{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T06:14:03Z","timestamp":1774332843916,"version":"3.50.1"},"reference-count":27,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T00:00:00Z","timestamp":1721779200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T00:00:00Z","timestamp":1721779200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Endocr Disord"],"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Dysfunction of cholesterol metabolism may be associated with low skeletal muscle mass. \u00a0This study aimed to explore the relationship between skeletal muscle mass and cholesterol metabolic disorders in adults.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>The 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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>There 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.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>SMR 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.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12902-024-01660-y","type":"journal-article","created":{"date-parts":[[2024,7,24]],"date-time":"2024-07-24T03:31:06Z","timestamp":1721791866000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Crosstalk between skeletal muscle ratio and cholesterol metabolism disorders: a cross-section study"],"prefix":"10.1186","volume":"24","author":[{"given":"Yunle","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chunxing","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lijuan","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,24]]},"reference":[{"issue":"16","key":"1660_CR1","doi-asserted-by":"publisher","first-page":"1557","DOI":"10.1056\/NEJMra1806939","volume":"381","author":"ED Michos","year":"2019","unstructured":"Michos ED, McEvoy JW, Blumenthal RS. 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