Table 2_Association between cumulative changes of the C-reactive protein-triglyceride gluc

6,888 individuals aged 45 and older from the 2011 and 2015 China Health and Retirement Longitudinal Study (CHARLS) were analyzed over a four-year period, with 262 participants (3.8%) developing rapid kidney function decline. The dataset supports a study exploring associations between cumulative changes in a combined inflammatory-metabolic index (CTI) and kidney health outcomes. It was authored by Lina Huang and last updated on figshare in April 2026.

Use Cases

• Modeling the association between cumulative biomarker changes and kidney function decline based on multivariate logistic regression results.
• Conducting subgroup analyses for risk factors like sex, education, and comorbidities mentioned in the description.
• Validating findings in a supplementary cross-sectional analysis using NHANES data, as described.
• Investigating dose-response patterns between an inflammatory-metabolic index and renal outcomes using restricted cubic spline models.

Strengths

• Data from 6,888 individuals provides a substantial cohort for analysis.
• Results were validated through sensitivity analyses on original, imputed, and pooled datasets.
• Supplementary analysis used NHANES data, suggesting external validation efforts.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset is very small at 16.7 KB, indicating it likely contains summary or processed results rather than raw individual-level data.

Provenance

Source

China Health and Retirement Longitudinal Study (CHARLS) and National Health and Nutrition Examination Survey (NHANES).

Collection Method

Analysis of longitudinal cohort data using multivariate logistic regression and restricted cubic spline models.

Time Range

Covers a four-year period from the 2011 and 2015 CHARLS waves.

Freshness

Last updated 2026-04-13 05:21:05; freshness should be verified.

Geography

Primary data from China (CHARLS), with supplementary data from the United States (NHANES).