subject>Male</subject><subject>Mental Health</subject><subject>Middle Aged</subject><subject>Nutrition & Dietetics</subject><subject>Nutrition Surveys</subject><subject>Nutritional Status</subject><subject>Nutritive Value</subject><subject>Obesity - diagnosis</subject><subject>Quality of Life</subject><subject>Surveys and Questionnaires</subject><subject>Young Adult</subject><issn>0212-1611</issn><issn>1699-5198</issn><issn>1699-5198</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpNUcFu3CAURFWqZpP20B-IOCYHbwEv2D5WaZtEipRD0rP1jB9ZIhYcYFttf7C_FbybVD0gBMzMG2YI-czZUrBOsS9-vWRC1uIdWXDVdZXkXXtEFkxwUXHF-TE5SemJMdGxVn0gxzUXreCqWZC_39BYb7MNngZD_TbH_QGc29HnLTibIdtfSDVkfAzR_rH-kZ5PMeRwcUDvJkwU_EiBTtaFPNN8fuPtMRvMGKkJkW5sjEWlaPw3iv5G56oB5-sBEo60uIHX8bvZl7MG6RrB5TWN6IqXsTxjmvkebMSP5L0Bl_DT635Kfv74_nB5Xd3eXd1cfr2tdC27XEnZQiObVQMM6pVWSkvegJZSII4g0CjdKtkZUKvWoBkVNGMDI5dKD009QH1KlgfdpC260D-FbSw_SP39HHY_hy0Y7xhjq7J4WwgXB4KOIaWIpp9KHhB3PWf9vr3er_t9ewV7dsBO22GD4z_kW131C6VYmoU</recordid><startdate>20190826</startdate><enddate>20190826</enddate><creator>de Cuevillas, Begoña</creator><creator>Álvarez Álvarez, Ismael</creator><creator>Cuervo, Marta</creator><creator>Fernández Montero, Alejandro</creator><creator>Navas Carretero, Santiago</creator><creator>Martínez, José Alfredo</creator><general>Grupo Arán</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>GPN</scope></search><sort><creationdate>20190826</creationdate><title>Definition of nutritionally qualitative categorizing (proto)nutritypes and a pilot quantitative nutrimeter for mirroring nutritional well-being based on a quality of life health related questionnaire</title><author>de Cuevillas, Begoña ; Álvarez Álvarez, Ismael ; Cuervo, Marta ; Fernández Montero, Alejandro ; Navas Carretero, Santiago ; Martínez, José Alfredo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-558a75747a0a34c66c517ac552eeda2ef6c8659fa648fefd6a7d7ad156cb73ba3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adiposity</topic><topic>Adult</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Body Mass Index</topic><topic>Cross-Sectional Studies</topic><topic>Diet, Mediterranean</topic><topic>Exercise</topic><topic>Feeding Behavior</topic><topic>Female</topic><topic>Health Status</topic><topic>Humans</topic><topic>Life Style</topic><topic>Linear Models</topic><topic>Lipids - blood</topic><topic>Male</topic><topic>Mental Health</topic><topic>Middle Aged</topic><topic>Nutrition & Dietetics</topic><topic>Nutrition Surveys</topic><topic>Nutritional Status</topic><topic>Nutritive Value</topic><topic>Obesity - diagnosis</topic><topic>Quality of Life</topic><topic>Surveys and Questionnaires</topic><topic>Young Adult</topic><toplevel>online_resources</toplevel><creatorcontrib>de Cuevillas, Begoña</creatorcontrib><creatorcontrib>Álvarez Álvarez, Ismael</creatorcontrib><creatorcontrib>Cuervo, Marta</creatorcontrib><creatorcontrib>Fernández Montero, Alejandro</creatorcontrib><creatorcontrib>Navas Carretero, Santiago</creatorcontrib><creatorcontrib>Martínez, José Alfredo</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>SciELO</collection><jtitle>Nutrición hospitalaria : organo oficial de la Sociedad Española de Nutrición Parenteral y Enteral</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>de Cuevillas, Begoña</au><au>Álvarez Álvarez, Ismael</au><au>Cuervo, Marta</au><au>Fernández Montero, Alejandro</au><au>Navas Carretero, Santiago</au><au>Martínez, José Alfredo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Definition of nutritionally qualitative categorizing (proto)nutritypes and a pilot quantitative nutrimeter for mirroring nutritional well-being based on a quality of life health related questionnaire</atitle><jtitle>Nutrición hospitalaria : organo oficial de la Sociedad Española de Nutrición Parenteral y Enteral</jtitle><addtitle>Nutr Hosp</addtitle><date>2019-08-26</date><risdate>2019</risdate><volume>36</volume><issue>4</issue><spage>862</spage><epage>874</epage><pages>862-874</pages><issn>0212-1611</issn><issn>1699-5198</issn><eissn>1699-5198</eissn><abstract>Background: there are numerous approaches to assess nutritional status, which are putatively applied to nutritionally classify diseased people, but less information is available to study the role of environmental factors on nutritional well-being. A qualitative (nutritypes) and quantitative (nutrimeter) nutritional categorization based on dietary, lifestyle and disease criteria can be a useful nutritional approach to personalize health interventions and identify at risk individuals. Methods: cross-sectional study conducted on 102 patients (60 women), evaluating quality of life using the Short-Form 36 questionnaire (SF-36) and lifestyle factors with a general questionnaire, the Mediterranean Diet Adherence Screener (MEDAS) and the Global Physical Activity Questionnaire (GPAQ). A nutrimeter based on physical activity, fat mass, diet and diseases (hypertension, prediabetes, obesity and dyslipidemia) data was defined with an equation to quantitatively score the nutritive well-being of the participants, and classify them into two (proto)nutritypes. Results: participants were categorized into two groups (lower/higher global health) according to quality of life. Significant or marginal statistical differences in physical activity, fat mass, diet and disease were found (all p < 0.1). Two (proto)nutritypes were identified based on participant's age, sex, fat mass, physical activity, diet and diseases. Participants classified as high nutritional well-being nutritype showed higher values for physical, mental and global health dimensions. Age, fat mass, physical activity and diet, when categorized by the median, confirm that the designed nutritional well-being nutrimeter identified two (proto)nutritypes. Conclusions: the association between phenotypical (fat mass/diseases) and lifestyle factors (diet/physical activity) with quality of life allowed categorizing individuals with a nutritional quantitative score or nutrimeter according to their nutritional well-being and discriminate two qualitative (proto)nutritypes.</abstract><cop>Spain</cop><pub>Grupo Arán</pub><pmid>31282167</pmid><doi>10.20960/nh.02532</doi><tpages>13</tpages><oa>free_for_read</oa></addata></record> |
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| ispartof | Nutrición hospitalaria : organo oficial de la Sociedad Española de Nutrición Parenteral y Enteral, 2019-08, Vol.36 (4), p.862-874 |
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| source | MEDLINE; EZB-FREE-00999 freely available EZB journals; Alma/SFX Local Collection |
| subjects | Adiposity Adult Age Factors Aged Body Mass Index Cross-Sectional Studies Diet, Mediterranean Exercise Feeding Behavior Female Health Status Humans Life Style Linear Models Lipids - blood Male Mental Health Middle Aged Nutrition & Dietetics Nutrition Surveys Nutritional Status Nutritive Value Obesity - diagnosis Quality of Life Surveys and Questionnaires Young Adult |
| title | Definition of nutritionally qualitative categorizing (proto)nutritypes and a pilot quantitative nutrimeter for mirroring nutritional well-being based on a quality of life health related questionnaire |
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