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Abstract (English)

Obesity and sarcopenic obesity (SO) are characterized by excess body fat with or without low muscle mass affecting bio‐psycho‐social health, functioning, and subsequently quality of life in older adults. We mapped outcomes addressed in randomized controlled trials (RCTs) on lifestyle interventions in community‐dwelling older people with (sarcopenic) obesity. Systematic searches in Medline, Embase, Cochrane Central, CINAHL, PsycInfo, Web of Science were conducted. Two reviewers independently performed screening and extracted data on outcomes, outcome domains, assessment methods, units, and measurement time. A bubble chart and heat maps were generated to visually display results. Fifty‐four RCTs (7 in SO) reporting 464 outcomes in the outcome domains: physical function (n = 42), body composition/anthropometry (n = 120), biomarkers (n = 190), physiological (n = 30), psychological (n = 47), quality of life (n = 14), pain (n = 4), sleep (n = 2), medications (n = 3), and risk of adverse health events (n = 5) were included. Heterogeneity in terms of outcome definition, assessment methods, measurement units, and measurement times was found. Psychological and quality of life domains were investigated in a minority of studies. There is almost no information beyond 52 weeks. This evidence map is the first step of a harmonization process to improve comparability of RCTs in older people with (sarcopenic) obesity and facilitate the derivation of evidence‐based clinical decisions.

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Obesity reviews, 23 (2022), 10, e13497. https://doi.org/10.1111/obr.13497. ISSN: 1467-789X
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English

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610 Medicine and health

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Sustainable Development Goals

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@article{Galicia Ernst2022, url = {https://hohpublica.uni-hohenheim.de/handle/123456789/16531}, doi = {10.1111/obr.13497}, author = {Galicia Ernst, Isabel and Torbahn, Gabriel and Schwingshackl, Lukas et al.}, title = {Outcomes addressed in randomized controlled lifestyle intervention trials in community‐dwelling older people with (sarcopenic) obesity - an evidence map}, journal = {Obesity reviews}, year = {2022}, volume = {23}, number = {10}, }
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