Predictive Value of Lipid Accumulation Product,Fatty Liver Index,Visceral Adiposity Index for Metabolic Syndrome According to Menopausal Status

Abstract

Background:

The aim of this study is to investigate the value of clinical indicators of metabolic syndrome according to menopausal status in healthy Korean women.

Methods:

The study included 3936 female patients who were managed at Pusan National University Hospital Health Promotion Center from 2008 to 2014. Each patient completed self-report questionnaires and underwent personal interviews with a healthcare provider to assess their past medical history such as any previous disease, medication and/or menstrual histories along with the measurement of her current body size. Lipid accumulation product (LAP), fatty liver index (FLI), visceral adiposity index (VAI), other anthropometric measurements, and laboratory results were evaluated regarding the patient's diagnostic status of metabolic syndrome and menopause.

Results:

The prevalence of metabolic syndrome was 11.6% and that of premenopausal and postmenopausal group were 7.0% and 14.6%, respectively. By univariate analysis, the area under the curve of the receiver operating characteristic curve of LAP, VAI, and FLI were 0.93, 0.93, and 0.93, respectively, in premenopausal group, and they were decreased in postmenopausal group, with the value of 0.89, 0.89, and 0.88, respectively.

Conclusion:

This study showed the predictive values of LAP, VAI, and FLI for metabolic syndrome upon the patient's status of menopause—such markers should be carefully applied in women of menopausal transition.

Introduction

Nowadays, due to the increased prevalence of abdominal obesity paired with decreased physical activities and modern lifestyle changes, most of urban women in current societies have been exposed to subsequently increased risks for metabolic syndrome, which is known to affect more than 50% of the elderly female population through its association with a threefold increase in the population's morbidity and mortality, mainly due to related cardiovascular disease (CVD).^1
–3 Because of close relation of metabolic syndrome and morbidities of CVD, early diagnosis through appropriate screening exams and corresponding aggressive treatments has been emphasized.

Metabolic syndrome is especially associated with insulin resistance.¹ Obesity is a proinflammatory state that fosters insulin resistance, which is in turn widely believed as the contributing state of dyslipidemia and glucose intolerance.⁴ Menopause has been associated with changes in body composition resulting in an increase in central adiposity and especially visceral fat, and central adiposity in postmenopausal women has been recognized as an independent risk for developing metabolic syndrome, dyslipidemia, and CVD.⁵ In addition to CVD, the risk for nonalcoholic fatty liver disease increases with age in women, showing higher prevalence among 40–49 years and after menopause.⁶

Among such various pathologic states related with metabolic syndrome, obesity plays a critical role in developing, diagnosing, and treating metabolic syndrome. Indicators to predict and measure the degree of obesity are widely studied, including lipid accumulation product (LAP), fatty liver index (FLI), and visceral adiposity index (VAI), all of which are increased in the prevalence of obesity and often used in important public health issues.⁷ LAP is known as a safe and inexpensive index for central lipid accumulation, composed of waist circumference (WC) and fasting concentration of circulating triglycerides (TG).⁸ FLI is also an algorithm based on TG concentration, and gamma-glutamyl transferase (GGT) level, body mass index (BMI), and WC. Currently, it is widely applied in specific population type, such as women with age over 50, and strongly associated with hypertension and type 2 diabetic mellitus.⁹ VAI is an index to evaluate the distribution and function of adipose tissue, based on WC, BMI, TG, and high-density lipoprotein cholesterol (HDL-C).^10
–12

Each of LAP, FLI, and VAI is currently being studied as an effective marker for prediction of metabolic syndrome in wide spectrum of general population, but predominance to predict metabolic syndrome according to menopausal status has not been clearly investigated.

Therefore, this study aimed to determine the association between the three indices and metabolic syndrome and to further explore their practicality to predict the risk of metabolic syndrome in subjects with menopausal status, ultimately contributing to the possibility of early diagnosis of the disease and effective therapeutic intervention.

Methods

Study population

This cross-sectional study included 5930 female patients who were managed at Pusan National University Hospital Health Promotion Center between 2008 and 2014. Each patient was assessed for her demographic data at first visit and further completed self-report questionnaires with personal interviews with a healthcare provider to record their past medical history such as any previous disease, medication, and/or menstrual histories. Patients with fatty liver, hepatitis B, hepatitis C, steroid treatment for asthma, arthritis, rheumatic diseases, unclear medical record, and/or incomplete self-report questionnaires were excluded from analysis; finally, 3936 patients were included in the study, and all of them agreed with informed consent forms indicating that their medical records were to be used for this study.

The patients were further categorized as per their menopausal status: 1565 premenopausal patients and 2371 postmenopausal patients. Menopause was defined when the patient had her both ovaries resected and/or was amenorrhic for more than 1 year. Premenopausal group included those patients with both ovaries intact or with history of single ovary resection and/or amenorrhea for or less than 1 year. For patients who had already undergone hysterectomy, menopause was defined when their serum follicle-stimulating hormone (FSH) level was higher than 40 mIU/mL, while those patients with serum FSH level below 40 mIU/mL were defined as premenopausal state.

Anthropometric measurements and laboratory analysis

Each of the patient's height, weight, and WC was measured individually. BMI was analyzed as the patient's weight in kilograms divided by her height in meters squared, and the percent total body fat and body muscle were measured with automatic machine (X-SCAN PLUS II; Jawon medical, Seoul, South Korea). A single automatic measurement of systolic and diastolic blood pressure was done and recorded for each patient (BP-203 RV II; Colin Corp., Aichi, Japan) 10 min after she was in sitting position. Laboratory blood tests were done after 8 hrs of overnight fasting and included following measurements: total cholesterol, low-density lipoprotein (LDL), HDL-C, total bilirubin, direct bilirubin, total protein, albumin, blood urea nitrogen, creatinine, free fatty acid, uric acid, phosphate, calcium, alkaline phosphatase, and C-reactive protein using Roche Modular DP (Tokyo, Japan) with enzymatic colorimetric method, fasting glucose using glucose oxidase (LX-20; Beckman Coulter), insulin concentration using Coat-A-Count^® Insulin by solid-phase 125I radioimmunoassay, thyroid stimulating hormone (TSH) using Coat-A-Count TSH IRMA, SIMENS, and free thyroxine (FT4) using Coat-A-Count free T4, SIMENS. Homeostasis model assessment for insulin resistance (HOMA-IR) was calculated using the following equation: HOMA-IR = (glucose × insulin)/405.¹³

Calculation of LAP, FLI, and VAI

LAP¹⁴

LAP was calculated as follows: LAP = (WC [cm] −58) × TG (mmol/L).

FLI⁹

FLI was calculated as follows: FLI = (e 0.953 × loge (TG) + 0.139 × BMI + 0.718 × loge (GGT) + 0.053 × WC − 15.745)/(1 + e 0.953 × loge (TG) + 0.139 × BMI + 0.718 × loge (GGT) + 0.053 × WC − 15.745) × 100.

VAI¹⁰

VAI was calculated as follows: VAI = (WC/36.58 + (1.89 × BMI)) × (TG/0.81) × (1.52/HDL).

Diagnostic criteria

In this study, diagnostic criteria for metabolic syndrome was applied as stated in the National Cholesterol Education Program reported in Adult Treatment Panel III. Patients with three or more inclusion out of five diagnostic criteria were diagnosed as having metabolic syndrome, which are as follows: (1) abdominal circumference over 80 cm (for Asian women), (2) TG level over 150 mg/dL, (3) HDL-C less than 50 mg/dL, (4) fasting blood glucose (FBG) over 110 mg/dL or diabetes mellitus (DM), and (5) blood pressure over 130/85 or hypertension medication.¹⁵ Those without metabolic syndrome were considered as control group.

Statistical analysis

SAS 9.3 program was used for statistical analysis. Independent t-test or Wilcoxon rank sum test was used for continuous variables in comparisons of two groups. In comparisons among three groups, one-way ANOVA or Kruskal–Wallis test was used for continuous variables. For categorical variables, chi square test was applied. For calculation of area under the receiver operating characteristic (ROC) curve, logistic regression model was used. Two-sided values of P < 0.05 were considered as statistically significant.

Results

Comparative evaluation of the clinical characteristics in relation to the menopausal status and metabolic syndrome

Statistically significant differences were found in all parameters except serum-free fatty acid, free T4 and TSH, albumin, creatinine, and phosphate levels between pre- and postmenopausal groups (Table 1). Table 2 indicates the differences between parameters regarding the presence or absence of metabolic syndrome in each of the pre- and postmenopausal groups. In premenopausal group, 109 patients had metabolic syndrome with the prevalence rate of 7.0%, and compared to the premenopausal group, postmenopausal group was composed of higher percentage of metabolic syndrome patients with the prevalence rate of 14.67% (346 patients). There was no significant difference again in serum-free fatty acid level, but total bilirubin, total protein, uric acid, and calcium levels were all significantly higher in the patients with metabolic syndrome in comparison to those without metabolic syndrome in both premenopausal and postmenopausal groups. However, when comparing the premenopausal against the postmenopausal among the patients with metabolic syndrome, these values were not significantly different.

Table 1.

Clinical Characteristics of the Subjects

Characteristics	Overall (n = 3936)	MetS (−) (n = 3481)	MetS (+) (n = 455)	P
Characteristics	100%	88.4%	11.6%	P
PreM women (%)	1565 (39.8)	1456(43.8)	109 (24.0)	<0.001
PostM women (%)	2371 (60.2)	2025 (58.2)	346 (76.0)
Nonsmoking (%)	3731 (94.8)	3303 (94.9)	428 (94.1)	0.530
Smoking (%)	205 (5.2)	178 (5.1)	29 (5.9)
Age	52.14 (10.97)	51.39 (10.85)	57.86 (10.19)	<0.001
Age^*	53.00 [16.00, 85.00]	52.00 [16.00, 84.00]	58.00 [24.00, 85.00]	<0.001
Body weight	57.16 (7.94)	56.19 (7.10)	64.51 (9.89)	<0.001
Obesity degree	109.30 (14.01)	107.37 (12.76)	124.09 (14.32)	<0.001
Percent body fat	29.49 (4.82)	28.88 (4.59)	34.19 (3.89)	<0.001
SBP	117.68 (16.84)	115.53 (15.57)	134.13 (17.08)	<0.001
DBP	71.91 (10.17)	70.84 (9.62)	80.16 (10.54)	<0.001
WC	79.34 (8.24)	78.09 (7.47)	88.89 (7.56)	<0.001
BMI	23.02 (3.11)	22.58 (2.75)	26.41 (3.60)	<0.001
Body muscle	36.75 (3.56)	36.53 (3.33)	38.48 (4.61)	<0.001
Cholesterol	200.68 (37.86)	199.30 (37.34)	211.20 (40.17)	<0.001
Triglyceride^**	82.00 [59.00, 116.00]	77.00 [57.00, 105.00]	156.00 [108.00, 193.00]	<0.001
HDL-C	59.23 (14.94)	61.01 (14.50)	45.61 (10.57)	<0.001
LDL-C	125.84 (35.53)	124.21 (34.93)	138.27 (37.59)	<0.001
Free fatty acid	651.61 (317.36)	650.91 (320.78)	656.93 (290.14)	0.681
Glucose^**	87.00 [82.00, 94.25]	86.00 [81.00, 92.00]	102.00 [93.00, 114.00]	<0.001
Insulin^**	4.04 [3.06, 5.31]	3.90 [2.97, 5.06]	5.73 [4.28, 8.10]	<0.001
Free T4^**	1.28 [1.16, 1.43]	1.28 [1.16, 1.43]	1.27 [1.17, 1.41]	0.408
TSH^**	1.69 [1.14, 2.57]	1.69 [1.14, 2.57]	1.70 [1.21, 2.63]	0.461
HOMA-IR^**	0.88 [0.64, 1.23]	0.83 [0.62, 1.12]	1.53 [1.08, 2.28]	<0.001
LDH	318.53 (89.96)	316.10 (89.05)	337.14 (94.74)	<0.001
Total bilirubin	0.93 (0.36)	0.94 (0.36)	0.88 (0.32)	0.001
Direct bilirubin	0.20 (0.08)	0.20 (0.08)	0.19 (0.07)	<0.001
Total protein	7.17 (0.40)	7.16 (0.40)	7.25 (0.39)	<0.001
Albumin	4.36 (0.26)	4.36 (0.26)	4.37 (0.26)	0.793
BUN	14.33 (3.93)	14.28 (3.84)	14.74 (4.48)	0.036
Creatinine^**	0.70 [0.65, 0.79]	0.70 [0.65, 0.79]	0.70 [0.64, 0.80]	0.546
Uric acid	4.39 (1.02)	4.34 (0.99)	4.73 (1.18)	<0.001
γ-GTP^**	15.00 [12.00, 22.00]	15.00 [12.00, 21.00]	21.00 [15.00, 33.00]	<0.001
Phosphate^**	3.80 [3.50, 4.10]	3.80 [3.50, 4.10]	3.80 [3.50, 4.20]	0.744
Calcium	9.42 (0.39)	9.40 (0.39)	9.52 (0.38)	<0.001
ALP	123.06 (61.03)	120.62 (59.80)	141.73 (66.87)	<0.001
CRP^**	0.04 [0.02, 0.07]	0.03 [0.02, 0.07]	0.08 [0.03, 0.16]	<0.001
LAP^**	18.95 [11.53, 30.82]	17.09 [10.68, 26.58]	50.79 [35.45, 69.63]	<0.001
FLI	16.25 (16.60)	12.76 (12.13)	42.88 (21.36)	<0.001
VAI^**	1.14 [0.74, 1.84]	1.05 [0.70, 1.55]	2.83 [2.01, 3.88]	<0.001

Data are presented as the means (SD). P value by Student's t-test.

Values are presented as median [range].

Values are presented as median [IQR].

MetS (−), without metabolic syndrome; MetS (+), with metabolic syndrome; PreM, premenopausal; PostM, postmenopausal; SBP, systolic blood pressure; DBP, diastolic blood pressure; WC, waist circumference; BMI, body mass index; HDL-C, high density lipoprotein cholesterol; LDL, low density lipoprotein; free T4, free thyroxine; TSH, thyroid stimulating hormone; HOMA-IR, homeostasis model assessment for insulin resistance; LDH, lactate dehydrogenase; BUN, blood urea nitrogen; γ-GTP, gamma-glutamyltransferase; ALP, alkaline phosphatase; CRP, C-reactive protein; LAP, lipid accumulation product; FLI, fatty liver index; VAI, visceral adiposity index.

Table 2.

Differences of Parameters According to Presence or Absence of Metabolic Syndrome in Both Groups

	Premenopause				Postmenopause
	Overall	MetS (−)	MetS (+)	P	Overall	MetS (−)	MetS (+)	P
n	1565	1456	109		2371	2025	346
%	100.0%	93.0%	7.0%		100.0%	85.4%	14.6%
Free fatty acid	602.00 (315.89)	606.11 (319.76)	547.01 (253.41)	0.023	684.35 (314.14)	683.12 (317.71)	691.56 (292.67)	0.625
Total bilirubin	0.94 (0.37)	0.94 (0.38)	0.96 (0.31)	0.690	0.92 (0.35)	0.93 (0.36)	0.86 (0.32)	<0.001
Total protein	7.16 (0.40)	7.15 (0.41)	7.19 (0.38)	0.288	7.17 (0.40)	7.16 (0.40)	7.27 (0.40)	<0.001
Uric acid	4.23 (0.92)	4.22 (0.91)	4.39 (0.99)	0.077	4.49 (1.07)	4.43 (1.03)	4.84 (1.22)	<0.001
Calcium	9.35 (0.38)	9.35 (0.39)	9.38 (0.33)	0.319	9.46 (0.39)	9.44 (0.38)	9.56 (0.39)	<0.001

Data are presented as the means (SD). P value by Student's t-test.

FLI, LAP, and VAI of patients with metabolic syndrome according to their menopausal status

The differences of FLI, LAP, and VAI in patients of metabolic syndrome were described in Table 3. All of LAP, FLI, and VAI were significantly higher in postmenopausal group; the area under the curve (AUC) of the ROC curve for FLI in premenopausal group was 0.93 and that of postmenopausal group was 0.89, for LAP, the values were 0.93 in premenopausal group and 0.89 in postmenopausal group; and for VAI, they were 0.90 in premenopausal group and 0.87 in postmenopausal group, respectively.

Table 3.

Logistic Regression Analysis of Fatty Liver Index, Lipid Accumulation Product, and Visceral Adiposity Index in Patients with Metabolic Syndrome

Variable	OR	95% CI		P	AUC	95% CI
Variable	OR	Lower	Upper	P	AUC	Lower area	Upper area
All women with metabolic syndrome
FLI	1.09	1.08	1.10	<0.0001	0.91	0.90	0.92
LAP	1.09	1.09	1.10	<0.0001	0.91	0.90	0.92
VAI	3.12	2.82	3.45	<0.0001	0.88	0.86	0.90
Premenopause
FLI	1.10	1.08	1.11	<0.0001	0.93	0.91	0.95
LAP	1.09	1.08	1.11	<0.0001	0.93	0.91	0.95
VAI	3.19	2.63	3.86	<0.0001	0.90	0.87	0.93
Postmenopause
FLI	1.09	1.08	1.10	<0.0001	0.89	0.87	0.91
LAP	1.09	1.08	1.10	<0.0001	0.89	0.88	0.91
VAI	3.00	2.67	3.38	<0.0001	0.87	0.84	0.89

AUC, area under the curve; OR, odds ratio.

Discussion

In this study, the prevalence of metabolic syndrome in the premenopausal women was 7.0% (109/1565), whereas that in menopausal women was 14.6% (346/2371). Such findings agreed with one of our previous research studying the prevalence of metabolic syndrome in 2832 female patients at Pusan National University Hospital Health Promotion Center from 2006 to 2010; in premenopausal women, the prevalence was 8.69%, and in menopausal women it was 21.85%.¹⁶ Throughout a decade, similar pattern is continuously observed.

Such increased prevalence of metabolic syndrome in menopausal women weighs on prediction of the disease risk, as early intervention—not only the initial treatment itself but also individual awareness with prevention efforts—may result in positive prognosis. Few examinations showing unremarkable changes upon the status of metabolic syndrome have been observed to exhibit significant changes during menopausal transition.¹⁷ Such findings imply that menopausal transition itself might influence how metabolic syndrome affects the same patient, further suggesting that the menopausal status of the patient should be considered when evaluating markers to predict the presence and severity of metabolic syndrome.

Among such markers, several have stood out with their clinical significance: VAI, LAP, and FLI to be discussed. VAI has been significantly associated with the metabolic syndrome factors including cardio- and cerebrovascular risks; the state of visceral obesity is often compromised by increased adipocytokine production, heightened proinflammatory condition, declined insulin sensitivity, and increased diabetic risks.^10,18 According to Amato et al., VAI could be used as an effective indicator of which increase is strongly related to cardiometabolic risk in general population.¹⁰ In this study, women with metabolic syndrome showed higher VAI than the control group, with the AUC of ROC curves of VAI in premenopausal group being 0.90 and 0.87 for postmenopausal group; our results confirm the clinical significance of VAI that could imply the female menopausal state of having metabolic syndrome.

Another index to consider is LAP. LAP is a predictive parameter of mainly diabetes and CVD, often more valued than BMI,^19,20 and has been introduced as a novel index for analyzing central lipid accumulation to estimate the risk of metabolic syndrome.²¹ As in previous studies such as the study of Chiang and Koo regarding Asian population with the age of 50 years or more, our study showed significant increase in LAP among both pre- and postmenopausal women with metabolic syndrome, confirming LAP as a valuable indicator for metabolic syndrome in pre- and postmenopausal women.

Other than the above two indices, FLI could also be used as a predictive marker for metabolic syndrome not only in general population but also in women of menopausal transition. It was originally developed to select subjects to be referred for ultrasonography to diagnose fatty liver²²; not surprisingly, FLI could be a good markers of metabolic syndrome because it is derived from three parameters used to diagnose smetabolic syndrome as well as GGT.²³ So far, several studies announced the AUC for FLI as diagnostic tools of metabolic syndrome; the AUC for FLI was 0.985 according to Rogulj et al. and 0.875 according to by Cheng et al.^9,23 According to our study, it was 0.89, agreeing with the previous studies. Collectively, FLI, LAP, and VAI showed their significant correlation to metabolic syndrome in women under menopausal transition and subsequently their potential role in predicting metabolic syndrome risk in such population.

FLI, LAP, and VAI are thus significant markers to predict the presence and severity of metabolic syndrome, regardless of the patient's menopausal status, and in this study, those markers were collectively studied in each population group. In premenopausal status, FLI and LAP showed relatively higher AUC than VAI, and in postmenopausal status, LAP had higher AUC than the other two. Moreover, in postmenopausal status, AUC of all of the three markers was found to be somewhat decreased, indicating that these markers had higher predicative values in premenopausal than in postmenopausal status. Such result can be strengthened with furthers studies with more number of subjects; when such phenomenon was confirmed with larger population, more efforts to come up with the markers that could predict metabolic syndrome with special consideration of physiological changes in postmenopausal status of the patient are inevitable.

The FLI and LAP are originally designed to evaluate the risk of fatty liver and CVD, and both have been shown to be efficient markers of metabolic syndrome.^4,10,12,15 In general, the use of FLI to predict metabolic syndrome was rather concentrated in patients with ongoing fatty liver disease, but several studies on Asian population shows the significantly effective use of FLI even in the population without fatty liver disease.²⁴ In this study, all the patients had never been diagnosed with fatty liver disease, but the FLI of women with metabolic syndrome was still significantly increased, proving FLI could be effectively used in population without fatty liver disease.

In terms of generality of population, this study mostly regards women in menopausal transition—before and after menopause, with a few patients with ages of extreme ends—solely with Korean ethnicity, even narrowed down to the female population in the city of Busan. It might hardly represent the general population, but if further studies were carried in other regions of Korea, such comprehensive study could explain more generalized characteristics of Korean women, further adding to valuable knowledge on Asian menopausal population.

Despite increased risk of metabolic syndrome in Asian population, the use of metabolic indices to predict the risk of such disease has been not thoroughly studied, especially in Asian population. In our study, the possibility of FLI, VAI, and LAP as more effective indices for metabolic syndrome when collectively used has been clearly observed through statistical analysis. Further studies regarding the collective use of FLI, VAI, and LAP on various ethnicities and populations and potential cutoff values for each index could result in their clinical application in early intervention and prevention of the disease.

Footnotes

Author Disclosure Statement

No conflicting financial interests exist.

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