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Li S, Hou L, Zhu S, Yi Q, Liu W, Zhao Y, Wu F, Li X, Pan A, Song P. Lipid Variability and Risk of Cardiovascular Diseases and All-Cause Mortality: A Systematic Review and Meta-Analysis of Cohort Studies. Nutrients 2022; 14:nu14122450. [PMID: 35745179 PMCID: PMC9231112 DOI: 10.3390/nu14122450] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 06/04/2022] [Accepted: 06/10/2022] [Indexed: 11/16/2022] Open
Abstract
No consensus has yet been reached on the associations of lipid variability (LV) with cardiovascular diseases (CVDs) and all-cause mortality. We aimed to quantify the associations of different types and metrics of LV with CVDs and all-cause mortality. PubMed, Medline, and Embase databases were searched for eligible cohort studies published until 14 December 2021. Lipids included total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). Metrics of variability included standard deviation (SD), coefficient of variation (CV), and variation independent of the mean (VIM). The primary outcomes were CVDs and all-cause mortality. Random-effects meta-analysis was used to generate a summary of the relative risks (SRRs). Sources of heterogeneity were explored by subgroup analysis and meta-regression. A total of 11 articles based on seven cohorts were included. Participants in the top quartile of TC variability had an increased risk of CVDs (vs. bottom quartile: TC-CV: SRR 1.29, 95% CI 1.15-1.45; TC-SD: 1.28, 1.15-1.43; TC-VIM: 1.26, 1.13-1.41, respectively) and all-cause mortality (vs. bottom quartile: TC-CV: 1.28, 1.15-1.42; TC-SD: 1.32, 1.22-1.44; TC-VIM: 1.32, 1.25-1.40, respectively). Participants in the top quartile of HDL-C variability had an increased risk of CVDs (vs. bottom quartile: HDL-C-CV: 1.11, 1.07-1.15; HDL-C-SD: 1.18, 1.02-1.38; HDL-C-VIM: 1.18, 1.09-1.27, respectively) and all-cause mortality (vs. bottom quartile: HDL-C-CV: 1.29, 1.27-1.31; HDL-C-SD: 1.24, 1.09-1.41; HDL-C-VIM: 1.25, 1.22-1.27, respectively). LDL-C variability was also associated with an increased risk of CVDs (for top vs. bottom quartile; LDL-C-SD: 1.09, 1.02-1.17; LDL-C-VIM: 1.16, 1.02-1.32, respectively) and all-cause mortality (for top vs. bottom quartile; LDL-C-CV: 1.19, 1.04-1.36; LDL-C-SD: 1.17, 1.09-1.26, respectively). The relationships of TG variability with the risk of CVDs and all-cause mortality were inconclusive across different metrics. The effects of SRR became stronger when analyses were restricted to studies that adjusted for lipid-lowering medication and unadjusted for mean lipid levels. These findings indicate that the measurement and surveillance of lipid variability might have important clinical implications for risk assessment of CVDs and all-cause mortality.
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Affiliation(s)
- Shuting Li
- School of Public Health and Women’s Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China; (S.L.); (L.H.); (S.Z.); (Q.Y.); (W.L.)
| | - Leying Hou
- School of Public Health and Women’s Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China; (S.L.); (L.H.); (S.Z.); (Q.Y.); (W.L.)
| | - Siyu Zhu
- School of Public Health and Women’s Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China; (S.L.); (L.H.); (S.Z.); (Q.Y.); (W.L.)
| | - Qian Yi
- School of Public Health and Women’s Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China; (S.L.); (L.H.); (S.Z.); (Q.Y.); (W.L.)
| | - Wen Liu
- School of Public Health and Women’s Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China; (S.L.); (L.H.); (S.Z.); (Q.Y.); (W.L.)
| | - Yang Zhao
- The George Institute for Global Health, University of New South Wales, Sydney, NSW 2050, Australia;
- The George Institute for Global Health, Peking University Health Science Center, Beijing 100600, China
| | - Feitong Wu
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS 7000, Australia;
| | - Xue Li
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China;
| | - An Pan
- Ministry of Education Key Laboratory of Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430000, China;
| | - Peige Song
- School of Public Health and Women’s Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou 310058, China; (S.L.); (L.H.); (S.Z.); (Q.Y.); (W.L.)
- Correspondence: ; Tel.: +86-571-88981368
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Liu M, Chen X, Zhang S, Lin J, Wang L, Liao X, Zhuang X. Assessment of Visit-to-Visit Blood Pressure Variability in Adults With Optimal Blood Pressure: A New Player in the Evaluation of Residual Cardiovascular Risk? J Am Heart Assoc 2022; 11:e022716. [PMID: 35470678 PMCID: PMC9238602 DOI: 10.1161/jaha.121.022716] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Background There is a paucity of evidence regarding the association between visit‐to‐visit blood pressure variability and residual cardiovascular risk. We aimed to provide relevant evidence by determining whether high systolic blood pressure (SBP) variability in the optimal SBP levels still influences the risk of cardiovascular disease. Methods and Results We studied 7065 participants (aged 59.3±5.6 years; 44.3% men; and 82.9% White) in the ARIC (Atherosclerosis Risk in Communities) study with optimal SBP levels from visit 1 to visit 3. Visit‐to‐visit SBP variability was measured by variability independent of the mean in the primary analysis. The primary outcome was the major adverse cardiovascular event (MACE), defined as the first occurrence of all‐cause mortality, coronary heart disease, stroke, and heart failure. During a median follow‐up of 19.6 years, 2691 participants developed MACEs. After multivariable adjustment, the MACE risk was higher by 21% in participants with the highest SBP variability (variability independent of the mean quartile 4) compared with the lowest SBP variability participants (variability independent of the mean quartile 1) (hazard ratio, 1.21; 95% CI, 1.09–1.35). The restricted cubic spline showed that the hazard ratio for MACE was relatively linear, with a higher variability independent of the mean being associated with higher risk. These association were also found in the stratified analyses of participants with or without hypertension. Conclusions In adults with optimal SBP levels, higher visit‐to‐visit SBP variability was significantly associated with a higher risk of MACE regardless of whether they had hypertension. Therefore, it may be necessary to further focus on the visit‐to‐visit SBP variability even at the guideline‐recommended optimal blood pressure levels.
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Affiliation(s)
- Menghui Liu
- Department of Cardiology The First Affiliated Hospital of Sun Yat-Sen University Guangzhou People's Republic of China.,NHC Key Laboratory of Assisted Circulation (Sun Yat-sen University) Guangzhou People's Republic of China
| | - Xiaohong Chen
- Department of Otorhinolaryngology The Third Affiliated Hospital of Sun Yat-Sen University Guangzhou People's Republic of China
| | - Shaozhao Zhang
- Department of Cardiology The First Affiliated Hospital of Sun Yat-Sen University Guangzhou People's Republic of China.,NHC Key Laboratory of Assisted Circulation (Sun Yat-sen University) Guangzhou People's Republic of China
| | - Junfan Lin
- Sun Yat-sen University School of Medicine Guangzhou People's Republic of China
| | - Lichun Wang
- Department of Cardiology The First Affiliated Hospital of Sun Yat-Sen University Guangzhou People's Republic of China.,NHC Key Laboratory of Assisted Circulation (Sun Yat-sen University) Guangzhou People's Republic of China
| | - Xinxue Liao
- Department of Cardiology The First Affiliated Hospital of Sun Yat-Sen University Guangzhou People's Republic of China.,NHC Key Laboratory of Assisted Circulation (Sun Yat-sen University) Guangzhou People's Republic of China
| | - Xiaodong Zhuang
- Department of Cardiology The First Affiliated Hospital of Sun Yat-Sen University Guangzhou People's Republic of China.,NHC Key Laboratory of Assisted Circulation (Sun Yat-sen University) Guangzhou People's Republic of China
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