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Associations of plasma very-long-chain SFA and the metabolic syndrome in adults

Published online by Cambridge University Press:  29 August 2018

Jing Zhao
Affiliation:
Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, 200031 Shanghai, People’s Republic of China
Xiaofan Li
Affiliation:
Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, 200031 Shanghai, People’s Republic of China
Xiang Li
Affiliation:
Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, 200031 Shanghai, People’s Republic of China
Qianqian Chu
Affiliation:
Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, 200031 Shanghai, People’s Republic of China
Yunhua Zhou
Affiliation:
Department of Anatomy, Histology and Embryology, School of Basic Medical Sciences, Fudan University, 200032 Shanghai, People’s Republic of China
Zi Li
Affiliation:
Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, 200031 Shanghai, People’s Republic of China
Hong Zhang
Affiliation:
Institute of Biostatistics, Fudan University, 200433 Shanghai, People’s Republic of China
Thomas J. Brenna
Affiliation:
Dell Pediatric Research Institute, Dell Medical School, University of Texas at Austin, Austin, TX 78705, USA Division of Nutritional Sciences, Cornell University, Ithaca, NY 14853, USA
Yiqing Song
Affiliation:
Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN 46202, USA
Ying Gao*
Affiliation:
Key Laboratory of Nutrition and Metabolism, Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, 200031 Shanghai, People’s Republic of China
*
*Corresponding author: Y. Gao, email yinggao@sibs.ac.cn
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Abstract

Plasma levels of very-long-chain SFA (VLCSFA) are associated with the metabolic syndrome (MetS). However, the associations may vary by different biological activities of individual VLCSFA or population characteristics. We aimed to examine the associations of VLCSFA and MetS risk in Chinese adults. Totally, 2008 Chinese population aged 35–59 years were recruited and followed up from 2010 to 2012. Baseline MetS status and plasma fatty acids data were available for 1729 individuals without serious diseases. Among 899 initially metabolically healthy individuals, we identified 212 incident MetS during the follow-up. Logistic regression analysis was used to estimate OR and 95 % CI. Cross-sectionally, each VLCSFA was inversely associated with MetS risk; comparing with the lowest quartile, the multivariate-adjusted OR for the highest quartile were 0·18 (95 % CI 0·13, 0·25) for C20 : 0, 0·26 (95 % CI 0·18, 0·35) for C22 : 0, 0·19 (95 % CI 0·13, 0·26) for C24 : 0 and 0·16 (0·11, 0·22) for total VLCSFA (all Pfor trend<0·001). The associations remained significant after further adjusting for C16 : 0, C18 : 0, C18 : 3n-3, C22 : 6n-3, n-6 PUFA and MUFA, respectively. Based on follow-up data, C20 : 0 or C22 : 0 was also inversely associated with incident MetS risk. Among the five individual MetS components, higher levels of VLCSFA were most strongly inversely associated with elevated TAG (≥1·7 mmol/l). Plasma levels of VLCSFA were significantly and inversely associated with MetS risk and individual MetS components, especially TAG. Further studies are warranted to confirm the findings and explore underlying mechanisms.

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Copyright
© The Authors 2018 
Figure 0

Table 1 Basic characteristics of subjects with and without the metabolic syndrome (MetS) at baseline (Mean values and standard deviations; frequencies and percentages)

Figure 1

Fig. 1 Risk of the metabolic syndrome by very-long-chain SFA (VLCSFA) levels at baseline. Lines represent OR (95 % CI) based on restricted cubic splines for VLCSFA levels with knots at the 5th, 50th and 95th percentiles. OR were estimated using a logistic regression model after adjustment for age, sex and agricultural work; bars represent the numbers of participants. (a) C20 : 0 (Pnon-linearity<0·001), (b) C22 : 0 (Pnon-linearity=0·002), (c) C24 : 0 (Pnon-linearity=0·021) and (d) total VLCSFA (Pnon-linearity<0·0001).

Figure 2

Table 2 The associations of very-long-chain SFA (VLCSFA) and prevalence of the metabolic syndrome (MetS) at baseline* (Odds ratios and 95 % confidence intervals)

Figure 3

Table 3 Associations of very-long-chain SFA (VLCSFA) and risk of the metabolic syndrome (MS) according to the number of MS components at baseline* (Odds ratios and 95 % confidence intervals)

Figure 4

Table 4 Associations of very-long-chain SFA (VLCSFA) and risk of incident metabolic syndrome (MetS) after 2 years* (Odds ratios and 95 % confidence intervals)

Figure 5

Fig. 2 Associations of very-long-chain SFA and risk of the metabolic syndrome components at baseline. Logistic regression was used to estimate the OR and CI. All the OR were adjusted for age, sex and agricultural work. The five components were adjusted in the models, except for itself. The five components were classified into high/low group according to the cut-off in the metabolic syndrome definition. BP, blood pressure; FBG, fasting blood glucose; WC, waist circumference.

Figure 6

Fig. 3 Stratified analysis of the associations of very-long-chain SFA (VLCSFA) and risk of the metabolic syndrome at baseline. All the OR were adjusted for age, sex and agricultural work. The OR meant the risk of the metabolic syndrome for 1 sd increase of VLCSFA.

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