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Sarcopenic Obesity Phenotype Index (SOPi): A Population-Based Study

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00064165%3A_____%2F25%3A10504946" target="_blank" >RIV/00064165:_____/25:10504946 - isvavai.cz</a>

  • Nalezeny alternativní kódy

    RIV/00216208:11110/25:10504946

  • Výsledek na webu

    <a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=HTI44z4iH9" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=HTI44z4iH9</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/jcsm.70099" target="_blank" >10.1002/jcsm.70099</a>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Sarcopenic Obesity Phenotype Index (SOPi): A Population-Based Study

  • Popis výsledku v původním jazyce

    Background: Sarcopenic obesity (SO) is a clinical condition defined by the coexistence of high body fat mass and low muscle function and mass, which increases the risk of adverse health outcomes, including disability and mortality. Early detection and frequent monitoring of SO are essential for preventive interventions and management strategies. The current binary approach for SO diagnosis is limited in capturing the spectrum of SO or its progression over time. The main objective of this study was to develop a continuous SOPi that integrates diagnostic criteria such as muscle function and body composition. We aimed to evaluate the association between SOPi and all-cause mortality, to identify baseline-related factors with SOPi and to assess changes in the SOPi over time. Methods: Participants from the Rotterdam Study with baseline and follow-up measures of handgrip strength (HGS), dual-energy X-ray absorptiometry-measured appendicular lean mass index (ALM/kg) and body fat percentage (BF%) were included. SOPi was calculated as a sex-specific equation integrating z-scores (Z) of (BF%)-(HGS)-(ALM/kg). Cox regression and multivariable linear regression models were fitted to evaluate mortality risk and associated factors with SOPi, respectively. Subgroup analysis of SOPi changes was performed by linear mixed-effects models. Results: In the total population (n = 5888, age 69.5 +- 9.1 years, BMI 27.5 +- 4.3 kg/m2, 56.8% females) and over the 9.9-year median follow-up period, 1538 (26.1%) participants died. Each standard deviation (SD) increase in sex-specific SOPi was associated with a 10% higher risk of premature death (HR = 1.10 [95%CI: 1.07; 1.13]). Thirteen factors were associated with high SOPi, such as reduced physical activity, higher triglyceride-glucose index, HOMA-IR, systemic inflammation, osteopenia, hypertension, liver steatosis, asthma, coronary heart disease, oral corticosteroid use, lower protein intake, lower quality of life and lower educational status. In participants with obesity, lower physical activity and/or insulin resistance (n = 1682), a significantly higher and faster increase in SOPi was observed compared to participants without these factors (males: β = 2.63 [95%CI: 2.22; 3.03]; females: β = 2.90 [95%CI: 2.58; 3.23]). Conclusion: SOPi is a significant predictor of premature death and can identify associated factors, particularly useful among persons at risk of SO. SOPi is higher and increases faster in individuals with specific phenotypes. SOPi integrates prognosis information, which could be used as a risk indicator and for prevention of SO.

  • Název v anglickém jazyce

    Sarcopenic Obesity Phenotype Index (SOPi): A Population-Based Study

  • Popis výsledku anglicky

    Background: Sarcopenic obesity (SO) is a clinical condition defined by the coexistence of high body fat mass and low muscle function and mass, which increases the risk of adverse health outcomes, including disability and mortality. Early detection and frequent monitoring of SO are essential for preventive interventions and management strategies. The current binary approach for SO diagnosis is limited in capturing the spectrum of SO or its progression over time. The main objective of this study was to develop a continuous SOPi that integrates diagnostic criteria such as muscle function and body composition. We aimed to evaluate the association between SOPi and all-cause mortality, to identify baseline-related factors with SOPi and to assess changes in the SOPi over time. Methods: Participants from the Rotterdam Study with baseline and follow-up measures of handgrip strength (HGS), dual-energy X-ray absorptiometry-measured appendicular lean mass index (ALM/kg) and body fat percentage (BF%) were included. SOPi was calculated as a sex-specific equation integrating z-scores (Z) of (BF%)-(HGS)-(ALM/kg). Cox regression and multivariable linear regression models were fitted to evaluate mortality risk and associated factors with SOPi, respectively. Subgroup analysis of SOPi changes was performed by linear mixed-effects models. Results: In the total population (n = 5888, age 69.5 +- 9.1 years, BMI 27.5 +- 4.3 kg/m2, 56.8% females) and over the 9.9-year median follow-up period, 1538 (26.1%) participants died. Each standard deviation (SD) increase in sex-specific SOPi was associated with a 10% higher risk of premature death (HR = 1.10 [95%CI: 1.07; 1.13]). Thirteen factors were associated with high SOPi, such as reduced physical activity, higher triglyceride-glucose index, HOMA-IR, systemic inflammation, osteopenia, hypertension, liver steatosis, asthma, coronary heart disease, oral corticosteroid use, lower protein intake, lower quality of life and lower educational status. In participants with obesity, lower physical activity and/or insulin resistance (n = 1682), a significantly higher and faster increase in SOPi was observed compared to participants without these factors (males: β = 2.63 [95%CI: 2.22; 3.03]; females: β = 2.90 [95%CI: 2.58; 3.23]). Conclusion: SOPi is a significant predictor of premature death and can identify associated factors, particularly useful among persons at risk of SO. SOPi is higher and increases faster in individuals with specific phenotypes. SOPi integrates prognosis information, which could be used as a risk indicator and for prevention of SO.

Klasifikace

  • Druh

    J<sub>imp</sub> - Článek v periodiku v databázi Web of Science

  • CEP obor

  • OECD FORD obor

    30227 - Geriatrics and gerontology

Návaznosti výsledku

  • Projekt

    <a href="/cs/project/8F21001" target="_blank" >8F21001: Preventing obesity, sarcopenia, and Sarcopenic Obesity in retirement – digital personalized interventions for healthy NUTrition and physical activity for Seniors</a><br>

  • Návaznosti

    V - Vyzkumna aktivita podporovana z jinych verejnych zdroju

Ostatní

  • Rok uplatnění

    2025

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název periodika

    Journal of Cachexia, Sarcopenia and Muscle

  • ISSN

    2190-5991

  • e-ISSN

    2190-6009

  • Svazek periodika

    16

  • Číslo periodika v rámci svazku

    5

  • Stát vydavatele periodika

    US - Spojené státy americké

  • Počet stran výsledku

    12

  • Strana od-do

    e70099

  • Kód UT WoS článku

    001602613400038

  • EID výsledku v databázi Scopus

    2-s2.0-105018789875