The National Health and Nutrition Examination Survey (NHANES) in the United States is a research program designed to assess the health and nutritional status of adults and children in the country. Due to its adoption of a complex sampling design, it is imperative to correctly apply the weights provided by NHANES to ensure the accuracy and external validity of research results. This article first introduces the relevant concepts of the NHANES database and its weights, followed by a practical demonstration of weight selection, calculation, and implementation in the R programming language. It further discusses the significance of using weights in NHANES data and systematically showcases how to perform weighted analysis based on R, providing a valuable reference for relevant researchers.
ObjectiveTo investigate the association between the stress-induced hyperglycemia ratio (SHR) and all-cause, cardiovascular, and diabetes-related mortality in patients with advanced cardiovascular-kidney-metabolic (CKM) syndrome, and to evaluate the value of SHR as an independent prognostic marker. MethodsThis retrospective cohort study used data from the 1999–2018 U.S. National Health and Nutrition Examination Survey (NHANES). A total of 2 135 patients with advanced CKM (stages 3 and 4) were included. Kaplan-Meier analysis and multivariable Cox regression models were applied to assess the relationship between SHR and mortality outcomes. Restricted cubic spline (RCS) analysis was employed to explore potential non-linear associations. Subgroup analyses were conducted to identify possible effect modifiers. ResultsOver a mean follow-up of 248 months, 674 all-cause, 198 cardiovascular, and 31 diabetes-related deaths occurred. Elevated SHR was significantly associated with diabetes-related mortality (HR=3.48, P<0.001) in a dose-response manner. SHR exhibited a U-shaped relationship with both all-cause and cardiovascular mortality (non-linearity P<0.001), indicating increased risk at both low and high SHR levels. Subgroup analyses revealed that sex, BMI, and hyperlipidemia significantly modified the association between SHR and diabetes-related death. ConclusionSHR is an independent predictor of mortality risk in patients with advanced CKM syndrome, particularly for diabetes-related death. These findings support the integration of SHR into risk stratification of high-risk CKM populations and provide a basis for metabolic stress-targeted interventions.
ObjectiveTo preliminary investigate the association between systemic inflammatory biomarkers such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and diabetic retinopathy (DR). MethodsA cross-sectional study. A total of 5 999 patients diagnosed with diabetes in the NHANES database during the survey periods from 1999 to 2018 were included in the study. They were divided into the DR group (1 331 cases) and the non-DR group (4 668 cases) based on the presence or absence of DR. Demographic and laboratory data (including complete blood count, blood glucose, and lipid profiles) were collected, and NLR, PLR, and SII were calculated. The survey weights were used to handle the complex sampling design. After adjusting for confounding factors such as C-reactive protein, a weighted multivariate logistic regression model was applied to analyze the association between the logarithmically transformed and quartile-categorized NLR, PLR, SII and DR, and the odds ratio (OR) and its 95% confidence interval (CI) were calculated. Restricted cubic spline (RCS) was used to analyze the dose-response relationship, and subgroup analysis and interaction tests were conducted through Bonferroni correction. ResultsAfter multivariate adjustment, logistic regression analysis showed in the fully adjusted model with log transformation, neither SII (OR=1.160, 95%CI 0.756-1.780), NLR (OR=0.834, 95%CI 0.669-1.040), nor PLR (OR=1.360, 95%CI 0.859-2.154) showed statistically significant linear associations with DR (P＞0.05). RCS analysis indicated that SII showed no statistically significant overall association with DR (Poverall=0.062), but a non-linear relationship was observed (Pnon-linear=0.045). There was a significant non-linear dose-response relationship between PLR and DR (Poverall=0.011, Pnon-linear=0.009); and there was also a significant non-linear dose-response relationship between NLR and DR (Poverall=0.017, Pnon-linear=0.035). Subgroup analysis revealed that the absence of significant associations between SII, NLR, PLR and DR remained stable across different subgroups. ConclusionBased on a large sample cross-sectional study using the NHANES database, no independent linear association is found between PLR, NLR or SII and DR, and the results remain consistent across various subgroups.