Correlation between fatty liver index and estimated glomerular filtration rate in an elderly population in Yangzhou, China

doi:10.21203/rs.3.rs-2372540/v1

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Correlation between fatty liver index and estimated glomerular filtration rate in an elderly population in Yangzhou, China

https://doi.org/10.21203/rs.3.rs-2372540/v1

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OBJECTIVE: To investigate the correlation between fatty liver index (FLI) and estimated glomerular filtration rate (eGFR).

METHODS: We analyzed the correlation between fatty liver index (FLI) and estimated glomerular filtration rate (eGFR) in a cohort of elderly people who underwent physical examination at the Medical Examination Center of the Affiliated Hospital of Yangzhou University from 01/01/2020 to 12/31/2020, collected relevant data, and calculated the fatty liver index and estimated glomerular filtration rate.

RESULTS: A total of 7879 individuals were included in the analysis, and the results suggested that the probability of abnormal estimated glomerular filtration rate increased in the FLI≥30 group compared to the FLI<30 group, with abnormal estimated glomerular filtration rate of 66.37% and 62.19% in the two groups, respectively (P<0.001). Logistic regression analysis showed that the probability of abnormal estimated glomerular filtration rate increased by 0.7% for every 1 increase in FLI (OR=1.007, 95% CI 1.005-1.010, P<0.001).

CONCLUSION: Elevated FLI is associated with an increased risk of abnormalities in their estimated glomerular filtration rate in an elderly population in Yangzhou.

Non-alcoholic fatty liver disease(NAFLD) is a broader disease that can be used to describe a range of disorders associated with disorders of liver metabolism(1). With the global epidemic of obesity and metabolic syndrome, NAFLD is growing rapidly and is trending younger. NAFLD has become a major cause of chronic liver disease and increases the risk of end-stage liver disease, hepatocellular carcinoma (HCC), and liver-related all-cause mortality compared to the general population of similar age and sex (2, 3).The gold standard for confirming the diagnosis of NAFLD is liver aspiration. But the fatty liver index (FLI) is a simple index that can be used to evaluate the accumulation of fat in the liver and has a high sensitivity and specificity for the evaluation of fatty liver disease, and it can reflect the degree of hepatic steatosis more accurately than single indicators such as waist circumference and body weight(4). FLI also has a high sensitivity and specificity in the Chinese population(5).

Kidney disease is a major clinical and public health problem worldwide. Chronic kidney disease (CKD) is characterized by high prevalence, low awareness rate, poor prognosis and high medical costs, and is another serious health hazard after cardiovascular diseases, diabetes and After cardiovascular diseases, diabetes and malignant tumors, CKD is another serious health hazard. Therefore, earlier detection of abnormal glomerular filtration rate (GFR) will become significant. Due to the accuracy of the modification of diet in renal disease study(MDRD) formula for glomerular filtration rate estimation and the clinical availability of serum creatinine (Scr) values, assessment of early GFR changes became possible. The Chinese modified simplified modification of diet in renal disease study(MDRD) formula was developed by our researchers in 2006 on data from 684 Chinese chronic kidney disease(CKD) patients, making the MDRD formula applicable to our population(6).

Studies have shown that there is a high prevalence of non-alcoholic fatty liver disease in China. Nonalcoholic fatty liver disease is closely related to insulin resistance and metabolic syndrome, which not only leads to metabolic disorders in the liver, but also affects many related diseases, including diabetes, cardiovascular disease, chronic kidney disease, etc(2). In recent years, many scholars in China and abroad have begun to focus on the effects of nonalcoholic fatty liver disease on chronic kidney disease. The present study was designed to investigate the relationship between FLI and the abnormal rate of estimated glomerular filtration rate(eGFR) in an elderly population in Yangzhou.

2.1. Patient population

Older adults (≥60 years old) were selected for physical examination at the Medical Examination Center of the Affiliated Hospital of Yangzhou University from 01/01/2020 to 12/31/2020. After further excluding excessive alcohol drinkers (drinking equivalent ethanol amount, ≥140 g/week for men and ≥70 g/week for women), those who tested liver enzymes including alanine aminotransferase (ALT), aspartate aminotransferase (AST), and gamma-glutamyl transpeptidase (γ-GGT) greater than three times the reference range, and those with incomplete clinical data, 7879 study subjects were finally included in the statistical analysis(Fig 1). The clinical and laboratory data were retrospectively collected in the electronic medical record system.

Ethical approval was obtained from the research ethics committee of the Affiliated Hospital of Yangzhou University.Patients provided written informed consent. This study was performed in accordance with the Declaration of Helsinki.

2.2. FLI and eGFR

FLI calculation: Calculate FLI by referring to the formula given in the literature(4)

Where triglyceride(TG), body mass index(BMI), gamma-glutamyl transpeptidase (γ-GGT), waist Circumference (WC) units are mg/dL, kg/m2, U/L, cm. TG unit conversion 1mol/L = 0.01129mg/dL.

eGFR calculation: based on Chinese modified simplified MDRD formula(6)

eGFR =175×Scr^-1.234×age^-0.179×gender coefficient (1 for men, 0.79 for women)

Where Serum creatinine(Scr) and eGFR units are mg/dl, ml/min/1.73m².Scr unit conversion 1umol/L=88.4mg/dl.

2.3. Statistical analysis

Continuous variables are presented as the mean and standard deviation (SD). For the comparison of the continuous variables, the Student t-test. Categorical variables are presented as frequencies and percentages. For the comparison of categorical variables, the chi-squared test was performed. Correlation analysis was performed using Pearson correlation analysis.Univariate logistic regression models were used to evaluate the relationship between clinical, laboratory variables and the eGFR. A P value < 0.05 was considered statistically significant, and the odds ratios and 95% confidence intervals were calculated. All analyses were performed using SPSS software (Version 25.0).

3.1. Patient population

There were 7879 cases with a mean age of 69.91±7.36 years; among them, there were 4008 cases in the FLI≥30 group, and the probability of eGFR<90mL/(min-1.73m2) was 66.37%, a figure that was higher than that of the FLI<30 group(Table 1).The clinical laboratory characteristics for people in Table 2.BMI, WC,SBP, DBP, STP, Alb,Glo, TB, CB, UCB, ALT, AST, γ-GGT, FPG, Scr, UA, TC,TG, and HDL-C were higher in the FLI≥30 group than in the FLI<30 group, and eGFR in the FLI≥30 group was lower than that of the FLI <30 group, and the differences were all statistically significant (all p<0.05). There were no significant differences in age, BUN, and LDL-C among the clinical indicators of the two groups(Table 2).

3.2. Relationship between variables

We compared the correlation of FLI with other variables. The results show that FLI was positively correlated with BMI, WC, SBP, DBP, STP, Alb, Glo, ALT,AST, γ-GGT,FPG, Scr, UA, TC, and TG, and negatively correlated with TB, CB, UCB, HDL-C, and eGFR (p<0.05). There was no significant correlation between FLI and age, and no significant correlation with BUN and LDL-C(Table 3).

3.3. Independent predictors of eGFR

Many clinical, laboratory variables predict abnormalities in eGFR by univariate logistic analysis, including fatty liver, diabetes, STP,G,BUN.TC,LDL-C(Table 4).These variables were entered into a multifactorial logistic analysis. In the multivariate logistic analysis, FLI was an independent predictor of eGFR abnormalities. FLI has a predictive effect on eGFR, with each unit increase in FLI increasing the probability of eGFR abnormality by 0.7%(Table 5).

The gold standard for the diagnosis of NAFLD is usually considered to be liver puncture biopsy, but the feasibility of implementation in large populations is low, so it is important to find an index for the evaluation of nonalcoholic fatty liver disease. Studies suggest that FLI has a high sensitivity and specificity for the evaluation of nonalcoholic fatty liver disease, and in our population, FLI also has a high sensitivity and specificity. It can be seen that this index of FLI is also applicable to our population to some extent. In this study, the population was divided into two groups according to FLI, which to some extent can distinguish whether the study subjects have non-alcoholic fatty liver disease status, and the results showed that the elevated FLI was significantly associated with an increased probability of abnormal glomerular filtration rate estimates, which is consistent with many international studies reported. With the westernization of the dietary structure of our population and the prevalence of a more sedentary lifestyle, nonalcoholic fatty liver disease has now replaced hepatitis B as the number one chronic liver disease in China and is often the primary cause of abnormal liver enzymes in health checks. A meta-analysis showed that NAFLD affects nearly a quarter of the world's population, with prevalence rates of 27.37% in Asia, 23.71% in Europe, and 24.13% in North America(7). Data also show that the prevalence of NAFLD in Asia continues to increase(8). NASH not only leads to cirrhosis, hepatocellular carcinoma, and liver failure through nonalcoholic steatohepatitis (NASH), but also significantly increases the incidence of type 2 diabetes, metabolic syndrome, and cardiovascular disease. Lin et al. also concluded(9) that cardiovascular and cerebrovascular disease topped the list of causes of death in patients with NAFLD (35.6%), while renal disease was not negligible (7.5%).

NAFLD and chronic kidney disease(CKD) share many common risk factors, and NAFLD and CKD often co-exist, which makes the correlation between them a cause for consideration. In recent years, more and more clinical studies have suggested that NAFLD may be an independent risk factor for the development of CKD. A number of domestic and international studies have shown (10, 11) that NAFLD is significantly associated with CKD in the past. Data from Korea revealed(10) that individuals with NAFLD combined with CKD had a significant decrease in annual GFR compared to individuals without NAFLD, and the mean difference in the percentage decrease in annual GFR between individuals with NAFLD and non-NAFLD individuals remained significant in multivariate adjusted models. Mantovani et al. also found(12) that NAFLD (especially in patients with advanced NAFLD) elevates the risk of CKD by approximately two-fifths in Asian populations. Data from the united network of organ sharing (UNOS) from 2002 to 2011 showed that NASH-related cirrhosis has become a common indication for combined liver and kidney transplantation(13). Allen et al. found that cirrhosis due to NAFLD was a potential risk factor for the development of CKD compared to other causes of cirrhosis(14). Three prospective studies(15-17) showed NAFLD as a risk factor for high prevalence of KD, including Targher G (17), who followed 1760 diabetic patients for 6.5 years and found that fatty liver was significantly associated with increased incidence of CKD after correcting for a large number of confounding factors. Another prospective study also showed that NAFLD was a risk factor for a high prevalence of CKD, and after correcting for a large number of confounding factors, fatty liver was found to be significantly associated with an increased incidence of CKD (18). Foreign studies (19) showed that NAFLD was associated with the incidence of CKD (HR=1.58, 95% CI:1.51∼1.66). It indicates that NAFLD is closely associated with CKD. In a study of 1412 adult Han Chinese, Li(20) found that NAFLD diagnosed by ultrasound, independently of blood glucose levels, was closely associated with impaired renal function and that the prevalence of mild renal impairment was significantly higher in patients with NAFLD. It has been shown that the prevalence of CKD in patients with NAFLD is 21-54% compared to 3.7%-24.2% in patients without NAFLD, and that the risk of CKD in NAFLD diagnosed by ultrasound is 1.5-2 times higher than in NAFLD without NAFLD after correction for metabolic syndrome components. Another Meta-analysis also showed that NAFLD was associated with an increased prevalence and risk of CKD, and both studies showed that the severity of NAFLD was positively associated with the prevalence of CKD(2, 21).

Understanding the complex and interrelated mechanisms between NAFLD and CKD is important because of the serious public health burden of these two diseases, and the common mechanism of liver and kidney injury may be a research target for the prevention and treatment of CKD. NAFLD and CKD are characterized by ectopic toxic lipid accumulation due to disorders of hepatic and renal lipid metabolism, and trigger lipid peroxidative stress, apoptosis, inflammation and fibrosis(22). However, the pathophysiological mechanisms underlying NAFLD and CKD are not well defined at present. a review by Targher G (23) et al. provides a more comprehensive summary of the possible underlying mechanisms: (a) increased visceral adiposity and inflammation (b) insulin resistance (c) fatty liver formation (d) in the presence of increased free fatty acid (FFA) in-flow and chronic inflammation, the liver can cause an amplification of the chronic inflammatory response leading to a systemic inflammatory response, while the liver will be the target of the systemic inflammatory response (e) cytokine imbalance may lead to the development of CKD and its related diseases through a variety of deleterious pleiotropic effects, such as activation of various pro-inflammatory pathways, upregulating adhesion molecules, inducing endothelial dysfunction and oxidative stress, and decreasing lipocalin expression, thus contributing to the pathogenesis of CKD and its related diseases. (f) Decreased concentrations of plasma lipocalin(an adipose-secreting cytokine with antidiabetic and anti-inflammatory effects)may be another potential mechanism linking NAFLD and CKD.

As mentioned earlier, many studies have confirmed that NAFLD is an independent risk factor for CKD, but early CKD is also associated with high morbidity and mortality, and earlier detection of abnormal glomerular filtration rate (eGFR) would be of great significance. Machado et al (24) found in their study that patients with NAFLD diagnosed by liver biopsy were more likely to have low eGFR levels. Although many studies have confirmed that NAFLD increases the incidence and prevalence of CKD, whether NAFLD has an effect on eGFR in people with eGFR >60 mL/(min-1.73m2) has yet to be investigated, and there are few studies in this area. Therefore, the purpose of this study is to investigate the effect of NAFLD on early eGFR by studying the correlation between FLI and eGFR in the general medical examination population. It is hoped that we can intervene the related risk factors in the pre-CKD stage to reduce the occurrence of CKD and provide research targets for the prevention and treatment of CKD. At the same time, due to the asymptomatic nature of NAFLD and the lack of specific treatment methods, people do not know enough about NAFLD and do not pay enough attention to it. It is hoped that this study can enhance people's knowledge about NAFLD, and pay enough attention to NAFLD and intervene in it as early as possible.

Overall, this study found that eGFR decreases as FLI rises in an elderly population in the Yangzhou.

There are still some limitations of this paper. First, this study was only conducted by cross-sectional data analysis, and the causal relationship between NAFLD and CKD cannot be well described. Second, the gold standard for the diagnosis of NAFLD is usually considered to be liver puncture biopsy. Although FLI has a high sensitivity and specificity, it still has some limitations and cannot truly reflect whether the population has NAFLD.

As FLI rises eGFR begins to decrease in phase and FLI is an independent risk factor for decreased eGFR. This effect may be manifested before CKD has even occurred. The significance of the results of this study is to help us recognize that patients with NAFLD are at risk for early eGFR reduction, and that intervention in NAFLD before the onset of CKD may reduce the occurrence and progression of CKD in patients with NAFLD and provide possible research targets for the prevention and treatment of CKD, as well as to draw attention to NAFLD and to actively Early interventions should be carried out.

Ethics approval and consent to participate

Ethical approval was obtained from the research ethics committee of the Affiliated Hospital of Yangzhou University.Patients provided written informed consent(2022-YKL5-18-003). This study was performed in accordance with the Declaration of Helsinki.

Consent to publish

The author consented to publication in the journal.

Availability of data and materials

The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.

Competing interests

Nothing to report.

Funding

This study was supported by the Jiangsu Provincial Geriatric Health Research Project (LK2021054) and Yangzhou Science and Technology Development Plan Project(YZ2020073).

Acknowledgement

First and foremost, I would like to show my deepest gratitude to my supervisor, Dr.Qing Shan, a respectable, responsible and resourceful scholar,who has provided me with valuable guidance in every stage of the writing of this thesis. Without his enlightening instruction, impressive kindness and patience, I could not have completed my thesis. His keen and vigorous academic observation enlightens me not only in this thesis but also in my future study.

I would also like to thank all my teachers who have helped me to develop the fundamental and essential academic competence. Last but not least, I' d like to thank all my friends, especially my two lovely roommates, for their encouragement and support.

Authors Contribution

Jiacheng Yong contributed to the conception of the study and performed the data analyses and wrote the manuscript. All authors helped perform the analysis with constructive discussions.

Fan JG, Farrell GC. Epidemiology of non-alcoholic fatty liver disease in China. Journal of Hepatology. 2009;50(1):204-10. doi: 10.1016/j.jhep.2008.10.010. PubMed PMID: WOS:000261902900025.
Armstrong MJ, Adams LA, Canbay A, Syn WK. Extrahepatic Complications of Nonalcoholic Fatty Liver Disease. Hepatology. 2014;59(3):1174-97. doi: 10.1002/hep.26717. PubMed PMID: WOS:000331787500044.
Ong JP, Pitts A, Younossi ZM. Increased overall mortality and liver-related mortality in non-alcoholic fatty liver disease. Journal of Hepatology. 2008;49(4):608-12. doi: 10.1016/j.jhep.2008.06.018. PubMed PMID: WOS:000259953600018.
Bedogni G, Bellentani S, Miglioli L, Masutti F, Passalacqua M, Castiglione A, et al. The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. Bmc Gastroenterology. 2006;6. doi: 10.1186/1471-230x-6-33. PubMed PMID: WOS:000242017200001.
Huang XL, Xu M, Chen Y, Peng K, Huang Y, Wang P, et al. Validation of the Fatty Liver Index for Nonalcoholic Fatty Liver Disease in Middle-Aged and Elderly Chinese. Medicine. 2015;94(40). doi: 10.1097/md.0000000000001682. PubMed PMID: WOS:000369412500001.
Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, et al. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. Journal of the American Society of Nephrology. 2006;17(10):2937-44. doi: 10.1681/asn.2006040368. PubMed PMID: WOS:000240926500034.
Younossi ZM, Koenig AB, Abdelatif D, Fazel Y, Henry L, Wymer M. Global Epidemiology of Nonalcoholic Fatty Liver Disease-Meta-Analytic Assessment of Prevalence, Incidence, and Outcomes. Hepatology. 2016;64(1):73-84. doi: 10.1002/hep.28431. PubMed PMID: WOS:000379233400013.
Li J, Zou BY, Yeo YH, Feng YM, Xie XY, Lee DH, et al. Prevalence, incidence, and outcome of non-alcoholic fatty liver disease in Asia, 1999-2019: a systematic review and meta-analysis. Lancet Gastroenterology & Hepatology. 2019;4(5):389-98. doi: 10.1016/s2468-1253(19)30039-1. PubMed PMID: WOS:000463786300024.
Lin YS, Gong XR, Li X, Shao CX, Wu TF, Li MR, et al. Distinct Cause of Death Profiles of Hospitalized Non-alcoholic Fatty Liver Disease: A 10 Years' Cross-Sectional Multicenter Study in China. Frontiers in Medicine. 2021;7. doi: 10.3389/fmed.2020.584396. PubMed PMID: WOS:000611391200001.
Jang HR, Kang D, Sinn DH, Gu S, Cho SJ, Lee JE, et al. Nonalcoholic fatty liver disease accelerates kidney function decline in patients with chronic kidney disease: a cohort study. Scientific Reports. 2018;8. doi: 10.1038/s41598-018-23014-0. PubMed PMID: WOS:000427588300019.
Zhang M, Lin S, Wang MF, Huang JF, Liu SY, Wu SM, et al. Association between NAFLD and risk of prevalent chronic kidney disease: why there is a difference between east and west? Bmc Gastroenterology. 2020;20(1). doi: 10.1186/s12876-020-01278-z. PubMed PMID: WOS:000534039000006.
Mantovani A, Zaza G, Byrne CD, Lonardo A, Zoppini G, Bonora E, et al. Nonalcoholic fatty liver disease increases risk of incident chronic kidney disease: A systematic review and meta-analysis. Metabolism-Clinical and Experimental. 2018;79:64-76. doi: 10.1016/j.metabol.2017.11.003. PubMed PMID: WOS:000426024100007.
Singal AK, Salameh H, Kuo YF, Wiesner RH. Evolving Frequency and Outcomes of Simultaneous Liver Kidney Transplants Based on Liver Disease Etiology. Transplantation. 2014;98(2):216-21. doi: 10.1097/tp.0000000000000048. PubMed PMID: WOS:000339262000019.
Allen AM, Kim WR, Therneau TM, Larson JJ, Heimbach JK, Rule AD. Chronic kidney disease and associated mortality after liver transplantation - A time-dependent analysis using measured glomerular filtration rate. Journal of Hepatology. 2014;61(2):286-92. doi: 10.1016/j.jhep.2014.03.034. PubMed PMID: WOS:000339775700017.
Chang Y, Ryu S, Sung E, Woo HY, Oh E, Cha K, et al. Nonalcoholic fatty liver disease predicts chronic kidney disease in nonhypertensive and nondiabetic Korean men. Metabolism-Clinical and Experimental. 2008;57(4):569-76. doi: 10.1016/j.metabol.2007.11.022. PubMed PMID: WOS:000254099900021.
Ryu S, Chang Y, Kim DI, Kim WS, Suh BS. gamma-Glutamltransferase rase as a predictor of chronic kidney disease in nonhypertensive and nondiabetic Korean men. Clinical Chemistry. 2007;53(1):71-7. doi: 10.1373/clinchem.2006.078980. PubMed PMID: WOS:000243233200011.
Targher G, Bertolini L, Rodella S, Zoppini G, Lippi G, Day C, et al. Non-alcoholic fatty liver disease is independently associated with an increased prevalence of chronic kidney disease and proliferative/laser-treated retinopathy in type 2 diabetic patients. Diabetologia. 2008;51(3):444-50. doi: 10.1007/s00125-007-0897-4. PubMed PMID: WOS:000252888200010.
Navaneethan S, Thomas G, Kashyap S, Srinivas T, Sehgal A, Kirwan JP. Metabolic Syndrome and Kidney Disease: A Systematic Review and Meta-Analysis. Obesity. 2011;19:S121-S2. PubMed PMID: WOS:000296603100339.
Kaps L, Labenz C, Galle PR, Weinmann-Menke J, Kostev K, Schattenberg JM. Non-alcoholic fatty liver disease increases the risk of incident chronic kidney disease. United European Gastroenterology Journal. 2020;8(8):942-8. doi: 10.1177/2050640620944098. PubMed PMID: WOS:000551992800001.
Li GL, Shi W, Hu H, Chen YQ, Liu L, Yin DZ. Nonalcoholic fatty liver disease associated with impairment of kidney function in nondiabetes population. Biochemia Medica. 2012;22(1):92-9. PubMed PMID: WOS:000300597200010.
Musso G, Gambino R, Tabibian JH, Ekstedt M, Kechagias S, Hamaguchi M, et al. Association of Non-alcoholic Fatty Liver Disease with Chronic Kidney Disease: A Systematic Review and Meta-analysis. Plos Medicine. 2014;11(7). doi: 10.1371/journal.pmed.1001680. PubMed PMID: WOS:000340617400010.
Musso G, Cassader M, Cohney S, De Michieli F, Pinach S, Saba F, et al. Fatty Liver and Chronic Kidney Disease: Novel Mechanistic Insights and Therapeutic Opportunities. Diabetes Care. 2016;39(10):1830-45. doi: 10.2337/dc15-1182. PubMed PMID: WOS:000383709000041.
Targher G, Chonchol M, Zoppini G, Abaterusso C, Bonora E. Risk of chronic kidney disease in patients with non-alcoholic fatty liver disease: Is there a link? Journal of Hepatology. 2011;54(5):1020-9. doi: 10.1016/j.jhep.2010.11.007. PubMed PMID: WOS:000290012400027.
Machado MV, Goncalves S, Carepa F, Coutinho J, Costa A, Cortez-Pinto H. Impaired renal function in morbid obese patients with nonalcoholic fatty liver disease. Liver International. 2012;32(2):241-8. doi: 10.1111/j.1478-3231.2011.02623.x. PubMed PMID: WOS:000298919500009.

Table 1 The baseline characteristics of people with FLI<30 and FLI≥30.

Variable	Cohort	FLI<30	FLI≥30	P value
	n=7879	n=3871	n=4008
General situation
Age(years)(mean±SD)	69.91±7.36	70.45±7.61	69.40±7.08	<0.01
Male	6802（86.33%）	3218（83.13%）	3584（89.42%）	<0.01
BMI(kg/m²)	24.49±2.91	22.61±2.18	26.30±2.32	<0.01
WC(cm)	87.13±8.65	81.39±6.45	92.66±6.66	<0.01
SBP(mmHg)	134.18±17.23	131.41±17.24	136.85±16.79	<0.01
DBP(mmHg)	82.30±9.72	80.61±9.67	83.94±9.49	<0.01
FLI	34.71±22.69	15.61±7.77	53.16±16.17	<0.01
eGFR[mL/(min·1.73m²）]	84.71±19.21	85.72±18.96	83.74±19.41	<0.01
eGFR<90mL/（min·1.73m²）	5068(64.32%)	2408(62.21%)	2660(66.37%)	<0.01
Smoking	1613(20.47%)	724(18.70%)	889(22.18%)	<0.01
Drinking	1431(18.16%)	557(14.39%)	874(21.81%)	<0.01
Basic disease
Fatty Liver	2189(27.78%)	326（8.42%）	1863（46.48%）	<0.01
Hypertension	3648(44.02%)	1388(35.86%)	2260(56.39%)	<0.01
Diabetes	1089(13.82%)	468(12.09%)	621(15.49%)	<0.01

Table 2 The laboratory indicators of people with FLI<30 and FLI≥30.

Variable	Cohort	FLI<30	FLI≥30	P value
	n=7879	n=3871	n=4008
Laboratory indicators
STP(g/L)	72.86±4.18	72.01±4.00	73.68±4.18	<0.01
Alb(g/L)	42.11±2.04	41.83±2.03	42.39±2.01	<0.01
Glo(g/L)	30.75±3.70	30.18±3.61	31.30±3.70	<0.01
TB(umol/L)	16.67±5.72	17.10±5.78	16.26±5.62	<0.01
CB(umol/L)	4.57±1.55	4.83±1.53	4.32±1.52	<0.01
UCB(umol/L)	12.10±4.59	12.26±4.60	11.94±4.57	<0.01
ALT(U/L)	21.76±13.03	18.08±9.90	25.31±14.60	<0.01
AST(U/L)	22.05±7.22	21.14±6.07	22.93±8.08	<0.01
γ--GGT(U/L)	27.80±17.75	20.31±10.03	35.03±20.39	<0.01
FPG(mmol/L)	6.15±1.70	5.85±1.46	6.43±1.86	<0.01
BUN(mmol/L)	5.70±1.64	5.70±1.64	5.71±1.65	0.812
Scr(umol/L)	88.21±28.65	86.56±27.44	89.81±29.68	<0.01
UA(umol/L)	360.11±83.38	338.67±76.68	380.83±84.36	<0.01
TC(mmol/L)	4.80±0.96	4.74±0.94	4.87±0.97	<0.01
TG(mmol/L)	1.67±1.09	1.15±0.49	2.15±1.28	<0.01
HDL-C(mmol/L)	1.23±0.29	1.34±0.30	1.13±0.23	<0.01
LDL-C(mmol/L)	2.72±0.80	2.72±0.78	2.72±0.82	0.811

BMI=body mass index;WC= waist circumference; SPB=systolic blood pressure;DBP= diastolic blood pressure STP=Serum total protein;Alb= Albumin; Glo=Globulin;TB =total bilirubin;CB= Conjugated bilirubin;UCB= Unconjugated bilirubin;ALT= alanine aminotransferase;AST=aspartate aminotransferase; γ-GGT= gamma-glutamyl transpeptidase;FPG=fasting plasma glucose; BUN=blood urea nitrogen;Scr= Serum creatinine;UA=uric acid; TC=total cholesterol; TG=triglyceride;LDL-C=low density lipoprotein cholesterol;HDL-C=high density lipoprotein cholesterol; eGFR= estimated glomerular filtration rate.

Table 3 Correlation of FLI with various clinical indicators.

Variable	FLI
Variable	r	P value
Age(years)	-0.090	<0.01
BMI(kg/m²)	0.773	<0.01
WC(cm)	0.789	<0.01
SBP(mmHg)	0.177	<0.01
DBP(mmHg)	0.200	<0.01
STP(g/L)	0.246	<0.01
Alb(g/L)	0.165	<0.01
Glo(g/L)	0.187	<0.01
TB(umol/L)	-0.082	<0.01
CB(umol/L)	-0.190	<0.01
UCB(umol/L)	-0.038	<0.01
ALT(U/L)	0.357	<0.01
AST(U/L)	0.176	<0.01
γ--GGT(U/L)	0.526	<0.01
FPG(mmol/L)	0.225	<0.01
BUN(mmol/L)	0.013	0.254
Scr(umol/L)	0.073	<0.01
UA(umol/L)	0.299	<0.01
TC(mmol/L)	0.089	<0.01
TG(mmol/L)	0.598	<0.01
HDL-C(mmol/L)	-0.437	<0.01
LDL-C(mmol/L)	-0.018	0.116
eGFR[mL/(min·1.73m²）]	-0.071	<0.01

Table 4 Predictors of eGFR<90mL/（min·1.73m²） on univariate logistic analysis

Univariate analysis	OR(95%CI)	P value
Age	1.055(1.048,1.063)	＜0.001
BMI	1.001(0.976,1.026)	0.945
WC	1.004(0.996,1.013)	0.314
Smoking	0.982(0.876,1.102)	0.795
Drinking	1.040(0.923,1.171)	0.523
Fatty Liver	1.217(1.079,1.373)	0.001
Hypertension	0.778(0.707,0.856)	＜0.001
Diabetes	1.356(1.189,1.546)	＜0.001
STP	1.015(1.004,1.027)	0.009
Alb	0.925(0.903,0.947)	＜0.001
Glo	1.045(0.031,0.058)	＜0.001
TB	0.955 (0.927,0.984)	0.967
CB	0.945(0.918,0.974)	0.003
UCB	1.005(0.995,1.015)	0.352
ALT	0.989(0.985,0993)	＜0.001
AST	0.997(0.990,1.003)	0.312
γ--GGT	0.997(0.994,1.000)	0.089
FPG	0.897(0.872,0.922)	＜0.001
BUN	1.399(1.349,1.451)	＜0.001
Scr	1.365(1.344,1.386)	＜0.001
UA	1.009(1.008,1.009)	＜0.001
TC	1.195(1.138,1.255)	＜0.001
TG	1.026(0.972,1.084)	0.348
HDL-C	0.930(0.778,1.112)	0.428
LDL-C	1.215(1.145,1.287)	＜0.001

Table 5 Predictors of eGFR<90mL/（min·1.73m²） on multivariate logistic analysis

Multivariate analysis	OR(95%CI)	P value
FLI	1.007(1.005,1.010)	＜0.001
Age	1.052(1.044,1.059)	＜0.001
Fatty Liver	1.139(1.004,1.292)	0.044
Diabetes	1.678(1.456,1.934)	＜0.001
STP	0.958(0.934,0.982)	0.001
Glo	1.069(1.039,1.100)	＜0.001
BUN	1.402(1.349,1.456)	＜0.001
TC	1.178(1.059,1.310)	0.003
LDL-C	1.052(0.928,1.193)	0.428

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Correlation between fatty liver index and estimated glomerular filtration rate in an elderly population in Yangzhou, China

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