Association between Glycosylated Hemoglobin and Serum Uric Acid: A US NHANES 2011-2020

Abstract

Background: Serum uric acid (SUA) and glycosylated hemoglobin (HbA1c) were closely related to the body's metabolism. This study aimed to investigate the relationship between HbA1c and SUA in adults.

Methods: This study selected 7293 participants aged ≥20 from 2011 to 2020 in the National Health and Nutrition Examination Survey (NHANES). The multivariate linear regression model was used to test the association between HbA1c and SUA. Subgroup analysis was performed according to age, gender, race, and body mass index (BMI). This study solved the relationship between HbA1c and SUA by fitting a smooth curve. Finally, the inflection point in the nonlinear relationship was calculated by the recursive algorithm, and the relationship between HbA1c and SUA on both sides of the inflection point was analyzed by the two-segment piecewise linear regression model.

Results: All 7293 participants found a negative correlation between HbA1c and SUA by completely adjusting the model (β = -7.93 and 95% CI: -9.49--6.37). In addition, when this study was stratified by gender, age, race, and BMI status, this negative correlation was still statistically significant. In the subgroup analysis, we found that the relationship between the two had different results due to gender differences. In men, HbA1c had a significant negative correlation with SUA. However, in women, the HbA1c value was positively correlated with SUA before 6.8%, and the HbA1c value was negatively correlated with SUA after 6.8%, which indicates that the relationship between HbA1c and SUA in women has changed in prediabetes and diabetes.

Conclusion: This study shows that HbA1c is positively correlated with SUA in American adults before 7%. There is a negative correlation after the HbA1c value of 7%.

Figure 1

Flowchart of participant selection. NHANES, National Health and Nutrition Examination Survey; HbA1c, glycosylated hemoglobin; SUA, serum uric acid.

Figure 2

The association between Hb1Ac and SUA. (a) The solid red line represents the smooth curve fit between variables. Blue bands represent the 95% confidence interval from the fit. (b) Each black point represents a sample. Age, sex, race/ethnicity, education level, the ratio of family income to poverty, BMI, energy intake, protein intake, carbohydrate intake, dietary fiber intake, total fat intake, LDL-C, HDL-C, TG, TCHO, urine albumin, urine creatinine, urine albumin creatinine ratio, SBP, DBP, heavy alcohol consumption, smoking status, and minutes sedentary activity were adjusted.

Figure 3

The association between HbA1c and SUA stratified by age. Sex, race/ethnicity, education level, the ratio of family income to poverty, BMI, energy intake, protein intake, carbohydrate intake, dietary fiber intake, total fat intake, LDL-C, HDL-C, TG, TCHO, urine albumin, urine creatinine, urine albumin creatinine ratio, SBP, DBP, heavy alcohol consumption, smoking status, and minutes sedentary activity were adjusted.

Figure 4

The association between HbA1c and SUA stratified by sex. Age, race/ethnicity, education level, the ratio of family income to poverty, BMI, energy intake, protein intake, carbohydrate intake, dietary fiber intake, total fat intake, LDL-C, HDL-C, TG, TCHO, urine albumin, urine creatinine, urine albumin creatinine ratio, SBP, DBP, heavy alcohol consumption, smoking status, and minutes sedentary activity were adjusted.

Figure 5

The association between HbA1c and SUA stratified by race/ethnicity. Age, sex, education level, the ratio of family income to poverty, BMI, energy intake, protein intake, carbohydrate intake, dietary fiber intake, total fat intake, LDL-C, HDL-C, TG, TCHO, urine albumin, urine creatinine, urine albumin creatinine ratio, SBP, DBP, heavy alcohol consumption, smoking status, and minutes sedentary activity were adjusted.

Figure 6

The association between HbA1c and SUA stratified by BMI. Age, sex, race/ethnicity, education level, the ratio of family income to poverty, energy intake, protein intake, carbohydrate intake, dietary fiber intake, total fat intake, LDL-C, HDL-C, TG, TCHO, urine albumin, urine creatinine, urine albumin creatinine ratio, SBP, DBP, heavy alcohol consumption, smoking status, and minutes sedentary activity were adjusted.