The haemoglobin glycation index is associated with nonalcoholic fatty liver disease in healthy subjects

Yoo, Jee Hee; Kang, Yu Mi; Cho, Yun Kyung; Lee, Jiwoo; Jung, Chang Hee; Park, Joong‐Yeol; Ryu, Ohk Hyun; Kim, Hong‐Kyu; Lee, Woo Je

doi:10.1111/cen.14001

Cited by 17 publications

(12 citation statements)

References 30 publications

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“…The new marker, HGI, which is calculated by FBG and HbA1c, reflects the individual discrepancy. In our study, participants with higher HGI also had higher levels of HbA1c and other metabolic parameters, including TC, LDL-C, in line with other studies reporting that high HGI individuals displayed an unfavorable cardio-metabolic risk [ 19 , 20 ]. The measurement of HGI is important since it would help to avoid misinterpretation of glycemic control and to avoid inappropriate therapeutic management [ 16 ].…”

Section: Discussionsupporting

confidence: 91%

“…HGI was found to be positively associated with cardiovascular disease, microvascular and macrovascular complications, and mortality in patients with diabetes [ 16 ]. It was also reported that high HGI was related to some cardiometabolic risk factors including triglycerides, SUA, fasting insulin, inflammatory markers, carotid atherosclerosis and nonalcoholic fatty liver disease in non-diabetic individuals [ 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

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Interaction of sex and diabetes on the association between hemoglobin glycation index, hemoglobin A1c and serum uric acid

Ying

Wang

et al. 2022

Diabetol Metab Syndr

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Background Hemoglobin glycation index (HGI), which is calculated by blood glucose and hemoglobin A1c(HbA1c), reflects the individual discrepancy in HbA1c. This study aimed to investigate the association between HGI/HbA1c and serum uric acid(SUA) stratified by sex and diabetes. Methods The study recruited 33772 participants who underwent physical examinations between April 2016 and August 2021 in Beijing Chao-Yang Hospital. A random subsample of 3000 subjects was utilized to calculate the formula of HGI and data of the remaining 30772 participants were used for analysis. HGI and HbA1c were categorized according to quartiles (Q1, Q2, Q3, Q4), using Q1 as the reference. We used multiple linear regression and restricted cubic splines for data analysis. Results 30772 participants with a mean age of 44.4 years old were included in the analysis, 48.6% (N = 14944) of which were female and 7.7% (N = 2363) with diabetes. Associations of HGI, HbA1c and SUA were modified by sex and diabetes. The relationship between SUA levels and HGI was positive in women without diabetes, with one unit increase in HGI associating with an 11.3 μmol/L increase in SUA (P < 0.001) after adjusting for other confounders. On average, each one-unit increase in HbA1c was associated with a 14.3 μmol/L decrease in SUA in women with diabetes, a 14.9 μmol/L decrease in SUA in men with diabetes, and a 16.5 μmol/L increase in SUA in women without diabetes (all P < 0.001). The SUA levels in men without diabetes showed a bell-shaped relation with HbA1c, increasing as the HbA1c rose to around 5.7% and then falling with a further increase of HbA1c (P < 0.001). Conclusions SUA levels were inversely correlated with HbA1c in diabetic patients, also in men with prediabetes (HbA1c ≥ 5.7%), but positively correlated with HbA1c and HGI in women without diabetes. Glycemic control may help to reduce the risk of hyperuricemia in non-diabetes women.

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Section: Discussionsupporting

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Interaction of sex and diabetes on the association between hemoglobin glycation index, hemoglobin A1c and serum uric acid

Ying

Wang

et al. 2022

Diabetol Metab Syndr

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“…Data are expressed as the mean ± SD for continuous variables and as a percentage for categorical variables 47 . Comparisons between baseline characteristics according to sex-specific SMI tertiles and sarcopenic obese status were made using a one-way analysis of variance (ANOVA) with Bonferroni's method for continuous variables, and chi-square test with linear by linear analysis was used in categorical variables 47 . Cumulative event rates for incident albuminuria were estimated by Kaplan-Meier survival curves, and equalities were compared with the log-rank test.…”

Section: Measurement Of Skeletal Muscle Mass Indexmentioning

confidence: 99%

Effects of low skeletal muscle mass and sarcopenic obesity on albuminuria: a 7-year longitudinal study

Yoo

Kim

Park

et al. 2020

Sci Rep

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We aimed to identify the association between low skeletal muscle, sarcopenic obesity, and the incidence of albuminuria in the general population using a longitudinal study. Data from 29,942 subjects who underwent two or more routine health examinations from 2006 to 2013 were retrospectively reviewed. Relative skeletal muscle mass was presented using the skeletal muscle mass index (SMI), a measure of body weight-adjusted appendicular skeletal muscle mass estimated by bioelectrical impedance analysis. The cumulative incidence of albuminuria was 981 (3.3%) during the 7-year follow-up period. The hazard ratio of incident albuminuria was 1.44 (95% CI: 1.22-1.71, p for trend <0.001) in the lowest SMI tertile relative to the highest SMI tertile after multivariable adjustment. After additionally adjusting for general and central obesity, the hazard ratio was 1.35 (95% CI: 1.13-1.61, p for trend = 0.001) and 1.30 (95% CI: 1.08-1.56, p for trend = 0.003), respectively. Furthermore, the risk of developing albuminuria was much higher in the sarcopenic obesity group (HR: 1.49, 95% CI: 1.21-1.81, p for trend <0.001) compared to the other groups. Sarcopenic obesity, as well as low skeletal muscle, may lead to albuminuria in general populations.Low muscle mass or sarcopenia is defined as a progressive decrease in muscle mass and strength by aging, which can lead to the progression of chronic metabolic diseases and eventually leads to morbidity and mortality 1 . Recently, sarcopenia and obesity have been reported to synergistically worsen functional decline and outcomes than either condition alone. Moreover, the population is getting older and the prevalence of obesity is rapidly increasing in Asia 2,3 . Therefore, sarcopenia and obesity have emerged as a major health issue worldwide, including Korea 4,5 .Albuminuria is a risk marker for endothelial cell dysfunction, which leads to cardiovascular and kidney disease not only in patients with diabetes or hypertension but also in the general population 6-10 . Moreover, albuminuria is independently associated with all-cause mortality 11,12 .Several cross-sectional studies suggest that both sarcopenia and obesity are individually associated with the prevalence of albuminuria in subjects with diabetes and hypertension 13,14 . Even in healthy populations, both sarcopenia and obesity have consistently emerged as significant risk factors for albuminuria in cross-sectional settings [15][16][17][18][19] .However, the causal relationship between low muscle mass and albuminuria in longitudinal data has not been elucidated. Even though obesity may exaggerate functional decline with sarcopenia, the association between sarcopenic obesity and albuminuria has not been established.Therefore, this study examines whether subjects with low skeletal muscle mass have higher incidences of albuminuria in a large population-based 7-year longitudinal study. In addition, we further explored the combined effects of sarcopenia and obesity on the risk of developing albuminuria.

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“…Obviously, HGI has been used to represent the nonenzymatic protein glycation, which is known to play a key role in the pathogenesis of NAFLD [20,21]. However, only two studies had been carried out to assess the correlation between HGI and NAFLD in nondiabetic individuals [17,22]. e aims of our study were (1) to assess the prevalence of NAFLD among nondiabetic Chinese adults; (2) to investigate whether HGI is associated with the prevalence of NAFLD and related to biomarkers in Chinese nondiabetic subjects; and (3) to construct a risk score to conveniently predict a person's risk of NAFLD.…”

Section: Introductionmentioning

confidence: 99%

Association between Hemoglobin Glycation Index and NAFLD in Chinese Nondiabetic Individuals

Zhu

et al. 2019

Canadian Journal of Gastroenterology and Hepatology

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Purpose. Limited studies have preliminarily identified a positive association between nonalcoholic fatty liver disease (NAFLD) and hemoglobin glycation index (HGI). However, this association has not been fully established. We aim to investigate the association between NAFLD and HGI in Chinese nondiabetic individuals and to construct a risk score based on HGI to predict a person’s risk of NAFLD. Methods. After strict exclusion criteria, 5,903 individuals were included in this retrospective cross-sectional study. We randomly selected 1,967 subjects in the enrollment to obtain an equation of linear regression, which was used to calculate predicted HbA1c and drive HGI. The other subjects were classified into four categories according to HGI level (≤−0.22, −0.21∼0.02, 0.03∼0.28, and ≥0.29). All subjects retrospectively reviewed the baseline characteristics, laboratory examinations, and abdominal ultrasonography. Results. The prevalence of NAFLD in this population was 20.7%, which increases along with the growth of HGI levels (P<0.001). Adjusted to multiple factors, this trend still remained significant (OR: 1.172 (95% CI, 1.074–1.279)). The combined NAFLD risk score based on HGI resulted in an area under the receiver operator characteristic curve (AUROC) of 0.85 provided sensitivity, specificity, positive predictive value, and a negative predictive value for NAFLD of 84.4%, 71.3%, 65.0%, and 88.0%, respectively. Conclusions. NAFLD is independently associated with HGI levels in Chinese nondiabetic individuals. And, NAFLD risk score may be used as one of the risk predictors of NAFLD in nondiabetic population.

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The haemoglobin glycation index is associated with nonalcoholic fatty liver disease in healthy subjects

Cited by 17 publications

References 30 publications

Interaction of sex and diabetes on the association between hemoglobin glycation index, hemoglobin A1c and serum uric acid

Interaction of sex and diabetes on the association between hemoglobin glycation index, hemoglobin A1c and serum uric acid

Effects of low skeletal muscle mass and sarcopenic obesity on albuminuria: a 7-year longitudinal study

Association between Hemoglobin Glycation Index and NAFLD in Chinese Nondiabetic Individuals

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