Preventing Progression of Renal Disease: A New Method for Monitoring Body Fat Percentage in Predialysis Chronic Kidney Disease Patients

•Developed a noninvasive method to estimate body fat percentage in CKD patients.•New model avoids the need for bioimpedance and simplifies nutritional assessment.•Method validated with high explanatory power and strong statistical associations.•Practical for resource-limited settings, improving CKD...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nutrition (Burbank, Los Angeles County, Calif.) Los Angeles County, Calif.), 2025-02, Vol.130, p.112605, Article 112605
Hauptverfasser: Jiménez-Mérida, María del Rocío, Alcaide-Leyva, José Manuel, Lopez-Lucena, Miguel, Portero de la Cruz, Silvia, Molina-Luque, Rafael, Martínez-Angulo, Pablo
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page 112605
container_title Nutrition (Burbank, Los Angeles County, Calif.)
container_volume 130
creator Jiménez-Mérida, María del Rocío
Alcaide-Leyva, José Manuel
Lopez-Lucena, Miguel
Portero de la Cruz, Silvia
Molina-Luque, Rafael
Martínez-Angulo, Pablo
description •Developed a noninvasive method to estimate body fat percentage in CKD patients.•New model avoids the need for bioimpedance and simplifies nutritional assessment.•Method validated with high explanatory power and strong statistical associations.•Practical for resource-limited settings, improving CKD patient management.•Findings support improved patient outcomes through better nutritional assessment. Chronic kidney disease (CKD) is a progressive condition affecting metabolic pathways and physiological mechanisms. In Spain, CKD prevalence has risen, increasing patients requiring renal replacement therapy (RRT). Managing nutritional status in advanced CKD (ACKD) patients is crucial as it influences disease progression and quality of life. This study aims to describe the nutritional status of predialysis patients at University Hospital Reina Sofia, Cordoba, Spain, and develop a quick and easy model for estimating body fat percentage without bioimpedance. This cross-sectional study, conducted from February to May 2023, involved 106 patients from the ACKD consultation at the University Hospital Reina Sofia. Inclusion criteria were stage 3 or 4 CKD patients who consented to participate. Data included demographic and anthropometric variables, with body composition assessed using a Tanita BC-545N bioimpedance analyzer. The sample included 32 females (30.5%) and 73 males (69.5%), with an average BMI of 30.31 (SD 5.48). Significant findings were higher body fat percentage in women (37.82%) than men (27.86%; P < 0.001) and notable differences in waist circumference and waist-to-hip ratio between sexes. Multiple linear regression showed waist circumference, height, and sex as significant predictors of body fat percentage, with an intraclass correlation coefficient of 0.71 (95% CI = 0.59–0.79). Accurately assessing body composition in CKD patients is crucial as traditional measures like BMI may not capture health risks effectively. The developed model offers a practical alternative to bioimpedance for estimating body fat percentage, potentially improving CKD management and patient outcomes. Further validation in diverse populations and integration with lifestyle interventions is needed.
doi_str_mv 10.1016/j.nut.2024.112605
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_3129220667</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S0899900724002545</els_id><sourcerecordid>3129220667</sourcerecordid><originalsourceid>FETCH-LOGICAL-c263t-6e8bbb7fe95d331c9880aff385ac9a64b47c7e753b2922775ea5ac0e3403ee353</originalsourceid><addsrcrecordid>eNp9kc1u1DAUhS0EokPhAdggS2zYZPBvHMOqDPRHtDBCsLYc52bqUSZubadonoDXxtG0LFh0dRf3O9_iHIReU7KkhNbvt8txyktGmFhSymoin6AFbRSvKBPiKVqQRutKE6KO0IuUtoQQqmv9HB1xLYWuRbNAf9YR7mDMftzgdQybCCn5MOLQ4x8w2gF_9glsgg_4BH-D3_gK8nXocB8ivgqjzyHOyU-h2-NTm_Eaois2uwHsxyKEztthn3zCq-tYeIe_-m6E_YMWr232JZBeome9HRK8ur_H6Nfpl5-r8-ry-9nF6uSycqzmuaqhadtW9aBlxzl1ummI7XveSOu0rUUrlFOgJG-ZZkwpCbZ8CHBBOACX_Bi9O3hvYridIGWz88nBMNgRwpQMp3OQ1LUq6Nv_0G2YYulkpgSTShLBCkUPlIshpQi9uYl-Z-PeUGLmlczWlJXMvJI5rFQyb-7NU7uD7l_iYZYCfDwAUKq48xBNcqUmV-qM4LLpgn9E_xdju6LW</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3142575042</pqid></control><display><type>article</type><title>Preventing Progression of Renal Disease: A New Method for Monitoring Body Fat Percentage in Predialysis Chronic Kidney Disease Patients</title><source>MEDLINE</source><source>Access via ScienceDirect (Elsevier)</source><creator>Jiménez-Mérida, María del Rocío ; Alcaide-Leyva, José Manuel ; Lopez-Lucena, Miguel ; Portero de la Cruz, Silvia ; Molina-Luque, Rafael ; Martínez-Angulo, Pablo</creator><creatorcontrib>Jiménez-Mérida, María del Rocío ; Alcaide-Leyva, José Manuel ; Lopez-Lucena, Miguel ; Portero de la Cruz, Silvia ; Molina-Luque, Rafael ; Martínez-Angulo, Pablo</creatorcontrib><description>•Developed a noninvasive method to estimate body fat percentage in CKD patients.•New model avoids the need for bioimpedance and simplifies nutritional assessment.•Method validated with high explanatory power and strong statistical associations.•Practical for resource-limited settings, improving CKD patient management.•Findings support improved patient outcomes through better nutritional assessment. Chronic kidney disease (CKD) is a progressive condition affecting metabolic pathways and physiological mechanisms. In Spain, CKD prevalence has risen, increasing patients requiring renal replacement therapy (RRT). Managing nutritional status in advanced CKD (ACKD) patients is crucial as it influences disease progression and quality of life. This study aims to describe the nutritional status of predialysis patients at University Hospital Reina Sofia, Cordoba, Spain, and develop a quick and easy model for estimating body fat percentage without bioimpedance. This cross-sectional study, conducted from February to May 2023, involved 106 patients from the ACKD consultation at the University Hospital Reina Sofia. Inclusion criteria were stage 3 or 4 CKD patients who consented to participate. Data included demographic and anthropometric variables, with body composition assessed using a Tanita BC-545N bioimpedance analyzer. The sample included 32 females (30.5%) and 73 males (69.5%), with an average BMI of 30.31 (SD 5.48). Significant findings were higher body fat percentage in women (37.82%) than men (27.86%; P &lt; 0.001) and notable differences in waist circumference and waist-to-hip ratio between sexes. Multiple linear regression showed waist circumference, height, and sex as significant predictors of body fat percentage, with an intraclass correlation coefficient of 0.71 (95% CI = 0.59–0.79). Accurately assessing body composition in CKD patients is crucial as traditional measures like BMI may not capture health risks effectively. The developed model offers a practical alternative to bioimpedance for estimating body fat percentage, potentially improving CKD management and patient outcomes. Further validation in diverse populations and integration with lifestyle interventions is needed.</description><identifier>ISSN: 0899-9007</identifier><identifier>ISSN: 1873-1244</identifier><identifier>EISSN: 1873-1244</identifier><identifier>DOI: 10.1016/j.nut.2024.112605</identifier><identifier>PMID: 39549648</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Adipose Tissue ; Aged ; Anthropometric measurements ; Body Composition ; Body fat ; Body fat estimation ; Body Mass Index ; Body measurements ; Chronic illnesses ; Chronic kidney disease ; Composition effects ; Correlation coefficient ; Correlation coefficients ; Cross-Sectional Studies ; Demographic variables ; Disease Progression ; Electric Impedance ; Female ; Health risks ; Hemodialysis ; Hospitals ; Humans ; Hypothesis testing ; Intervention ; Kidney diseases ; Kidneys ; Male ; Metabolic pathways ; Metabolism ; Middle Aged ; Monitoring methods ; Nutritional Status ; Obesity ; Overweight ; Patients ; Predialysis ; Quality of life ; Regression analysis ; Renal Insufficiency, Chronic - physiopathology ; Renal Insufficiency, Chronic - therapy ; Renal replacement therapy ; Sex ratio ; Spain</subject><ispartof>Nutrition (Burbank, Los Angeles County, Calif.), 2025-02, Vol.130, p.112605, Article 112605</ispartof><rights>2024 Elsevier Inc.</rights><rights>Copyright © 2024 Elsevier Inc. All rights reserved.</rights><rights>2024. Elsevier Inc.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c263t-6e8bbb7fe95d331c9880aff385ac9a64b47c7e753b2922775ea5ac0e3403ee353</cites><orcidid>0000-0001-8949-1907</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.nut.2024.112605$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39549648$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jiménez-Mérida, María del Rocío</creatorcontrib><creatorcontrib>Alcaide-Leyva, José Manuel</creatorcontrib><creatorcontrib>Lopez-Lucena, Miguel</creatorcontrib><creatorcontrib>Portero de la Cruz, Silvia</creatorcontrib><creatorcontrib>Molina-Luque, Rafael</creatorcontrib><creatorcontrib>Martínez-Angulo, Pablo</creatorcontrib><title>Preventing Progression of Renal Disease: A New Method for Monitoring Body Fat Percentage in Predialysis Chronic Kidney Disease Patients</title><title>Nutrition (Burbank, Los Angeles County, Calif.)</title><addtitle>Nutrition</addtitle><description>•Developed a noninvasive method to estimate body fat percentage in CKD patients.•New model avoids the need for bioimpedance and simplifies nutritional assessment.•Method validated with high explanatory power and strong statistical associations.•Practical for resource-limited settings, improving CKD patient management.•Findings support improved patient outcomes through better nutritional assessment. Chronic kidney disease (CKD) is a progressive condition affecting metabolic pathways and physiological mechanisms. In Spain, CKD prevalence has risen, increasing patients requiring renal replacement therapy (RRT). Managing nutritional status in advanced CKD (ACKD) patients is crucial as it influences disease progression and quality of life. This study aims to describe the nutritional status of predialysis patients at University Hospital Reina Sofia, Cordoba, Spain, and develop a quick and easy model for estimating body fat percentage without bioimpedance. This cross-sectional study, conducted from February to May 2023, involved 106 patients from the ACKD consultation at the University Hospital Reina Sofia. Inclusion criteria were stage 3 or 4 CKD patients who consented to participate. Data included demographic and anthropometric variables, with body composition assessed using a Tanita BC-545N bioimpedance analyzer. The sample included 32 females (30.5%) and 73 males (69.5%), with an average BMI of 30.31 (SD 5.48). Significant findings were higher body fat percentage in women (37.82%) than men (27.86%; P &lt; 0.001) and notable differences in waist circumference and waist-to-hip ratio between sexes. Multiple linear regression showed waist circumference, height, and sex as significant predictors of body fat percentage, with an intraclass correlation coefficient of 0.71 (95% CI = 0.59–0.79). Accurately assessing body composition in CKD patients is crucial as traditional measures like BMI may not capture health risks effectively. The developed model offers a practical alternative to bioimpedance for estimating body fat percentage, potentially improving CKD management and patient outcomes. Further validation in diverse populations and integration with lifestyle interventions is needed.</description><subject>Adipose Tissue</subject><subject>Aged</subject><subject>Anthropometric measurements</subject><subject>Body Composition</subject><subject>Body fat</subject><subject>Body fat estimation</subject><subject>Body Mass Index</subject><subject>Body measurements</subject><subject>Chronic illnesses</subject><subject>Chronic kidney disease</subject><subject>Composition effects</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Cross-Sectional Studies</subject><subject>Demographic variables</subject><subject>Disease Progression</subject><subject>Electric Impedance</subject><subject>Female</subject><subject>Health risks</subject><subject>Hemodialysis</subject><subject>Hospitals</subject><subject>Humans</subject><subject>Hypothesis testing</subject><subject>Intervention</subject><subject>Kidney diseases</subject><subject>Kidneys</subject><subject>Male</subject><subject>Metabolic pathways</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Monitoring methods</subject><subject>Nutritional Status</subject><subject>Obesity</subject><subject>Overweight</subject><subject>Patients</subject><subject>Predialysis</subject><subject>Quality of life</subject><subject>Regression analysis</subject><subject>Renal Insufficiency, Chronic - physiopathology</subject><subject>Renal Insufficiency, Chronic - therapy</subject><subject>Renal replacement therapy</subject><subject>Sex ratio</subject><subject>Spain</subject><issn>0899-9007</issn><issn>1873-1244</issn><issn>1873-1244</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2025</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9kc1u1DAUhS0EokPhAdggS2zYZPBvHMOqDPRHtDBCsLYc52bqUSZubadonoDXxtG0LFh0dRf3O9_iHIReU7KkhNbvt8txyktGmFhSymoin6AFbRSvKBPiKVqQRutKE6KO0IuUtoQQqmv9HB1xLYWuRbNAf9YR7mDMftzgdQybCCn5MOLQ4x8w2gF_9glsgg_4BH-D3_gK8nXocB8ivgqjzyHOyU-h2-NTm_Eaois2uwHsxyKEztthn3zCq-tYeIe_-m6E_YMWr232JZBeome9HRK8ur_H6Nfpl5-r8-ry-9nF6uSycqzmuaqhadtW9aBlxzl1ummI7XveSOu0rUUrlFOgJG-ZZkwpCbZ8CHBBOACX_Bi9O3hvYridIGWz88nBMNgRwpQMp3OQ1LUq6Nv_0G2YYulkpgSTShLBCkUPlIshpQi9uYl-Z-PeUGLmlczWlJXMvJI5rFQyb-7NU7uD7l_iYZYCfDwAUKq48xBNcqUmV-qM4LLpgn9E_xdju6LW</recordid><startdate>20250201</startdate><enddate>20250201</enddate><creator>Jiménez-Mérida, María del Rocío</creator><creator>Alcaide-Leyva, José Manuel</creator><creator>Lopez-Lucena, Miguel</creator><creator>Portero de la Cruz, Silvia</creator><creator>Molina-Luque, Rafael</creator><creator>Martínez-Angulo, Pablo</creator><general>Elsevier Inc</general><general>Elsevier Limited</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>7TS</scope><scope>7U7</scope><scope>ASE</scope><scope>C1K</scope><scope>FPQ</scope><scope>K6X</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-8949-1907</orcidid></search><sort><creationdate>20250201</creationdate><title>Preventing Progression of Renal Disease: A New Method for Monitoring Body Fat Percentage in Predialysis Chronic Kidney Disease Patients</title><author>Jiménez-Mérida, María del Rocío ; Alcaide-Leyva, José Manuel ; Lopez-Lucena, Miguel ; Portero de la Cruz, Silvia ; Molina-Luque, Rafael ; Martínez-Angulo, Pablo</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c263t-6e8bbb7fe95d331c9880aff385ac9a64b47c7e753b2922775ea5ac0e3403ee353</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2025</creationdate><topic>Adipose Tissue</topic><topic>Aged</topic><topic>Anthropometric measurements</topic><topic>Body Composition</topic><topic>Body fat</topic><topic>Body fat estimation</topic><topic>Body Mass Index</topic><topic>Body measurements</topic><topic>Chronic illnesses</topic><topic>Chronic kidney disease</topic><topic>Composition effects</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Cross-Sectional Studies</topic><topic>Demographic variables</topic><topic>Disease Progression</topic><topic>Electric Impedance</topic><topic>Female</topic><topic>Health risks</topic><topic>Hemodialysis</topic><topic>Hospitals</topic><topic>Humans</topic><topic>Hypothesis testing</topic><topic>Intervention</topic><topic>Kidney diseases</topic><topic>Kidneys</topic><topic>Male</topic><topic>Metabolic pathways</topic><topic>Metabolism</topic><topic>Middle Aged</topic><topic>Monitoring methods</topic><topic>Nutritional Status</topic><topic>Obesity</topic><topic>Overweight</topic><topic>Patients</topic><topic>Predialysis</topic><topic>Quality of life</topic><topic>Regression analysis</topic><topic>Renal Insufficiency, Chronic - physiopathology</topic><topic>Renal Insufficiency, Chronic - therapy</topic><topic>Renal replacement therapy</topic><topic>Sex ratio</topic><topic>Spain</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jiménez-Mérida, María del Rocío</creatorcontrib><creatorcontrib>Alcaide-Leyva, José Manuel</creatorcontrib><creatorcontrib>Lopez-Lucena, Miguel</creatorcontrib><creatorcontrib>Portero de la Cruz, Silvia</creatorcontrib><creatorcontrib>Molina-Luque, Rafael</creatorcontrib><creatorcontrib>Martínez-Angulo, Pablo</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Physical Education Index</collection><collection>Toxicology Abstracts</collection><collection>British Nursing Index</collection><collection>Environmental Sciences and Pollution Management</collection><collection>British Nursing Index (BNI) (1985 to Present)</collection><collection>British Nursing Index</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>Nursing &amp; Allied Health Premium</collection><collection>MEDLINE - Academic</collection><jtitle>Nutrition (Burbank, Los Angeles County, Calif.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jiménez-Mérida, María del Rocío</au><au>Alcaide-Leyva, José Manuel</au><au>Lopez-Lucena, Miguel</au><au>Portero de la Cruz, Silvia</au><au>Molina-Luque, Rafael</au><au>Martínez-Angulo, Pablo</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Preventing Progression of Renal Disease: A New Method for Monitoring Body Fat Percentage in Predialysis Chronic Kidney Disease Patients</atitle><jtitle>Nutrition (Burbank, Los Angeles County, Calif.)</jtitle><addtitle>Nutrition</addtitle><date>2025-02-01</date><risdate>2025</risdate><volume>130</volume><spage>112605</spage><pages>112605-</pages><artnum>112605</artnum><issn>0899-9007</issn><issn>1873-1244</issn><eissn>1873-1244</eissn><abstract>•Developed a noninvasive method to estimate body fat percentage in CKD patients.•New model avoids the need for bioimpedance and simplifies nutritional assessment.•Method validated with high explanatory power and strong statistical associations.•Practical for resource-limited settings, improving CKD patient management.•Findings support improved patient outcomes through better nutritional assessment. Chronic kidney disease (CKD) is a progressive condition affecting metabolic pathways and physiological mechanisms. In Spain, CKD prevalence has risen, increasing patients requiring renal replacement therapy (RRT). Managing nutritional status in advanced CKD (ACKD) patients is crucial as it influences disease progression and quality of life. This study aims to describe the nutritional status of predialysis patients at University Hospital Reina Sofia, Cordoba, Spain, and develop a quick and easy model for estimating body fat percentage without bioimpedance. This cross-sectional study, conducted from February to May 2023, involved 106 patients from the ACKD consultation at the University Hospital Reina Sofia. Inclusion criteria were stage 3 or 4 CKD patients who consented to participate. Data included demographic and anthropometric variables, with body composition assessed using a Tanita BC-545N bioimpedance analyzer. The sample included 32 females (30.5%) and 73 males (69.5%), with an average BMI of 30.31 (SD 5.48). Significant findings were higher body fat percentage in women (37.82%) than men (27.86%; P &lt; 0.001) and notable differences in waist circumference and waist-to-hip ratio between sexes. Multiple linear regression showed waist circumference, height, and sex as significant predictors of body fat percentage, with an intraclass correlation coefficient of 0.71 (95% CI = 0.59–0.79). Accurately assessing body composition in CKD patients is crucial as traditional measures like BMI may not capture health risks effectively. The developed model offers a practical alternative to bioimpedance for estimating body fat percentage, potentially improving CKD management and patient outcomes. Further validation in diverse populations and integration with lifestyle interventions is needed.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>39549648</pmid><doi>10.1016/j.nut.2024.112605</doi><orcidid>https://orcid.org/0000-0001-8949-1907</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 0899-9007
ispartof Nutrition (Burbank, Los Angeles County, Calif.), 2025-02, Vol.130, p.112605, Article 112605
issn 0899-9007
1873-1244
1873-1244
language eng
recordid cdi_proquest_miscellaneous_3129220667
source MEDLINE; Access via ScienceDirect (Elsevier)
subjects Adipose Tissue
Aged
Anthropometric measurements
Body Composition
Body fat
Body fat estimation
Body Mass Index
Body measurements
Chronic illnesses
Chronic kidney disease
Composition effects
Correlation coefficient
Correlation coefficients
Cross-Sectional Studies
Demographic variables
Disease Progression
Electric Impedance
Female
Health risks
Hemodialysis
Hospitals
Humans
Hypothesis testing
Intervention
Kidney diseases
Kidneys
Male
Metabolic pathways
Metabolism
Middle Aged
Monitoring methods
Nutritional Status
Obesity
Overweight
Patients
Predialysis
Quality of life
Regression analysis
Renal Insufficiency, Chronic - physiopathology
Renal Insufficiency, Chronic - therapy
Renal replacement therapy
Sex ratio
Spain
title Preventing Progression of Renal Disease: A New Method for Monitoring Body Fat Percentage in Predialysis Chronic Kidney Disease Patients
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-24T07%3A59%3A24IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Preventing%20Progression%20of%20Renal%20Disease:%20A%20New%20Method%20for%20Monitoring%20Body%20Fat%20Percentage%20in%20Predialysis%20Chronic%20Kidney%20Disease%20Patients&rft.jtitle=Nutrition%20(Burbank,%20Los%20Angeles%20County,%20Calif.)&rft.au=Jim%C3%A9nez-M%C3%A9rida,%20Mar%C3%ADa%20del%20Roc%C3%ADo&rft.date=2025-02-01&rft.volume=130&rft.spage=112605&rft.pages=112605-&rft.artnum=112605&rft.issn=0899-9007&rft.eissn=1873-1244&rft_id=info:doi/10.1016/j.nut.2024.112605&rft_dat=%3Cproquest_cross%3E3129220667%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3142575042&rft_id=info:pmid/39549648&rft_els_id=S0899900724002545&rfr_iscdi=true