Correlation between skeletal muscle mass to visceral fat area ratio,inflammatory factors, and insulin resistance in patients with type 2 diabetes Article Swipe
xiaohua li
,
Si-yun Tang
,
Jing Li
,
Hui Wu
,
Yichen Lu
,
Rui-li Cao
,
Gu-qin Lu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2904749/v1
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2904749/v1
objective To explore the correlation between Skeletal muscle mass and visceral fat area ratio (Skeletal muscle mass to visceral fat area ratio (SVR), neutrophil/lymphocyte ratio (NLR) and insulin resistance (IR) in patients with type 2 diabetes mellitus (T2DM). Methods We investigated the SVR, NLR, and IR in 201 patients with T2DM who visited the Department of Endocrinology of the Seventh People's Hospital of Shanghai University of Traditional Chinese Medicine between June 2022 and March 2023. Appendicular skeletal muscle mass (ASM), total body fat (TBF), visceral fat area (VFA), and basal metabolic volume were measured using multifrequency bioimpedance analysis method. The percentage of body fat to body mass (TBF%), appendicular skeletal muscle mass index (ASMI), and SVR were calculated. Results Patients were divided equally into three groups (Q1–Q3) according to SVR levels. Compared with the Q3 group, in both Q1 and Q2 groups, waist-hip ratio, neutrophils, NLR, fasting blood glucose, fasting insulin, homeostasis model assessment of insulin resistance (HOMA-IR), triglycerides, total cholesterol, free fatty acid, TBF, TBF%, and VFA were all increased ( P < 0.005), whereas lymphocytes, insulin sensitivity index (ISI), ASM, ASMI, basal metabolic rate, and SVR were all decreased (P < 0.005). Conclusion NLR was negatively correlated with ASM, ASMI, SVR, and ISI (P < 0.005) and positively correlated with TBF, TBF%, VFA, and HOMA-IR (P < 0.005). SVR can predict IR in T2DM.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-2904749/v1
- https://www.researchsquare.com/article/rs-2904749/latest.pdf
- OA Status
- green
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4377098845
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4377098845Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.21203/rs.3.rs-2904749/v1Digital Object Identifier
- Title
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Correlation between skeletal muscle mass to visceral fat area ratio,inflammatory factors, and insulin resistance in patients with type 2 diabetesWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-05-19Full publication date if available
- Authors
-
xiaohua li, Si-yun Tang, Jing Li, Hui Wu, Yichen Lu, Rui-li Cao, Gu-qin LuList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-2904749/v1Publisher landing page
- PDF URL
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https://www.researchsquare.com/article/rs-2904749/latest.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://www.researchsquare.com/article/rs-2904749/latest.pdfDirect OA link when available
- Concepts
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Insulin resistance, Type 2 diabetes, Skeletal muscle, Internal medicine, Endocrinology, Medicine, Diabetes mellitus, Insulin, Correlation, Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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22Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W4200026682, https://openalex.org/W2069936148, https://openalex.org/W2067096633, https://openalex.org/W2623159596, https://openalex.org/W2100207948, https://openalex.org/W1972271334, https://openalex.org/W2966915859, https://openalex.org/W4200310486, https://openalex.org/W2038821689, https://openalex.org/W1976210931, https://openalex.org/W2132273917, https://openalex.org/W2163710303, https://openalex.org/W2569777444, https://openalex.org/W2060141430, https://openalex.org/W2107887255, https://openalex.org/W2053518007, https://openalex.org/W2767244506, https://openalex.org/W2333428640, https://openalex.org/W2060010293, https://openalex.org/W2890514041, https://openalex.org/W2066600159, https://openalex.org/W4200579112 |
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| abstract_inverted_index.SVR, | 43, 203 |
| abstract_inverted_index.T2DM | 51 |
| abstract_inverted_index.TBF, | 165, 213 |
| abstract_inverted_index.VFA, | 215 |
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| abstract_inverted_index.were | 93, 117, 121, 169, 189 |
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| abstract_inverted_index.2023. | 75 |
| abstract_inverted_index.ASMI, | 183, 202 |
| abstract_inverted_index.March | 74 |
| abstract_inverted_index.T2DM. | 226 |
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| abstract_inverted_index.fatty | 163 |
| abstract_inverted_index.index | 113, 180 |
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