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Low-density lipoprotein-cholesterol, total cholesterol to high-density lipoprotein-cholesterol ratio and triglyceride were specifically addressed in this study. This retrospective cohort study included 105,552 patients aged 45\u201384 with type 2 diabetes mellitus and normal kidney function who were managed under Hong Kong public primary care clinics during 2008\u20132012. Those with kidney disease (estimated glomerular filtration rate\u2009&lt;\u200960\u00a0mL\/min\/1.73\u00a0m<jats:sup>2<\/jats:sup> or urine albumin to creatinine ratio\u2009\u2265\u20093\u00a0mg\/mmol) were excluded. Variabilities of low-density lipoprotein-cholesterol, total cholesterol to high-density lipoprotein-cholesterol ratio and triglyceride were determined using the standard deviation of the respective parameter obtained from a mixed effects model to minimize regression dilution bias. The associations between lipid variability and renal outcomes including incident kidney disease, renal function decline defined as\u2009\u2265\u200930% reduction in estimated glomerular filtration rate since baseline, and end-stage renal disease (estimated glomerular filtration rate\u2009&lt;\u200915\u00a0mL\/min\/1.73\u00a0m<jats:sup>2<\/jats:sup>) were evaluated by multivariable Cox regression. After a median follow-up of 66.5\u00a0months (0.5 million person-years in total), 49,653 kidney disease, 29,358 renal function decline, and 1765 end-stage renal disease cases were recorded. Positive linear associations between low-density lipoprotein-cholesterol and total cholesterol to high-density lipoprotein-cholesterol ratio variabilities and the risk of all renal outcomes were demonstrated. However, no association between triglyceride variability and any outcome was found. Each mmol\/L increase in low-density lipoprotein-cholesterol variability was associated with 20% (Hazard ratio 1.20 [95% CI 1.15\u20131.25]), 38% (Hazard ratio 1.37 [95% CI 1.30\u20131.45]), and 108% (Hazard ratio 2.08 [95% CI 1.74\u20132.50]) higher risk in incident kidney disease, renal function decline and end-stage renal disease respectively. Similarly, each unit increase in total cholesterol to high-density lipoprotein-cholesterol ratio variability was associated with 35% (Hazard ratio 1.15 [95% CI 1.10\u20131.20]), 33% (Hazard ratio 1.33 [95% CI 1.26\u20131.40]), and 75% (Hazard ratio 1.75 [95% CI 1.46\u20132.09]) heightened risk in incident kidney disease, renal function decline and end-stage renal disease respectively. Cholesterol variability may potentially be a useful predictor of kidney diseases in patients with type 2 diabetes mellitus. Attention should be drawn to cholesterol variability when managing diabetic patients and further research is warranted to investigate the modifiable risk factors for lipid variability.<\/jats:p>","DOI":"10.1038\/s41598-021-87067-4","type":"journal-article","created":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T10:05:57Z","timestamp":1618308357000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Greater variability in lipid measurements associated with kidney diseases in patients with type 2 diabetes mellitus in a 10-year diabetes cohort study"],"prefix":"10.1038","volume":"11","author":[{"given":"Eric Yuk Fai","family":"Wan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Esther Yee Tak","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weng Yee","family":"Chin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christie Sze Ting","family":"Lau","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Anna Hoi Ying","family":"Mok","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ian Chi Kei","family":"Wong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Esther Wai Yin","family":"Chan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cindy Lo Kuen","family":"Lam","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,4,13]]},"reference":[{"key":"87067_CR1","doi-asserted-by":"publisher","first-page":"A7","DOI":"10.1053\/j.ajkd.2018.01.002","volume":"71","author":"R Saran","year":"2018","unstructured":"Saran, R. et al. 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E.W.Y.C. received research grants from Bayer, Bristol-Myers Squibb, Janssen, a Division of Johnson and Johnson, Pfizer, and Takeda to evaluate real world evidence on pharmacological treatments of cardiovascular diseases but not related to current study. Other authors declare that they have no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"8047"}}