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Comparison of lipid accumulation product and body mass index as indicators of diabetes diagnosis among 215,651 Chinese adults.

Authors
  • Tian, Tian1
  • Pei, Hualian1
  • Chen, Zhen1
  • Hailili, Gulisiya1
  • Wang, Shuxia2
  • Sun, Yong2
  • Yao, Hua2
  • Jianghong, Dai1
  • 1 School of Public Health, Xinjiang Medical University, Urumqi, China. , (China)
  • 2 School of Health Management, Xinjiang Medical University, Urumqi, China. , (China)
Type
Published Article
Journal
PeerJ
Publisher
PeerJ
Publication Date
Jan 01, 2020
Volume
8
Identifiers
DOI: 10.7717/peerj.8483
PMID: 32095339
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

We aimed to assess if lipid accumulation product (LAP) could outperform body mass index (BMI) as a marker for diabetes diagnosis. We analyzed the results of a national physical examination project in Urumqi, China. This project was conducted in 442 community clinics in Urumqi from October 2016 to February 2017. LAP was highly correlated with diabetes. The subjects with higher amounts of LAP had a higher risk of diabetes, and the prevalence of diabetes in the fourth quartile of LAP was dramatically higher than in the first quartile (5.72% vs. 21.76%). The adjusted odds ratios (AOR) associated with diabetes in the fourth quartile of LAP was significantly higher than the AOR associated with diabetes in the first quartile, and when BMI ≥ 28 kg/m2 was compared with BMI < 28 kg/m2 (3.24 (3.11, 3.37) vs. 1.65 (1.60, 1.70)). The LAP's area under the curve (AUC) was significantly higher than the BMI's AUC when based on diabetes (0.655 vs. 0.604). In the normal BMI group, 34% of participants had a LAP value higher than the cutoff point found during ROC analysis. In this subgroup, we observed a significantly higher prevalence of diabetes that was similar to that of the subgroup with a BMI ≥ 28 kg/m2, and both of their LAP values were higher than the cutoff point. When use as a tool for diabetes diagnosis, LAP performed better than BMI, implying that LAP could be a preferable anthropometry assessment. © 2020 Tian et al.

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