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A new equation especially developed for predicting resting metabolic rate in the elderly for easy use in practice
Equations published in the literature for predicting resting metabolic rate (RMR) in older individuals were exclusively derived from studies with small samples of this age group. of the present investigation was therefore to compare the measured RMR of a relatively large group of older females and m...
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Published in: | European journal of nutrition 2002-06, Vol.41 (3), p.108-113 |
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description | Equations published in the literature for predicting resting metabolic rate (RMR) in older individuals were exclusively derived from studies with small samples of this age group.
of the present investigation was therefore to compare the measured RMR of a relatively large group of older females and males with values for RMR calculated from the most commonly used WHO [1] equations. Furthermore, on the basis of the data collected by our study group a new equation for calculating RMR in the elderly was to be developed. Variables used in this equation should be easily and exactly determinable in practice.
RMR was measured by indirect calorimetry after an overnight fast in a sample of 179 female (age 67.8 +/- 5.7 y, BMI 26.4 +/- 3.7 kg/m(2)) and 107 male (age 66.9 +/- 5.1 y, BMI 26.3 +/- 3.1 kg/m(2)) participants in the longitudinal study on nutrition and health status in an aging population of Giessen, Germany. The subjects were at least 60 years old, did not suffer from thyroid dysfunction, and were not taking thyroid hormones. Stepwise multiple linear regression analysis was used to estimate the best predictors of RMR.
In females there was no significant difference between our measured RMR (5504 +/- 653 kJ/d) and RMR predicted with the WHO [1] equation (5458 +/- 440 kJ/d), whereas in males measured RMR (6831 +/- 779 kJ/d) was significantly higher than calculated RMR (6490 +/- 550 kJ/d). Results of regression analysis, considering body weight, body height, age, and sex, showed that RMR is best calculated by the following equation: RMR [kJ/d]= 3169 + 50.0 x body weight [kg] - 15.3 x age [y] + 746 x sex [female = 0, male = 1]. The variables of this equation accounted for 74 % (R(2)) of the variance in RMR and predicted RMR within +/- 486 kJ/d (SEE).
On the basis of the data determined in a large group of older individuals, we offer a new equation for calculating RMR in the elderly that is both easy and accurate for use in practice. |
doi_str_mv | 10.1007/s003940200016 |
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of the present investigation was therefore to compare the measured RMR of a relatively large group of older females and males with values for RMR calculated from the most commonly used WHO [1] equations. Furthermore, on the basis of the data collected by our study group a new equation for calculating RMR in the elderly was to be developed. Variables used in this equation should be easily and exactly determinable in practice.
RMR was measured by indirect calorimetry after an overnight fast in a sample of 179 female (age 67.8 +/- 5.7 y, BMI 26.4 +/- 3.7 kg/m(2)) and 107 male (age 66.9 +/- 5.1 y, BMI 26.3 +/- 3.1 kg/m(2)) participants in the longitudinal study on nutrition and health status in an aging population of Giessen, Germany. The subjects were at least 60 years old, did not suffer from thyroid dysfunction, and were not taking thyroid hormones. Stepwise multiple linear regression analysis was used to estimate the best predictors of RMR.
In females there was no significant difference between our measured RMR (5504 +/- 653 kJ/d) and RMR predicted with the WHO [1] equation (5458 +/- 440 kJ/d), whereas in males measured RMR (6831 +/- 779 kJ/d) was significantly higher than calculated RMR (6490 +/- 550 kJ/d). Results of regression analysis, considering body weight, body height, age, and sex, showed that RMR is best calculated by the following equation: RMR [kJ/d]= 3169 + 50.0 x body weight [kg] - 15.3 x age [y] + 746 x sex [female = 0, male = 1]. The variables of this equation accounted for 74 % (R(2)) of the variance in RMR and predicted RMR within +/- 486 kJ/d (SEE).
On the basis of the data determined in a large group of older individuals, we offer a new equation for calculating RMR in the elderly that is both easy and accurate for use in practice.</description><identifier>ISSN: 1436-6207</identifier><identifier>EISSN: 1436-6215</identifier><identifier>DOI: 10.1007/s003940200016</identifier><identifier>PMID: 12111047</identifier><language>eng</language><publisher>Heidelberg: Springer</publisher><subject>Age Factors ; Aged ; Aged, 80 and over ; Aging - physiology ; Anthropometry ; Basal Metabolism ; Biological and medical sciences ; Body Composition - physiology ; Calorimetry, Indirect ; Cross-Sectional Studies ; Development. Metamorphosis. Moult. Ageing ; Female ; Fundamental and applied biological sciences. Psychology ; Germany ; Health Status ; Humans ; Linear Models ; Longitudinal Studies ; Male ; Middle Aged ; Nutritional Status ; Predictive Value of Tests ; Vertebrates: anatomy and physiology, studies on body, several organs or systems</subject><ispartof>European journal of nutrition, 2002-06, Vol.41 (3), p.108-113</ispartof><rights>2002 INIST-CNRS</rights><rights>Copyright Springer-Verlag 2002</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c346t-b692534c46ff730706692cdfd0ac6e0daf73583758b0f9e9684725879692a1ac3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=13744172$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12111047$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>LÜHRMANN, Petra M</creatorcontrib><creatorcontrib>HERBERT, Birgit M</creatorcontrib><creatorcontrib>KREMS, Carolin</creatorcontrib><creatorcontrib>NEUHÄUSER-BERTHOLD, Monika</creatorcontrib><title>A new equation especially developed for predicting resting metabolic rate in the elderly for easy use in practice</title><title>European journal of nutrition</title><addtitle>Eur J Nutr</addtitle><description>Equations published in the literature for predicting resting metabolic rate (RMR) in older individuals were exclusively derived from studies with small samples of this age group.
of the present investigation was therefore to compare the measured RMR of a relatively large group of older females and males with values for RMR calculated from the most commonly used WHO [1] equations. Furthermore, on the basis of the data collected by our study group a new equation for calculating RMR in the elderly was to be developed. Variables used in this equation should be easily and exactly determinable in practice.
RMR was measured by indirect calorimetry after an overnight fast in a sample of 179 female (age 67.8 +/- 5.7 y, BMI 26.4 +/- 3.7 kg/m(2)) and 107 male (age 66.9 +/- 5.1 y, BMI 26.3 +/- 3.1 kg/m(2)) participants in the longitudinal study on nutrition and health status in an aging population of Giessen, Germany. The subjects were at least 60 years old, did not suffer from thyroid dysfunction, and were not taking thyroid hormones. Stepwise multiple linear regression analysis was used to estimate the best predictors of RMR.
In females there was no significant difference between our measured RMR (5504 +/- 653 kJ/d) and RMR predicted with the WHO [1] equation (5458 +/- 440 kJ/d), whereas in males measured RMR (6831 +/- 779 kJ/d) was significantly higher than calculated RMR (6490 +/- 550 kJ/d). Results of regression analysis, considering body weight, body height, age, and sex, showed that RMR is best calculated by the following equation: RMR [kJ/d]= 3169 + 50.0 x body weight [kg] - 15.3 x age [y] + 746 x sex [female = 0, male = 1]. The variables of this equation accounted for 74 % (R(2)) of the variance in RMR and predicted RMR within +/- 486 kJ/d (SEE).
On the basis of the data determined in a large group of older individuals, we offer a new equation for calculating RMR in the elderly that is both easy and accurate for use in practice.</description><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Aging - physiology</subject><subject>Anthropometry</subject><subject>Basal Metabolism</subject><subject>Biological and medical sciences</subject><subject>Body Composition - physiology</subject><subject>Calorimetry, Indirect</subject><subject>Cross-Sectional Studies</subject><subject>Development. Metamorphosis. Moult. Ageing</subject><subject>Female</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>Germany</subject><subject>Health Status</subject><subject>Humans</subject><subject>Linear Models</subject><subject>Longitudinal Studies</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Nutritional Status</subject><subject>Predictive Value of Tests</subject><subject>Vertebrates: anatomy and physiology, studies on body, several organs or systems</subject><issn>1436-6207</issn><issn>1436-6215</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><recordid>eNpd0UtLxDAQAOAgiq6rR68SBL1VJ48m7XFZfMGCFz2XbDrVSLbtJq2y_96oi6KnCZNvhmGGkBMGlwxAX0UAUUrgAMDUDpkwKVSmOMt3f96gD8hhjK-JcKHYPjlgnDEGUk_IekZbfKe4Hs3gupZi7NE64_2G1viGvuuxpk0XaB-wdnZw7TMNGL_iCgez7LyzNJgBqWvp8IIUfY0hlX8WoYkbOsavvz6YVG7xiOw1xkc83sYpebq5fpzfZYuH2_v5bJFZIdWQLVXJcyGtVE2jBWhQKWHrpgZjFUJtUjYvhM6LJTQllqqQmueFLhMzzFgxJRffffvQrcc0crVy0aL3psVujJVmJQhVFgme_YOv3RjaNFvFmSyUZpwnlH0jG7oYAzZVH9zKhE3FoPo8RPXnEMmfbpuOyxXWv3q7-QTOt8BEa3wTTGtd_HVCS8k0Fx_vY49R</recordid><startdate>20020601</startdate><enddate>20020601</enddate><creator>LÜHRMANN, Petra M</creator><creator>HERBERT, Birgit M</creator><creator>KREMS, Carolin</creator><creator>NEUHÄUSER-BERTHOLD, Monika</creator><general>Springer</general><general>Springer Nature B.V</general><scope>IQODW</scope><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>3V.</scope><scope>7QP</scope><scope>7RQ</scope><scope>7RV</scope><scope>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope></search><sort><creationdate>20020601</creationdate><title>A new equation especially developed for predicting resting metabolic rate in the elderly for easy use in practice</title><author>LÜHRMANN, Petra M ; HERBERT, Birgit M ; KREMS, Carolin ; NEUHÄUSER-BERTHOLD, Monika</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c346t-b692534c46ff730706692cdfd0ac6e0daf73583758b0f9e9684725879692a1ac3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Aging - physiology</topic><topic>Anthropometry</topic><topic>Basal Metabolism</topic><topic>Biological and medical sciences</topic><topic>Body Composition - physiology</topic><topic>Calorimetry, Indirect</topic><topic>Cross-Sectional Studies</topic><topic>Development. Metamorphosis. Moult. Ageing</topic><topic>Female</topic><topic>Fundamental and applied biological sciences. Psychology</topic><topic>Germany</topic><topic>Health Status</topic><topic>Humans</topic><topic>Linear Models</topic><topic>Longitudinal Studies</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Nutritional Status</topic><topic>Predictive Value of Tests</topic><topic>Vertebrates: anatomy and physiology, studies on body, several organs or systems</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>LÜHRMANN, Petra M</creatorcontrib><creatorcontrib>HERBERT, Birgit M</creatorcontrib><creatorcontrib>KREMS, Carolin</creatorcontrib><creatorcontrib>NEUHÄUSER-BERTHOLD, Monika</creatorcontrib><collection>Pascal-Francis</collection><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>Calcium & Calcified Tissue Abstracts</collection><collection>Career & Technical Education Database</collection><collection>Nursing & Allied Health Database</collection><collection>Physical Education Index</collection><collection>ProQuest Health and Medical</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>ProQuest Public Health Database</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)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>Consumer Health Database (Alumni Edition)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Family Health</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>PML(ProQuest Medical Library)</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of nutrition</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>LÜHRMANN, Petra M</au><au>HERBERT, Birgit M</au><au>KREMS, Carolin</au><au>NEUHÄUSER-BERTHOLD, Monika</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new equation especially developed for predicting resting metabolic rate in the elderly for easy use in practice</atitle><jtitle>European journal of nutrition</jtitle><addtitle>Eur J Nutr</addtitle><date>2002-06-01</date><risdate>2002</risdate><volume>41</volume><issue>3</issue><spage>108</spage><epage>113</epage><pages>108-113</pages><issn>1436-6207</issn><eissn>1436-6215</eissn><abstract>Equations published in the literature for predicting resting metabolic rate (RMR) in older individuals were exclusively derived from studies with small samples of this age group.
of the present investigation was therefore to compare the measured RMR of a relatively large group of older females and males with values for RMR calculated from the most commonly used WHO [1] equations. Furthermore, on the basis of the data collected by our study group a new equation for calculating RMR in the elderly was to be developed. Variables used in this equation should be easily and exactly determinable in practice.
RMR was measured by indirect calorimetry after an overnight fast in a sample of 179 female (age 67.8 +/- 5.7 y, BMI 26.4 +/- 3.7 kg/m(2)) and 107 male (age 66.9 +/- 5.1 y, BMI 26.3 +/- 3.1 kg/m(2)) participants in the longitudinal study on nutrition and health status in an aging population of Giessen, Germany. The subjects were at least 60 years old, did not suffer from thyroid dysfunction, and were not taking thyroid hormones. Stepwise multiple linear regression analysis was used to estimate the best predictors of RMR.
In females there was no significant difference between our measured RMR (5504 +/- 653 kJ/d) and RMR predicted with the WHO [1] equation (5458 +/- 440 kJ/d), whereas in males measured RMR (6831 +/- 779 kJ/d) was significantly higher than calculated RMR (6490 +/- 550 kJ/d). Results of regression analysis, considering body weight, body height, age, and sex, showed that RMR is best calculated by the following equation: RMR [kJ/d]= 3169 + 50.0 x body weight [kg] - 15.3 x age [y] + 746 x sex [female = 0, male = 1]. The variables of this equation accounted for 74 % (R(2)) of the variance in RMR and predicted RMR within +/- 486 kJ/d (SEE).
On the basis of the data determined in a large group of older individuals, we offer a new equation for calculating RMR in the elderly that is both easy and accurate for use in practice.</abstract><cop>Heidelberg</cop><pub>Springer</pub><pmid>12111047</pmid><doi>10.1007/s003940200016</doi><tpages>6</tpages></addata></record> |
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subjects | Age Factors Aged Aged, 80 and over Aging - physiology Anthropometry Basal Metabolism Biological and medical sciences Body Composition - physiology Calorimetry, Indirect Cross-Sectional Studies Development. Metamorphosis. Moult. Ageing Female Fundamental and applied biological sciences. Psychology Germany Health Status Humans Linear Models Longitudinal Studies Male Middle Aged Nutritional Status Predictive Value of Tests Vertebrates: anatomy and physiology, studies on body, several organs or systems |
title | A new equation especially developed for predicting resting metabolic rate in the elderly for easy use in practice |
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