Literature DB >> 30205810

The fatty liver index (FLI) and incident hypertension: a longitudinal study among Chinese population.

Kena Zhou1,2, Jie Cen3,4.   

Abstract

BACKGROUND: Hypertension and nonalcoholic fatty liver both have been considered as the serious public health problems in recent years. However, the longitudinal association between hypertension and nonalcoholic fatty liver remains unclear in Chinese population.
METHODS: This study was aimed to investigate the longitudinal association between nonalcoholic fatty liver assessed by fatty liver index and the incident hypertension among Chinese population and to evaluate the ability of FLI index, through comparing with the predictive value of other indexes.
RESULTS: Four thousand six hundred eighty-six subjects (3177 males and 1509 females) were involved and followed up for 9 years. The subjects were divided into groups according to the fatty liver index. Univariate and multivariate Cox regression models were used to analyze the risk factors of hypertension. After 9 years of follow-up, 2047 subjects developed hypertension. The overall 9-year cumulative incidence of HTN was 43.7%, ranging from 36.0% (FLI <  30) to 75.3% (FLI ≥ 60) (P for trend < 0.001). Cox regression analyses indicated that nonalcoholic fatty liver assessed by fatty liver index was independently and positively associated with the risk of incident hypertension. In receiver operating characteristic (ROC) curve analysis, the ROC curve (AUC) of FLI was 0.701 (95% CI 0.686-0.716), which was larger than that of its components.
CONCLUSION: The nonalcoholic fatty liver assessed by FLI independently predicted the incident hypertension among the Chinese population.

Entities:  

Keywords:  Epidemiology; Fatty liver index; Hypertension; Nonalcoholic fatty liver

Mesh:

Substances:

Year:  2018        PMID: 30205810      PMCID: PMC6134515          DOI: 10.1186/s12944-018-0858-6

Source DB:  PubMed          Journal:  Lipids Health Dis        ISSN: 1476-511X            Impact factor:   3.876


Background

Hypertension (HTN), which is suggested to be associated with many diseases, including diabetes, hyperuricemia, and cardiovascular events [1-4], has been the leading cause of death worldwide. However, there is no accepted index that could predict the incident hypertension nowadays. Nonalcoholic fatty liver disease (NAFLD), a spectrum of hepatic pathologies ranging from simple steatosis to nonalcoholic steatohepatitis and cirrhosis, has also become a serious global public health problem in recent decades [5]. In the general Japanese population, the prevalence of NAFLD ranges from 24.6 to 29.7% [6, 7]. Moreover, it is estimated that the overall prevalence of NAFLD in mainland of China is about 20.09% (17.95–22.31%) [8]. Recently, the fatty liver index (FLI), as the predictor for the insulin resistance, has been associated with the fatty liver diseases [9]. Using this simple index, the fatty liver disease could be detected with considerable accuracy. In addition, NAFLD has also closely related to HTN in a cross-sectional study [10]. However, it is still unclear whether the FLI can predict the incident HTN in the Chinese population. Therefore, we performed a longitudinal population-based study in order to investigate the association between the FLI and incident HTN among Chinese population and to evaluate the ability of FLI index, through comparing with the predictive value of body mass index (BMI), waist circumference (WC), triglyceride (TG) and γ-glutamyltransferase (GGT).

Methods

Study subjects and design

Our population-based cohort study was conducted in the annual physical health examinations beginning from 2006 to 2015 in Zhenhai Lianhua Hospital in the city of Ningbo, China, to assess the longitudinal relationship between fatty liver index and the incident hypertension. Certain participants were excluded at study entry: (I) Individuals who had a history of HTN or overt cardiovascular diseases. (II) Individuals who were taking medicines that may affect the blood pressure. (III) Individuals who were drinking alcohol greater than 140 g per week for males and 70 g per week for females. Finally, 4686 subjects (3177 males and 1509 females) who had no HTN at baseline were evaluated for the development of HTN.

Measurements

A questionnaire for the initial health examinations in 2006 included subjects’ demographic characteristics, smoking status, alcohol consumption and medical history, and the data were obtained in the health check-up center of Zhenhai Lianhua Hospital under the senior physicians who were well-trained. Standing height and body weight were measured without shoes or outer clothing for each subject. BMI was calculated as weight in kilograms divided by height in meters squared. WC was measured around the smallest circumference with the measuring tape positioned between the ribs and iliac crest [11]. Sitting blood pressure was measured from the right arm three times with a 1-min interval between the measurements after the rest for 20 min, using an automated device (Omron HEM-7052; Omron Corp., Kyoto, Japan). The mean of three measurements was calculated for analysis. Venous blood samples were obtained from the subjects in the morning after at least 12 h prior to the examination. Blood urea nitrogen (BUN), creatinine (Cr), TG, total cholesterol (TC), high density lipoprotein cholesterol (HDL-C), low density lipoprotein (LDL-C), serum uric acid (SUA), fasting plasma glucose (FPG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), GGT, Apo-A1and Apo-B were estimated using an Olympus AU640 auto-analyzer (Olympus, Kobe, Japan). All the laboratories involved resoundingly completed the standardization.

Definitions

HTN was defined as systolic blood pressure (SBP) ≥ 140 mmHg, diastolic blood pressure (DBP) ≥ 90 mmHg or current drug use for HTN, in accordance with the criteria of the WHO [12]. FLI was calculated for fatty liver according to the previous studies [9, 13]: FLI = (e[0.953 × ln(TG) + 0.139 × BMI + 0.718 × ln(GGT) + 0.053 × WC - 15.745]/ (1 + e[0.953 × ln(TG) + 0.139 × BMI + 0.718 × ln(GGT) + 0.053 × WC - 15.745]) × 100, with triglycerides measured in mg/dl (1 mg/dl = 0.01129 mmol /l), GGT in U/l, and WC in cm. The FLI score range is 0–100. And the subjects who had three or more of the following abnormalities were diagnosed as Metabolic syndrome (MS): (I) raised blood pressure, systolic blood pressure (SBP) ≥ 130 mmHg or diastolic blood pressure (DBP) ≥ 85 mmHg, or treatment of previously diagnosed hypertension; (II) raised FPG, defined as FPG ≥ 6.1 mmol/L, or previously diagnosed diabetes; (III) raised triglyceride level, defined as triglycerides ≥1.7 mmol/L; (IV) reduced HDL-C, defined as HDL-C < 1.0 mmol/L; (V) WC ≥ 90 cm for Chinese men and ≥ 85 cm for Chinese women [14]. The estimated glomerular filtration rate (eGFR) was calculated using the improved Chinese population MDRD formula [15].

Statistical analysis

The fundamental characteristics of the samples were summarized by descriptive statistics. Continuous variables were expressed as median (IQR) and categorical variables were presented as percentages (%). Continuous variables were compared using the student’s t text, Mann-Whitney U test, Kruskal-Wallis H test or one way ANOVA depending on the normality of the data. Categorical variables between groups were compared using Chi-square text. For a statistical inference, all p values are bilateral, and a p value of less than 0.05 was considered statistically significant. All statistical analyses were performed using SPSS software (version 17.0, SPSS software, Chicago, IL, USA). The study subjects were classified into three groups according to FLI at baseline: FLI <  30 was defined as not having NAFLD, 30 ≤ FLI < 60 was defined as having intermediate FLI, and FLI ≥ 60 was defined as having NAFLD. The baseline characteristics of the subjects in each group were compared. The cumulative incidence of HTN was calculated by dividing the number of cases by the numbers of subjects followed up for each FLI group. Cox proportional hazards regression models were used to analyze the risk of incident HTN for each baseline FLI.

Results

Baseline characteristics

In the study, a total of 4686 subjects (3177 males and 1509 females) were evaluated at baseline. The baseline demographic and clinical characteristics of the subjects are showed in Table 1. As the FLI increased, it tended to be males and obese. In addition, SBP, DBP, FPG, UA, AST, ALT, y-GGT, TC, TG, LDL-C and Apo-B all tended to increase at higher FLI (p <  0.001), whereas Apo-A1 was significantly lower in subjects with higher FLI categories (P <  0.001).
Table 1

Baseline characteristics of the subjects according to FLI categories

VariablesFLI categories
All subjects (n = 4686)<  30 (n = 3479)30–59 (n = 903)≥ 60 (n = 304) P
Gender (male/%)3177/67.82087/60.0801/88.7289/95.1<  0.001
Age (years)40.0 (34.0–50.0)39.0 (33.0–50.0)44.0 (36.0–53.0)41.0 (34.0–51.0)<  0.001
BMI (kg/m2)22.5 (20.5–24.5)21.6 (20.0–23.2)25.0 (23.9–26.3)26.7 (24.9–28.2)<  0.001
SBP (mmHg)118.0 (109.0–126.0)115.0 (107.0–124.0)122.0 (116.0–129.0)125.0 (118.3–131.0)<  0.001
DBP (mmHg)75.0 (69.0–80.0)73.0 (68.0–79.0)79.0 (74.0–83.0)80.0 (75.0–84.0)<  0.001
WC (cm)78.0 (71.0–84.0)74.0 (69.0–79.0)86.0 (83.0–90.0)91.0 (87.0–95.0)<  0.001
FLI12.8 (4.93–30.7)7.85 (3.77–16.01)41.6 (34.7–50.0)70.4 (64.7–80.6)<  0.001
BUN (μmol/L)4.97 (4.21–5.78)4.93 (4.18–5.74)5.07 (4.28–5.97)4.99 (4.28–5.77)0.021
Cr (μmol/L)72.0 (61.0–81.0)70.0 (59.0–80.0)78.0 (72.0–85.0)77.0 (70.0–85.0)<  0.001
FPG (mmol/L)4.43 (4.14–4.77)4.41 (4.13–4.72)4.45 (4.15–4.85)4.57 (4.19–5.02)<  0.001
UA (μmol/L)323.0 (263.0–378.0)303.0 (248.0–357.0)373.0 (335.0–419.5)394.0 (351.0–444.0)<  0.001
AST (U/L)19.0 (17.0–24.0)19.0 (16.0–22.0)23.0 (19.0–27.0)26.0 (21.0–35.0)<  0.001
ALT (U/L)22.0 (16.0–33.0)19.0 (15.0–27.0)35.0 (25.0–48.0)48.0 (33.0–74.0)<  0.001
y-GGT (U/L)18.0 (13.0–28.0)15.0 (11.0–21.0)32.0 (23.0–47.0)60.0 (37.0–97.0)<  0.001
TC (mmol/L)4.68 (4.10–5.31)4.57 (4.00–5.15)4.88 (4.36–5.55)5.24 (4.70–5.86)<  0.001
TG (mmol/L)1.20 (0.87–1.74)1.04 (0.80–1.37)1.87 (1.43–2.41)2.63 (1.99–3.80)<  0.001
HDL-C (mmol/L)1.27 (1.07–1.55)1.30 (1.09–1.61)1.16 (1.02–1.36)1.20 (1.07–1.36)<  0.001
LDL-C (mmol/L)2.60 (2.13–3.13)2.51 (2.05–3.03)2.89 (2.40–3.39)3.00 (246–3.55)<  0.001
Apo-A1 (g/L)1.30 (1.13–1.49)1.33 (1.16–1.51)1.21 (1.06–1.37)1.20 (1.07–1.35)<  0.001
Apo-B (g/L)0.90 (0.75–1.07)0.85 (0.71–1.01)1.01 (0.86–1.18)1.10 (0.94–1.24)<  0.001
eGFR (mL/(min·1.73 m2))109.9 (97.9–124.4)111.5 (99.4–126.2)105.5 (94.3–118.4)105.5 (94.8–120.5)<  0.001
Baseline characteristics of the subjects according to FLI categories

Relationship between FLI and incident HTN

Our prospective study was conducted to investigate the predictive value of FLI for incident HTN. After 9-year follow-up, 2047 (43.68%) subjects including 1541 males and 506 females developed HTN, corresponding to 48.5% and 33.5% cumulative incidence of HTN in male and female, respectively. Also, we observed that baseline FLI predicted the incidence of HTN in a positive and dose-responsive manner (Fig. 1). The overall 9-year cumulative incidence of HTN was 43.7%, ranging from 36.0% (FLI <  30) to 75.3% (FLI ≥ 60) (P for trend < 0.001; Fig. 1). This tendency also held true for 1- to 9-year cumulative incidences. These findings indicate that those with higher FLI groups were more likely to develop HTN. In addition, the subjects with incident HTN were predominantly male, and the baseline Age, BMI, SBP, DBP, WC, FLI, BUN, Cr, FPG, UA, AST, ALT, y-GGT, TC, TG, LDL-C, HDL-C, Apo-B and eGFR were significantly different between two groups (Table 2).
Fig. 1

The association between baseline FLI categories and the cumulative incidence of hypertension

Table 2

Baseline characteristics of the subjects according to follow-up outcomes

VariablesSubjects developed HTN (n = 2047)Subjects did not develop HTN (n = 2639) P
Gender (male/female, n)1541/5061636/1003<  0.001
Age (years)44.0(36.0–54.0)38.0(33.0–46.0)<  0.001
BMI (kg/m2)23.6(21.8–25.4)21.7(19.8–23.6)<  0.001
SBP (mmHg)124.0(117.0–131.0)112.0(105.0–120.0)<  0.001
DBP (mmHg)80.0(75.0–84.0)71.0(67.0–76.0)<  0.001
WC (cm)81.0(75.0–87.0)75.0(69.0–81.0)<  0.001
FLI22.0(9.2–41.6)8.03(3.63–19.96)<  0.001
BUN (μmol/L)5.09(4.29–5.96)4.86(4.15–5.66)<  0.001
Cr (μmol/L)74.0(64.0–83.0)71.0(60.0–80.0)<  0.001
FPG (mmol/L)4.53(4.21–4.89)4.37(4.09–4.66)<  0.001
UA (μmol/L)342.0(284.0–395.0)306.0(250.0–364.0)<  0.001
AST (U/L)20.0(17.0–25.0)19.0(16.0–23.0)<  0.001
ALT (U/L)25.0(17.0–37.0)20.0(15.0–30.0)<  0.001
y-GGT (U/L)21.0(15.0–34.0)16.0(11.0–24.0)<  0.001
TC (mmol/L)4.83(4.28–5.50)4.56(3.99–5.14)<  0.001
TG (mmol/L)1.38(1.01–2.02)1.07(0.80–1.51)<  0.001
HDL-C (mmol/L)1.26(1.07–1.52)1.27(1.08–1.58)0.020
LDL-C (mmol/L)2.73(2.24–3.29)2.51(2.04–3.03)<  0.001
Apo-A1 (g/L)1.29(1.13–1.50)1.30(1.13–1.48)0.815
Apo-B (g/L)0.97(0.81–1.14)0.85(0.71–1.01)<  0.001
eGFR (mL/(min·1.73 m2))108.0(95.0–122.0)111.6(100.2–126.2)<  0.001
The association between baseline FLI categories and the cumulative incidence of hypertension Baseline characteristics of the subjects according to follow-up outcomes

The FLI and the risk of incident HTN

In the study, we also analyzed the hazard ratio for incident HTN in each FLI group by univariate and multivariate Cox proportional hazard models (Tables 3 and 4). Compared to the lowest FLI group, the hazard ratios (95% CI) for subjects in 30 ≤ FLI < 60 and FLI ≥ 60 group were 2.17(1.97–2.40) and 3.00(2.61–3.46), respectively (P for trend < 0.001). The same relationship between FLI and incident HTN was also revealed even after adjusting for age and gender (Mode 1), or age, gender, SBP, and DBP (Mode 2), or age, gender, and indicators of MS (Mode 3) in Table 4. These findings indicated higher FLI was associated with an increased risk of the development of HTN.
Table 3

Univariate Cox Proportional Hazard models of development of HTN during 9-year follow-up

VariablesHR(95%CI)P value
Gender (male)1.61(1.46–1.78)<  0.001
Age (years)1.03(1.03–1.04)<  0.001
BMI (kg/m2)1.16(1.15–1.18)<  0.001
WC (cm)1.06(1.05–1.06)<  0.001
BUN (mmol/L)1.11(1.07–1.15)<  0.001
Cr (μmol/L)1.00(1.00–1.01)<  0.001
FPG (mmol/L)1.26(1.21–1.30)<  0.001
UA (μmol/L)1.00(1.00–1.00)<  0.001
AST (U/L)1.01(1.00–1.01)<  0.001
ALT (U/L)1.00(1.00–1.00)<  0.001
y-GGT (U/L)1.00(1.00–1.01)<  0.001
TC (mmol/L)1.28(1.22–1.34)<  0.001
TG (mmol/L)1.29(1.25–1.33)<  0.001
HDL-C (mmol/L)0.86(0.77–0.97)0.010
LDL-C (mmol/L)1.31(1.24–1.38)<  0.001
Apo-A1 (g/L)1.02(0.86–1.21)0.812
Apo-B (g/L)3.47(2.95–4.09)<  0.001
eGFR (mL/(min·1.73 m2))1.00(0.99–1.00)<  0.001
FLI categories<  0.001
<  301.00(reference)
30–592.17(1.97–2.40)
≥ 603.00(2.61–3.46)
Table 4.

Risk of development HTN according to baseline FLI categories in unadjusted and adjusted models

Models<  30 (n = 3479)30–59 (n = 903)≥ 60 (n = 304) P
Unadjusted1.00 (reference)2.17 (1.97–2.40)3.00 (2.61–3.46)<  0.001
Mode 1 (Adjusted for age and gender)1.00 (reference)1.78 (1.61–1.98)2.58 (2.23–2.98)<  0.001
Mode 2 (Adjusted for age, gender, SBP, and DBP)1.00 (reference)1.27 (1.14–1.41)1.62 (1.39–1.87)<  0.001
Mode 3 (Adjusted for age, gender and indictors of MSa)1.00 (reference)1.23 (1.10–1.38)1.51 (1.27–1.80)<  0.001

aIncluding WC, SBP, DBP, FPG, HDL-C, TG

Univariate Cox Proportional Hazard models of development of HTN during 9-year follow-up Risk of development HTN according to baseline FLI categories in unadjusted and adjusted models aIncluding WC, SBP, DBP, FPG, HDL-C, TG

ROC curve analysis

ROC curve analyses were preformed to assess the diagnostic value of FLI and its components. The area under the ROC (AUC) curve to analyze the ability of the baseline FLI to predict the development of HTN was 0.701 (95% CI 0.686–0.716), which was larger than that of BMI (0.684 (95% CI 0.669–0.699), P for difference <  0.01), WC (0.684 (95% CI 0.669–0.699), P for difference <  0.01), TG (0.645 (95% CI 0.629–0.661), P for difference <  0.01) and GGT (0.633 (95% CI 0.617–0.649) P for difference <  0.01) (Fig. 2).
Fig. 2

Receiver operative characteristic (ROC) curves and corresponding areas under the curve (AUC) for HTN. The AUC of FLI, TG, GGT, WC and BMI were 0.701 (95% CI 0.686–0.716), 0.645 (95% CI 0.629–0.661), 0.633 (95% CI 0.617–0.649), 0.684 (95% CI 0.669–0.699) and 0.684 (95% CI 0.669–0.699), respectively. p values for the difference between FLI and other two AUCs were <  0.01

Receiver operative characteristic (ROC) curves and corresponding areas under the curve (AUC) for HTN. The AUC of FLI, TG, GGT, WC and BMI were 0.701 (95% CI 0.686–0.716), 0.645 (95% CI 0.629–0.661), 0.633 (95% CI 0.617–0.649), 0.684 (95% CI 0.669–0.699) and 0.684 (95% CI 0.669–0.699), respectively. p values for the difference between FLI and other two AUCs were <  0.01

Discussion

In our population-based prospective study, it demonstrated that there was a positive, dose-response relationship between NAFLD assessed by FLI and the risk of incident HTN during a 9-year period among Chinese population. Also, we found that the FLI was an independent predictor for incident HTN. Univariate and multivariate regression analysis suggested that subjects with higher baseline FLI were significantly associated with a higher risk of incident HTN after the adjustment for confounders. Our study confirmed the findings of relevant cross-sectional studies, which observed an independent positive relationship between NAFLD and incident HTN [10, 16], and importantly provides evidence on causality for the relationship. The results also show that the FLI index may be an effective predictor for the incident HTN, through comparing with the components of the FLI. Currently, increasing studies [17-19] suggest that lipids and GGT level may be an independent predictor of incident HTN. However, in our ROC analysis, the AUC of the FLI index in diagnosing HTN was larger than that of BMI, WC, TG and GGT. These indicated that the FLI index was more effective for predicting the incident HTN, compared with the components of the FLI index. The following hypotheses about the mechanism by which NAFLD participates in the development of HTN may be possible. The first and foremost is the insulin resistance (IR). To the best of our knowledge, several studies have demonstrated that NAFLD is associated with insulin resistance [20, 21], which may increase the sympathetic nervous system activity, induce the strong vasoconstriction effect, make the vascular smooth muscle proliferation, increase the synthesis and release of endothelin, and finally lead to the elevation of blood pressure [22, 23]. The other explanation is related to the renin-angiotensin system. Wu Y, et al. [24] demonstrated that NAFLD has been associated with renin-angiotensin system in a recent study. And of course it was also the cause of incident HTN. In addition, previous epidemiological studies have shown that the FLI was the well-known predictor for the development of nonalcoholic fatty liver and diabetes [25, 26]. Our results indicated that the FLI predicted the subsequent occurrence of HTN in a positive and dose-dependent manner. Therefore, the early detection of the FLI may be beneficial for early interventions to prevent HTN later in life among Chinese population. The 9-year longitudinal population-based study and a large number of subjects were our major strengths. Also, the longitudinal study expanded the observation to establish the temporal sequence between NAFLD assessed by FLI and the later risk of HTN in Chinese population. Moreover, the selection bias was less likely to appear in the present study as annual health check-ups in state-owned companies are mandatory in China. Despite its strengths, the study had some limitations. First, our study did not include the ultrasounds or magnetic resonance spectroscopy. Second, fasting insulin was not obtained due to the lack of relevant devices. Third, dietary and lifestyle were not collected. Therefore, further studies should be required to clarify these above factors.

Conclusion

In conclusion, the results of the study showed that nonalcoholic fatty liver assessed by FLI independently predicted the incident HTN, and suggested that the FLI should be closely monitored and it may be beneficial for HTN prevention.
  25 in total

Review 1.  Metabolic syndrome and nonalcoholic fatty liver disease: Is insulin resistance the link?

Authors:  Mohamed Asrih; François R Jornayvaz
Journal:  Mol Cell Endocrinol       Date:  2015-02-24       Impact factor: 4.102

2.  Serum gamma-glutamyl transferase level is an independent predictor of incident hypertension in Korean adults.

Authors:  Nan Hee Kim; Jung Kwon Huh; Byung Jin Kim; Min Woong Kim; Bum Soo Kim; Jin Ho Kang
Journal:  Clin Exp Hypertens       Date:  2012-04-03       Impact factor: 1.749

Review 3.  Gamma-glutamyltransferase and risk of hypertension: a systematic review and dose-response meta-analysis of prospective evidence.

Authors:  Setor K Kunutsor; Tanefa A Apekey; Bernard M Y Cheung
Journal:  J Hypertens       Date:  2015-12       Impact factor: 4.844

4.  Blood pressure is associated with the presence and severity of nonalcoholic fatty liver disease across the spectrum of cardiometabolic risk.

Authors:  Ehimen C Aneni; Ebenezer T Oni; Seth S Martin; Michael J Blaha; Arthur S Agatston; Theodore Feldman; Emir Veledar; Raquel D Conçeicao; Jose A M Carvalho; Raul D Santos; Khurram Nasir
Journal:  J Hypertens       Date:  2015-06       Impact factor: 4.844

5.  Prevalence of nonalcoholic fatty liver disease in mainland of China: a meta-analysis of published studies.

Authors:  ZhanZhan Li; Jing Xue; Peng Chen; LiZhang Chen; ShiPeng Yan; LiYa Liu
Journal:  J Gastroenterol Hepatol       Date:  2014-01       Impact factor: 4.029

Review 6.  Hyperuricemia, urate deposition and the association with hypertension.

Authors:  G Mancia; G Grassi; C Borghi
Journal:  Curr Med Res Opin       Date:  2015       Impact factor: 2.580

7.  Lipid disorder and intrahepatic renin-angiotensin system activation synergistically contribute to non-alcoholic fatty liver disease.

Authors:  Yu Wu; Kun L Ma; Yang Zhang; Yi Wen; Gui H Wang; Ze B Hu; Liang Liu; Jian Lu; Pei P Chen; Xiong Z Ruan; Bi C Liu
Journal:  Liver Int       Date:  2016-05-03       Impact factor: 5.828

Review 8.  Insulin resistance vs. hyperinsulinemia in hypertension: insulin regulation of Ca2+ transport and Ca(2+)-regulation of insulin sensitivity.

Authors:  M B Zemel
Journal:  J Nutr       Date:  1995-06       Impact factor: 4.798

Review 9.  Non-alcoholic fatty liver disease (NAFLD) and its connection with insulin resistance, dyslipidemia, atherosclerosis and coronary heart disease.

Authors:  Melania Gaggini; Mariangela Morelli; Emma Buzzigoli; Ralph A DeFronzo; Elisabetta Bugianesi; Amalia Gastaldelli
Journal:  Nutrients       Date:  2013-05-10       Impact factor: 5.717

10.  Fatty liver index as a simple predictor of incident diabetes from the KoGES-ARIRANG study.

Authors:  Dhananjay Yadav; Eunhee Choi; Song Vogue Ahn; Sang Baek Koh; Ki-Chul Sung; Jang-Young Kim; Ji Hye Huh
Journal:  Medicine (Baltimore)       Date:  2016-08       Impact factor: 1.889

View more
  8 in total

1.  Retraction Note: The fatty liver index (FLI) and incident hypertension: a longitudinal study among Chinese population.

Authors:  Kena Zhou; Jie Cen
Journal:  Lipids Health Dis       Date:  2020-05-25       Impact factor: 3.876

2.  Fatty liver index for hyperuricemia diagnosis: a community-based cohort study.

Authors:  Jianchang Qu; Jingtao Dou; Anping Wang; Yingshu Liu; Lu Lin; Kang Chen; Li Zang; Yiming Mu
Journal:  BMC Endocr Disord       Date:  2022-04-30       Impact factor: 3.263

3.  Effects of different exercise modalities on novel hepatic steatosis indices in overweight women with type 2 diabetes.

Authors:  Ebrahim Banitalebi; Mohammad Faramarzi; Samira Nasiri; Majid Mardaniyan; Vahid Rabiee
Journal:  Clin Mol Hepatol       Date:  2019-05-30

4.  Nonalcoholic fatty liver disease and risk of incident hypertension: a systematic review and meta-analysis.

Authors:  Stefano Ciardullo; Guido Grassi; Giuseppe Mancia; Gianluca Perseghin
Journal:  Eur J Gastroenterol Hepatol       Date:  2022-04-01       Impact factor: 2.566

Review 5.  Bidirectional Association between Hypertension and NAFLD: A Systematic Review and Meta-Analysis of Observational Studies.

Authors:  Gerui Li; Yuanyuan Peng; Ze Chen; Hang Li; Danli Liu; Xujun Ye
Journal:  Int J Endocrinol       Date:  2022-03-24       Impact factor: 3.257

6.  Fatty Liver Index is a valid predictor of non-alcoholic fatty liver disease (NAFLD) in pregnancy.

Authors:  Iresha Sandamali Koralegedara; Janith Niwanthaka Warnasekara; Ashani Rathnayake; Korale Gedara Dayaratne; Suneth Buddhika Agampodi
Journal:  BMJ Open Gastroenterol       Date:  2022-06

Review 7.  Abnormal metabolic processes involved in the pathogenesis of non-alcoholic fatty liver disease (Review).

Authors:  Mingmei Shao; Zixiang Ye; Yanhong Qin; Tao Wu
Journal:  Exp Ther Med       Date:  2020-08-28       Impact factor: 2.447

8.  The association between hypertension and nonalcoholic fatty liver disease (NAFLD): literature evidence and systems biology analysis.

Authors:  Chongyang Ma; Kai Yan; Zisong Wang; Qiuyun Zhang; Lianyin Gao; Tian Xu; Jiayang Sai; Fafeng Cheng; Yuqiong Du
Journal:  Bioengineered       Date:  2021-12       Impact factor: 3.269

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.