Frontiers in endocrinology · 2026
Nontraditional lipid and lipid-inflammatory parameters for risk stratification of abnormal glucose metabolism: a cross-sectional study in Chinese adults.
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Chen Dan-Jing, Fang Hua, Wu Sheng-Gen, Si Wen, Wang Shi-Yuan, Liu Li-Zhi, Han Ying, Peng Xian-E
Аннотация
OBJECTIVE: To evaluate the associations and diagnostic ability of non-traditional lipid parameters and lipid-inflammation parameters with abnormal glucose metabolism, and to investigate the mediating role of high-sensitivity C-reactive protein (hs-CRP).
METHODS: Based on cross-sectional survey data from 9,790 adults in Fujian Province, China (2020-2021), 2,301 participants were included in the analysis. Eight non-traditional lipid parameters and lipid-inflammation parameters incorporating hs-CRP were calculated. Associations with impaired glucose metabolism were examined using ordinal logistic regression, restricted cubic spline analysis, and subgroup analyses. Incremental diagnostic ability was evaluated using receiver operating characteristic curve analysis, C-statistics, net reclassification improvement, and integrated discrimination improvement. Mediation analysis was performed to examine the role of hs-CRP.
RESULTS: All parameters were significantly positively associated with impaired glucose metabolism, with several showing nonlinear dose-response relationships. Subgroup analyses demonstrated generally consistent associations with those in the overall population. In the prediabetes comparison, atherogenic coefficient, Castelli's index-I, remnant cholesterol-C-reactive protein index, and remnant cholesterol to high-density lipoprotein cholesterol-C-reactive protein index (RC/HDL-C-CRP) had superior diagnostic ability, whereas atherogenic index of plasma and RC/HDL-C-CRP performed better in the diabetic comparison. Mediation analysis indicated that hs-CRP partially mediated the association between non-traditional lipid parameters and prediabetes, with bidirectional mediation effects observed. No mediation effect was observed for diabetes risk.
CONCLUSION: Non-traditional lipid parameters and lipid-inflammation parameters were significantly associated with impaired glucose metabolism. Incorporating inflammatory information may enhance the identification of high-risk individuals, providing early warning particularly in prediabetic populations.
METHODS: Based on cross-sectional survey data from 9,790 adults in Fujian Province, China (2020-2021), 2,301 participants were included in the analysis. Eight non-traditional lipid parameters and lipid-inflammation parameters incorporating hs-CRP were calculated. Associations with impaired glucose metabolism were examined using ordinal logistic regression, restricted cubic spline analysis, and subgroup analyses. Incremental diagnostic ability was evaluated using receiver operating characteristic curve analysis, C-statistics, net reclassification improvement, and integrated discrimination improvement. Mediation analysis was performed to examine the role of hs-CRP.
RESULTS: All parameters were significantly positively associated with impaired glucose metabolism, with several showing nonlinear dose-response relationships. Subgroup analyses demonstrated generally consistent associations with those in the overall population. In the prediabetes comparison, atherogenic coefficient, Castelli's index-I, remnant cholesterol-C-reactive protein index, and remnant cholesterol to high-density lipoprotein cholesterol-C-reactive protein index (RC/HDL-C-CRP) had superior diagnostic ability, whereas atherogenic index of plasma and RC/HDL-C-CRP performed better in the diabetic comparison. Mediation analysis indicated that hs-CRP partially mediated the association between non-traditional lipid parameters and prediabetes, with bidirectional mediation effects observed. No mediation effect was observed for diabetes risk.
CONCLUSION: Non-traditional lipid parameters and lipid-inflammation parameters were significantly associated with impaired glucose metabolism. Incorporating inflammatory information may enhance the identification of high-risk individuals, providing early warning particularly in prediabetic populations.