Evidence map›Paper›PMID 39044230›Full record

ArticleBMC endocrine disorders2024

Crosstalk between skeletal muscle ratio and cholesterol metabolism disorders: a cross-section study.

Yunle Wang, Jun Hu, Hui Shen, Chunxing Liu, Lijuan Yang

Abstract read
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Article in BMC endocrine disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yunle Wang *Geriatrics Department, Shanghai Health and Medical Center, 67 Dajishan, Wuxi, Jiangsu, 214000, China.
Jun Hu *Health Care Center, Shanghai Health and Medical Center, Wuxi, China.
Hui ShenNutritional Department, Shanghai Health and Medical Center, Wuxi, China.
Chunxing LiuMedical Laboratory Department, Shanghai Health and Medical Center, Wuxi, China.
Lijuan YangGeriatrics Department, Shanghai Health and Medical Center, 67 Dajishan, Wuxi, Jiangsu, 214000, China. yanglijuan8527@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDysfunction of cholesterol metabolism may be associated with low skeletal muscle mass.  This study aimed to explore the relationship between skeletal muscle mass and cholesterol metabolic disorders in adults.

methodsThe data of a total of 5949 people with complete medical history data, biochemical data and body composition analysis were recruited. According to the serum cholesterol, low density lipoprotein (LDL), high density lipoprotein (HDL) and nonHDL, the population was divided into a disorder group and a normal group. Independent sample t tests, chi-square tests, Pearson's correlation analyses and binary logistic regression analyses were used to study the effect of body composition on abnormal cholesterol metabolism. According to BMI and sex, the population was divided into different subgroups, and binary logistic regression analysis was used to study the effect of the skeletal mass ratio on cholesteral metabolic disorders in different subgroups.

resultsThere were significant differences in sex, alcohol consumption, body weight, BMI, skeletal muscle mass index (SMI) [total skeletal muscle mass (kg)/height 2 (m2)] and skeletal muscle mass ratio (SMR) [total skeletal muscle mass (kg)/weight (kg) *100] between the disorder group (hypercholesterolemia, hyper-LDL, lower-HDL and hyper-nonHDL) and the normal group. Pearson correlation analysis revealed that the SMR was negatively correlated, while the SMI was positively correlated with cholesterol metabolic disorders in both sexes. The overweight group was older and had a greater SMI, abnormal cholesteral metabolism ratio and lower SMR than the normal-weight group. In the normal-weight group, the SMR was an independent protective factor against different kinds of cholesteral metabolic disorders in both sexes, while the SMI was a risk factor. In the overweight subgroup, the protective effect on HDL and nonHDL metabolism remained in the male subgroup but disappeared in the female subgroup. However, the SMI was an independent risk factor for different kinds of cholesteral metabolic disorders in both sexes.

conclusionsSMR was an independent protective factor against cholesterol metabolic disorders in both males and females, especially in the normal weight group. SMI was an independent risk factor, especially in the overweight group.

Indexed as

CholesterolMuscle, SkeletalAdultAgedBody CompositionBody Mass IndexCross-Sectional StudiesFemaleHumansMaleMiddle AgedCholesterolBMIBody composition analysisHypercholesterolemiaSkeletal muscle indexSkeletal muscle mass ratio

Identifiers

PMID39044230
PMCPMC11267780

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.