Association of non-conventional lipid-inflammatory parameters with incident hypertension risk: a prospective cohort study.

Emerging research has associated non-conventional lipid indices with hypertension risk; however, the joint contribution of these lipid metrics and inflammatory biomarkers to hypertension susceptibility remains unclear. Using a nationally representative cohort, we aimed to examine the independent associations of non-conventional lipid indices and their inflammatory composites with incident hypertension.

We included 6891 participants from the China Health and Retirement Longitudinal Study (2011-2020). We used multivariable Cox proportional hazards regression to assess the association between baseline and cumulative non-conventional lipid-inflammatory parameters and incident hypertension. We used restricted cubic spline modelling to characterise dose-response relationships. We evaluated receiver operating characteristic curves, net reclassification improvement, and integrated discrimination improvement as secondary conditional analyses.

Over a median follow-up of 7.79 years, 2532 incident hypertension cases occurred. Higher tertiles of non-conventional lipid indices were associated with progressively increased hypertension risk. In the primary model, elevated baseline and cumulative non-conventional lipid metrics were associated with a higher risk of hypertension across all composite indices. The lipoprotein combine index-C-reactive protein showed the largest effect size (hazard ratio = 1.59; 95% confidence interval = 1.44-1.75). Composite indices demonstrated modest incremental discrimination over individual measures (area under the curve range = 0.55-0.58).

Non-conventional lipid indices are independently associated with incident hypertension among middle-aged and older Chinese adults. Composite lipid-inflammatory markers provide modest incremental prognostic information beyond conventional lipids, though their standalone discriminatory performance is weak.
Cardiovascular diseases
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Authors

Zhao Zhao, Wang Wang, Li Li, Wu Wu, Lu Lu, Li Li
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