Endocrinol Metab > Volume 30(3); 2015 > Article
Kong, Kang, Joung, Lee, Kim, and Ku: Plasma Adiponectin Levels in Elderly Patients with Prediabetes

Abstract

Background

The significance of adiponectin levels in elderly individuals with prediabetes has yet to be determined. Thus, the present study was performed to evaluate the relationships between adiponectin levels and anthropometric variables, body composition parameters, insulin sensitivity, and lipid profiles in elderly prediabetic patients.

Methods

The present study included 120 subjects with prediabetes who were >65 years of age and were selected from among 1,993 subjects enrolled in the Korea Rural Genomic Cohort Study. All subjects underwent a 75 g oral glucose tolerance test and tests for measurement of insulin sensitivity. All diagnoses of prediabetes satisfied the criteria of the American Diabetes Association.

Results

Plasma adiponectin levels were lower in elderly prediabetic subjects than elderly subjects with normal glucose tolerance (P<0.01) as well as in elderly prediabetic patients with metabolic syndrome (MetS) than in those without MetS (P<0.02). When the subjects were categorized into two groups according to plasma adiponectin levels, the waist-to-hip ratio and 2-hour insulin levels were significantly lower in individuals with high plasma adiponectin levels than in those with low plasma adiponectin levels. Additionally, the plasma adiponectin levels of elderly prediabetic subject were inversely correlated with body mass index (BMI), waist circumference (WC), waist-to-hip ratio, visceral fat, visceral fat ratio, and 2-hour insulin levels.

Conclusion

The present findings demonstrated that the major factors correlated with adiponectin levels in elderly prediabetic subjects were BMI, WC, waist-to-hip ratio, visceral fat, visceral fat ratio, and 2-hour insulin levels.

INTRODUCTION

Type 2 diabetes mellitus (T2DM) and obesity are major public health problems, the incidences of which are rapidly increasing worldwide [1,2]. Furthermore, the global population is aging rapidly, and all countries, including Korea, have undergone a rapid increase in the rates of obesity among the elderly. For example, a recent report from the Korea Centers for Disease Control and Prevention found that the mean prevalence of obesity in individuals >65 years of age increased from 25.0% in 1998 to 34.2% in 2012 [3] and another study found that aging is associated with an increased body fat mass and insulin resistance [4]. Obesity, particularly central obesity, is associated with insulin resistance, dyslipidemia, and hypertension and is a strong risk factor of cardiovascular disease (CVD) [5,6]. Taken together, these data suggest that obesity, insulin resistance, and aging are closely related.
Adiponectin is an adipose tissue-specific adipokine that plays a protective role against insulin resistance and inflammation and also protects the body against metabolic diseases [7,8]. T2DM and the accumulation of visceral fat decrease adiponectin levels [9] via the inhibitory actions of tumor necrosis factor-α on the adiponectin gene [10]. A prospective cohort study that analyzed 372 elderly Korean subjects established a relationship between reduced plasma adiponectin levels and T2DM or metabolic syndrome (MetS) [11]. Additionally, a cross-sectional study of patients with impaired fasting glucose (IFG) revealed that plasma adiponectin levels are associated with the risk of CVD [12]. According to the majority of studies investigating prediabetic patients, adiponectin levels are related to a number of body composition parameters, lipid profiles, insulin resistance factors (such as the homeostasis model assessment of insulin resistance [HOMA-IR] index), and various serum biomarkers of CVD. However, the significance of adiponectin levels in elderly prediabetic individuals has yet to be determined.
Thus, the present study evaluated the relationship between plasma adiponectin levels and clinical factors including anthropometric variables, body composition parameters, insulin sensitivity, and lipid profiles in elderly patients with prediabetes.

METHODS

Subjects

The present study included 120 individuals with prediabetes who were >65 years of age and were selected from among 1993 subjects enrolled in the Korea Rural Genomic Cohort Study (Geumsan County). Institutional Review Board of Chungnam National University Hospital approval was obtained prior to commencement of the study and all participants provided written informed consent prior to participation.
MetS was diagnosed in accordance with the updated International Diabetes Federation guidelines [13] and all diagnoses of prediabetes satisfied the 2014 criteria of the American Diabetes Association [14]. Subjects who were newly diagnosed with diabetes were excluded from the present study. Each subject completed a standardized questionnaire concerning their personal medical history of chronic and acute illnesses and medication use.

Anthropometric and body composition measurements

All subjects underwent measurements of several anthropometric variables including height, body weight, waist circumference (WC), blood pressure (BP), and body mass index (BMI).
A single experimenter performed both the height and weight measurements, WC was measured from the midpoint between the lowest rib and the iliac crest upon expiration, and BP was measured after at least 5 minutes of rest while in a seated position using the right arm of the patients. BMI was calculated as weight (kg) divided by height squared (m2) and body composition was calculated using a bioelectric impedance analysis (InBody 4.0, Biospace Co., Seoul, Korea) that included fat mass, percent body fat, and lean mass.

Laboratory analysis

After a 12-hour overnight fast, all subjects underwent a 75 g oral glucose tolerance test, blood chemistry analysis, and measurement of their plasma adiponectin levels. Serum insulin levels were measured with the Coat-A-Count radioimmunoassay (RIA, DPC, Los Angeles, CA, USA) and plasma adiponectin levels were measured using a Human Adiponectin RIA kit (Linco Research Inc., Saint Louis, MO, USA). Insulin resistance was estimated using the HOMA-IR index and the quantitative insulin sensitivity check index (QUICKI) using the following formulae: HOMA-IR=(fasting insulin [µU/mL]×fasting plasma glucose [mmol/L])/405 and QUICKI=1/(log fasting insulin [µU/mL]+log fasting plasma glucose [mg/dL]).

Pulse-wave velocity

Brachial-ankle pulse-wave velocity (baPWV) was measured using a pulse wave analyzer (BP-203RPE, Colin, Komaki, Japan) and defined as the mean of the left- and right-sided baPWV values. The pulse waves of the brachial and tibial arteries were simultaneously recorded using an oscillometric method.

Statistical analysis

All statistical analyses were conducted using SPSS version 21.0 (IBM Co., Armonk, NY, USA) and all statistical values are presented as mean±standard deviations. Student t tests were used to compare the baseline characteristics of the normal glucose tolerance (NGT) and prediabetic groups and unpaired t tests were used to compare the mean anthropometric variables and clinical parameters of the groups with and without MetS. Pearson's correlation coefficients were calculated to evaluate the relationships between adiponectin levels and blood lipid profiles, anthropometric factors, body composition variables, and surrogate markers of insulin resistance in newly diagnosed elderly prediabetic subjects and elderly subjects with NGT. P values <0.05 were considered to indicate statistical significance.

RESULTS

Characteristics of the subjects

The present study included 120 newly diagnosed elderly prediabetic subjects and 100 elderly NGT subjects. The glucose and glycated hemoglobin (HbA1c) levels of the elderly prediabetic subjects were higher than those of the elderly NGT subjects. Additionally, the prediabetic subjects had significantly higher amounts of visceral fat, a higher visceral fat ratio, a higher HOMA-IR index, higher fasting and 2-hour insulin levels, and higher levels of HbA1c, total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C), PWV, BP, and ferritin but lower QUICK scores than the elderly NGT subjects. On the other hand, the NGT subjects had significantly higher plasma adiponectin levels than the prediabetic subjects (12.71±4.76 µg/mL vs. 10.39±4.56 µg/mL, respectively; P<0.01). Additionally, the anthropometric variables-WC, hip circumference (HC), visceral fat, the visceral fat ratio, and the total body fat ratio-were significantly higher in prediabetic females, but not males, relative to the NGT subjects (Table 1).

Clinical profiles of the elderly prediabetic subjects according to the presence of MetS

The elderly prediabetic subjects were separated into two groups based on the presence or absence of MetS. There were significant differences between subjects with and without MetS in all of the anthropometric variables and body composition parameters, fasting glucose levels, fasting insulin levels, 2-hour insulin levels, and insulin resistance-related factors, including the HOMA-IR index and QUICK. However, there were no significant differences in high density lipoprotein cholesterol (HDL-C), LDL-C, TC, and BP levels. The subjects without MetS had significantly higher plasma adiponectin levels than did those with MetS (11.10±4.62 µg/mL vs. 8.61±3.48 µg/mL, respectively; P<0.02) (Table 2).

Clinical profiles according to plasma adiponectin levels

When the subjects were categorized into two groups according to plasma adiponectin levels, the high plasma adiponectin group had significantly lower waist-to-hip ratio and 2-hour insulin levels than the low plasma adiponectin group. All of the anthropometric variables, except waist-to-hip ratio, all body composition parameters, and the fasting glucose, 2-hour glucose, TC, LDL-C, and BP levels were higher in the high plasma adiponectin group than in the low plasma adiponectin group; however, there were no significant differences (Table 3).

Correlations between adiponectin levels and clinical profiles

The Pearson's correlation coefficients between the subjects' adiponectin levels and lipid profiles, anthropometric variables, body composition parameters, and surrogate markers of insulin resistance are shown in Table 4. In the elderly prediabetic subjects, adiponectin levels were inversely correlated with BMI (r=-0.249, P<0.05), WC (r=-0.282, P<0.05), waist-to-hip ratio (r=-0.321, P<0.01), visceral fat (r=-0.306 0, P<0.01), the visceral fat ratio (r=-0.326, P<0.01), and the 2-hour insulin levels (r=-0.242, P<0.05). In the elderly NGT subjects, adiponectin levels were inversely correlated with total body fat (r=-0.255, P<0.05), visceral fat (r=-0.309, P<0.05), the visceral fat ratio (r=-0.268, P<0.05), total muscle (r=-0.311, P<0.05), alanine aminotransferase levels (r=-0.308, P<0.05) but positively correlated with TG (r=0.355, P<0.01) and HDL-C (r=0.242, P<0.05) levels.

DISCUSSION

The findings of the present study clearly demonstrated that increased insulin resistance and MetS were related to low adiponectin levels in elderly prediabetic patients. Additionally, the plasma adiponectin levels of these patients were correlated with the waist-to-hip ratio, visceral fat, and the visceral fat ratio, which are indicators of central obesity.
Many studies have reported that plasma adiponectin levels decrease as insulin resistance increases. For example, diabetic and obese monkeys have decreased adiponectin levels prior to the development of diabetes, and this decrease in adiponectin levels parallels changes in insulin sensitivity [15]. In a study of 376 prediabetic patients, the prediabetic group exhibited a significantly lower mean±SD adiponectin level compared to NGT subjects (4.6±2.3 µg/mL vs. 5.0±2.8 µg/mL in males, and 7.1±3.6 µg/mL vs. 8.1±4.6 µg/mL in females, respectively; P<0.001) [16]. Similarly, in the present study elderly prediabetic patients had significantly lower adiponectin levels than elderly individuals with NGT (10.2±4.3 µg/mL vs. 12.7±4.7 µg/mL, respectively; P<0.001).
Additionally, there were significant differences between the visceral fat level and visceral fat ratio of elderly prediabetic subjects and elderly NGT subjects. This finding suggests that, similar to the general population, the accumulation of visceral fat was related to insulin resistance in elderly prediabetic patients. Additionally, the BP, baPWV, and lipid profiles of the elderly prediabetic subjects exhibited significant increases compared to those of the elderly NGT subjects. This suggests that a prediabetes status in elderly patients is associated with the risk of CVD and metabolic diseases.
In the present study, all measures of the anthropometric variables and body composition parameters were higher in the prediabetic females than the prediabetic males. Furthermore, compared to the NGT subjects, anthropometric variables-such as WC, HC, visceral fat, the visceral fat ratio, and the total body fat ratio-were significantly higher in prediabetic females but not males. It is possible that changes in the hormonal status of females during menopause and aging result in increases in measures of central fat distribution and visceral fat accumulation. Previous studies have shown that testosterone decreases adiponectin levels [17] and that the adiponectin levels of males are lower than those of females [16,17,18,19]. However, in the present study, the adiponectin levels of males were higher than those of females. It has been demonstrated that effective estradiol treatment decreases adiponectin levels in postmenopausal females [20,21] and the present study indicates that a higher visceral fat ratio and higher BMI, WC, and visceral fat levels in females influence adiponectin levels.
Clinical and experimental studies have indicated that adiponectin directly affects obesity-related disorders, insulin resistance, and atherosclerosis [22,23,24,25]. Additionally, it is known that adiponectin plays an essential role in the development of MetS because there is a general correlation between MetS and plasma adiponectin levels in normal healthy subjects [26]. Furthermore, large population-based studies have shown that adiponectin levels in individuals with IFG and MetS are significantly lower than those of subjects with IFG but without MetS [12]. Similarly, the present study found that elderly prediabetic subjects with MetS had lower levels of adiponectin than the prediabetic subjects without MetS (11.10±4.62 µg/mL vs. 8.61±3.48 µg/mL, respectively; P<0.02). Additionally, the associations between the metabolic parameters and plasma adiponectin levels of IFG and NGT subjects in the present study were similar to those reported in previous studies [12,20].
Low adiponectin levels likely play a major role in the development of MetS [27,28]. A prospective cohort study that analyzed 372 elderly subjects divided into tertiles based on adiponectin levels found that individuals in the lowest tertile were 3.2-fold more likely to develop T2DM (95% confidence interval [CI], 1.415 to 7.295; P=0.005) and 2.7-fold more likely to develop MetS (95% CI, 0.94 to 6.70; P=0.031) than subjects in the highest tertile [11]. A study of 661 Japanese individuals reported that the components of MetS increased as adiponectin levels decrease [29] and a study of 596 healthy Korean subjects observed an association between low adiponectin levels and MetS [26]. However, in the present study, the elderly subjects with low adiponectin levels only showed significant increases in their waist-to-hip ratio and 2-hour insulin levels.
Many studies have found a correlation between plasma adiponectin levels and the metabolic profiles of various populations, including normal healthy adults, adults with central obesity, individuals with IFG, and T2DM patients [11,12,30,31,32,33,34]. In a majority of these studies, adiponectin levels were found to be correlated with metabolic parameters and serum biomarkers of insulin resistance or the risk of CVD. However, in the present study, adiponectin levels were negatively correlated with BMI, WC, the waist-to-hip ratio, visceral fat, the visceral fat ratio, and 2-hour insulin levels. Therefore, central obesity, particularly in conjunction with the accumulation of visceral fat, had the highest correlation with adiponectin levels in elderly prediabetic patients.
The present study has several limitations. First, the cross-sectional design and small sample size of this study meant that data regarding the exact predictive values of adiponectin levels in terms of the risks of T2DM and CVD or changes in adiponectin within specific individuals could not be obtained. Second, the present study was unable to adjust for MetS-related lifestyle factors. Nevertheless, this study is the first to investigate the relationships between various metabolic parameters and adiponectin levels in elderly prediabetic subjects.
In conclusion, the present study found that the clinical and biochemical characteristics associated with adiponectin levels in elderly prediabetic subjects were similar to those of prediabetic subjects of all ages, with only a few exceptions. Large-scale longitudinal prospective studies are needed to clarify the role of adiponectin in the development of T2DM and CVD.

ACKNOWLEDGMENTS

This work was supported by the research fund of Chungnam National University.

NOTES

CONFLICTS OF INTEREST: No potential conflict of interest relevant to this article was reported.

REFERENCES

1. Cowie CC, Rust KF, Ford ES, Eberhardt MS, Byrd-Holt DD, Li C, et al. Full accounting of diabetes and pre-diabetes in the US population in 1988-1994 and 2005-2006. Diabetes Care 2009;32:287-294.
[CROSSREF]  [PUBMED]  [PMC] 
2. Gill T. Epidemiology and health impact of obesity: an Asia Pacific perspective. Asia Pac J Clin Nutr 2006;15(Suppl):3-14.
[PUBMED] 
3. Kim CS, Ko SH, Kwon HS, Kim NH, Kim JH, Lim S, et al. Prevalence, awareness, and management of obesity in Korea: data from the Korea National Health and Nutrition Examination Survey (1998-2011). Diabetes Metab J 2014;38:35-43.
[CROSSREF]  [PUBMED]  [PMC] 
4. Ginter E, Simko V. Diabetes type 2 pandemic in 21st century. Bratisl Lek Listy 2010;111:134-137.
[CROSSREF]  [PUBMED] 
5. Koh-Banerjee P, Wang Y, Hu FB, Spiegelman D, Willett WC, Rimm EB. Changes in body weight and body fat distribution as risk factors for clinical diabetes in US men. Am J Epidemiol 2004;159:1150-1159.
[CROSSREF]  [PDF]
6. Walker SP, Rimm EB, Ascherio A, Kawachi I, Stampfer MJ, Willett WC. Body size and fat distribution as predictors of stroke among US men. Am J Epidemiol 1996;144:1143-1150.
[CROSSREF]  [PUBMED]  [PDF]
7. Combs TP, Berg AH, Obici S, Scherer PE, Rossetti L. Endogenous glucose production is inhibited by the adipose-derived protein Acrp30. J Clin Invest 2001;108:1875-1881.
[CROSSREF]  [PUBMED]  [PMC] 
8. Tilg H, Moschen AR. Role of adiponectin and PBEF/visfatin as regulators of inflammation: involvement in obesity-associated diseases. Clin Sci (Lond) 2008;114:275-288.
[CROSSREF]  [PUBMED]  [PDF]
9. Yang WS, Lee WJ, Funahashi T, Tanaka S, Matsuzawa Y, Chao CL, et al. Weight reduction increases plasma levels of an adipose-derived anti-inflammatory protein, adiponectin. J Clin Endocrinol Metab 2001;86:3815-3819.
[CROSSREF]  [PUBMED] 
10. Maeda N, Takahashi M, Funahashi T, Kihara S, Nishizawa H, Kishida K, et al. PPARgamma ligands increase expression and plasma concentrations of adiponectin, an adipose-derived protein. Diabetes 2001;50:2094-2099.
[CROSSREF]  [PUBMED] 
11. Choi KM, Lee J, Lee KW, Seo JA, Oh JH, Kim SG, et al. Serum adiponectin concentrations predict the developments of type 2 diabetes and the metabolic syndrome in elderly Koreans. Clin Endocrinol (Oxf) 2004;61:75-80.
[CROSSREF]  [PUBMED] 
12. Nam JS, Park JS, Cho MH, Jee SH, Lee HS, Ahn CW, et al. The association between pulse wave velocity and metabolic syndrome and adiponectin in patients with impaired fasting glucose: cardiovascular risks and adiponectin in IFG. Diabetes Res Clin Pract 2009;84:145-151.
[CROSSREF]  [PUBMED] 
13. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation 2009;120:1640-1645.
[CROSSREF] 
14. American Diabetes Association. Standards of medical care in diabetes: 2014. Diabetes Care 2014;37(Suppl 1):S14-S80.
[CROSSREF]  [PUBMED] 
15. Hotta K, Funahashi T, Bodkin NL, Ortmeyer HK, Arita Y, Hansen BC, et al. Circulating concentrations of the adipocyte protein adiponectin are decreased in parallel with reduced insulin sensitivity during the progression to type 2 diabetes in rhesus monkeys. Diabetes 2001;50:1126-1133.
[CROSSREF]  [PUBMED] 
16. Saltevo J, Kautiainen H, Vanhala M. Gender differences in adiponectin and low-grade inflammation among individuals with normal glucose tolerance, prediabetes, and type 2 diabetes. Gend Med 2009;6:463-470.
[CROSSREF]  [PUBMED] 
17. Nishizawa H, Shimomura I, Kishida K, Maeda N, Kuriyama H, Nagaretani H, et al. Androgens decrease plasma adiponectin, an insulin-sensitizing adipocyte-derived protein. Diabetes 2002;51:2734-2741.
[CROSSREF]  [PUBMED] 
18. Cnop M, Havel PJ, Utzschneider KM, Carr DB, Sinha MK, Boyko EJ, et al. Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia 2003;46:459-469.
[CROSSREF]  [PUBMED]  [PDF]
19. Snehalatha C, Mukesh B, Simon M, Viswanathan V, Haffner SM, Ramachandran A. Plasma adiponectin is an independent predictor of type 2 diabetes in Asian indians. Diabetes Care 2003;26:3226-3229.
[CROSSREF]  [PUBMED] 
20. Laughlin GA, Barrett-Connor E, May S. Sex-specific determinants of serum adiponectin in older adults: the role of endogenous sex hormones. Int J Obes (Lond) 2007;31:457-465.
[CROSSREF]  [PUBMED]  [PDF]
21. Morad V, Abrahamsson A, Dabrosin C. Estradiol affects extracellular leptin:adiponectin ratio in human breast tissue in vivo. J Clin Endocrinol Metab 2014;99:3460-3467.
[CROSSREF]  [PUBMED]  [PDF]
22. Ziemke F, Mantzoros CS. Adiponectin in insulin resistance: lessons from translational research. Am J Clin Nutr 2010;91:258S-261S.
[CROSSREF]  [PUBMED]  [PDF]
23. Villarreal-Molina MT, Antuna-Puente B. Adiponectin: anti-inflammatory and cardioprotective effects. Biochimie 2012;94:2143-2149.
[CROSSREF]  [PUBMED] 
24. Ouchi N, Walsh K. Adiponectin as an anti-inflammatory factor. Clin Chim Acta 2007;380:24-30.
[CROSSREF]  [PUBMED]  [PMC] 
25. Calton EK, Miller VS, Soares MJ. Factors determining the risk of the metabolic syndrome: is there a central role for adiponectin? Eur J Clin Nutr 2013;67:485-491.
[CROSSREF]  [PUBMED]  [PDF]
26. Yoo KH, Oh IM, Park JE, Kim MJ, Park JS, Park SJ, et al. Metabolic syndrome is associated with low adiponectin level and increased insulin resistance in apparently healthy Koreans. Korean J Obes 2012;21:175-182.
[CROSSREF]  [PDF]
27. Nigro E, Scudiero O, Monaco ML, Palmieri A, Mazzarella G, Costagliola C, et al. New insight into adiponectin role in obesity and obesity-related diseases. Biomed Res Int 2014;2014:658913
[CROSSREF]  [PUBMED]  [PMC]  [PDF]
28. Hulthe J, Hulten LM, Fagerberg B. Low adipocyte-derived plasma protein adiponectin concentrations are associated with the metabolic syndrome and small dense low-density lipoprotein particles: atherosclerosis and insulin resistance study. Metabolism 2003;52:1612-1614.
[CROSSREF]  [PUBMED] 
29. Ryo M, Nakamura T, Kihara S, Kumada M, Shibazaki S, Takahashi M, et al. Adiponectin as a biomarker of the metabolic syndrome. Circ J 2004;68:975-981.
[CROSSREF] 
30. De Rosa A, Monaco ML, Capasso M, Forestieri P, Pilone V, Nardelli C, et al. Adiponectin oligomers as potential indicators of adipose tissue improvement in obese subjects. Eur J Endocrinol 2013;169:37-43.
[CROSSREF]  [PUBMED] 
31. Hamilton MP, Gore MO, Ayers CR, Xinyu W, McGuire DK, Scherer PE. Adiponectin and cardiovascular risk profile in patients with type 2 diabetes mellitus: parameters associated with adiponectin complex distribution. Diab Vasc Dis Res 2011;8:190-194.
[CROSSREF]  [PUBMED] 
32. Mohan V, Deepa R, Pradeepa R, Vimaleswaran KS, Mohan A, Velmurugan K, et al. Association of low adiponectin levels with the metabolic syndrome: the Chennai Urban Rural Epidemiology Study (CURES-4). Metabolism 2005;54:476-481.
[CROSSREF]  [PUBMED] 
33. Hung J, McQuillan BM, Thompson PL, Beilby JP. Circulating adiponectin levels associate with inflammatory markers, insulin resistance and metabolic syndrome independent of obesity. Int J Obes (Lond) 2008;32:772-779.
[CROSSREF]  [PUBMED]  [PDF]
34. Lee SE, Moon JH, Ahn JH, Oh YS, Shinn SH. The association between plasma adiponectin and the components of metabolic syndrome in adults with abdominal obesity. Korean J Obes 2007;16:147-153.
Table 1

Baseline Characteristics of the Study Subjects

Values are expressed as mean±SD. Two-hour glucose and 2-hour insulin represent glucose and insulin levels at 120 minutes after a glucose challenge. NGT, normal glucose tolerance; BMI, body mass index; WC, waist circumference; HC, hip circumference; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; QUICKI, quantitative insulin sensitivity check index; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; PWV, pulse-wave velocity; SBP, systolic blood pressure; DBP, diastolic blood pressure; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, gamma-glutamyl transpeptidase; hs-CRP, high-sensitivity C-reactive protein.

aP<0.05 vs. NGT; bP<0.01 vs. NGT.

Characteristic NGT Prediabetes Male Female
NGT Prediabetes NGT Prediabetes
No. of subjects 100 120 33 55 67 65
Age, yr 67.13±1.69 67.20±1.81 67.09±1.82 67.38±1.94 67.15±1.64 67.05±1.69
BMI, kg/m2 23.92±3.25 24.30±3.14 24.14±2.37 23.90±3.41 23.82±3.62 24.64±2.88
WC, cm 80.77±8.14 82.42±8.54 82.21±6.94 80.87±8.48 80.05±8.62 83.72±8.43a
HC, cm 91.45±6.23 92.78±6.53 91.11±6.45 91.16±6.69 91.61±6.16 94.14±6.11a
Waist-to-hip ratio 0.88±0.07 0.88±0.05 0.90±0.10 0.88±0.05 0.87±0.05 0.88±0.05
Total body fat, kg 16.68±5.52 17.7±5.86 17.34±3.75 17.54±6.92 16.36±6.21 17.89±4.83
Visceral fat, kg 2.11±0.88 2.36±0.91a 2.14±0.61 2.27±0.97 2.09±0.99 2.44±0.86a
Total body fat ratio 27.59±6.31 28.53±6.99 29.31±5.10 28.71±7.82 26.74±6.70 28.38±6.27a
Visceral fat ratio 10.33±2.95 11.49±2.67b 10.54±2.64 11.50±2.91 10.23±3.10 11.48±2.48a
Total muscle, kg 39.42±6.98 39.90±7.03 37.33±6.21 37.95±5.91 40.45±7.15 41.58±7.52
Fasting glucose, mmol/L 4.91±6.35 5.38±0.55b 4.94±0.36 5.36±0.55b 4.90±0.35 5.39±0.55b
2-Hour glucose, mmol/L 6.13±1.06 8.10±1.74b 6.34±0.84 8.21±1.59b 6.03±1.15 8.01±1.86b
Fasting insulin, pmol/L 52.16±17.15 64.31±36.18b 53.48±11.95 65.84±40.98a 51.46±19.24 62.99±31.81a
2-Hour insulin, pmol/L 281.76±158.00 362.74±300.30b 274.05±132.02 358.29±207.79a 285.51±170.15 366.56±362.95
HbA1c, % 5.25±0.27 5.63±0.36b 5.29±0.19 5.66±0.31b 5.23±0.22 5.60±0.40b
HOMA-IR index 1.65±0.58 2.24±1.40b 1.69±0.42 2.29±1.57a 1.62±0.65 2.21±1.25b
QUICKI 0.35±0.02 0.34±0.02b 0.35±0.01 0.34±0.02b 0.36±0.02 0.34±0.02b
TC, mmol/L 5.30±0.96 5.72±1.00b 5.59±0.88 5.73±1.09 5.15±0.98 5.72±0.92b
TG, mmol/L 1.69±0.97 2.04±1.19a 1.77±0.88 2.14±1.22 1.66±1.02 1.96±1.17
HDL-C, mmol/L 1.18±0.27 1.18±0.30 1.17±0.28 1.20±0.33 1.19±0.26 1.18±0.23
LDL-C, mmol/L 3.14±0.83 3.41±0.83b 3.44±0.76 3.39±0.89 2.99±0.82 3.43±0.78b
Adiponectin, µg/mL 12.71±4.76 10.39±4.56b 14.07±4.68 10.72±4.74a 11.91±4.67 9.86±4.14a
PWV, m/s 15.30±2.70 16.13±3.40a 18.29±2.33 18.86±2.60 13.83±1.28 14.04±1.03
SBP, mm Hg 131.17±15.99 136.87±16.60b 139.58±15.25 145.76±16.43 127.03±14.77 129.34±12.67
DBP, mm Hg 82.66±9.51 85.78±10.14b 86.97±9.28 88.89±10.84 80.54±8.95 83.15±8.77
AST, U/L 27.04±7.82 29.30±10.32 26.51±6.62 30.85±11.56 27.29±8.38 27.98±13.47
ALT, U/L 22.29±12.07 26.49±12.28a 21.78±10.50 26.14±10.81 22.53±12.83 26.78±13.47
γ-GTP, U/L 24.54±23.29 34.21±42.06a 21.42±13.36 32.23±31.80a 26.07±26.83 35.89±49.29
hs-CRP, mg/dL 1.47±2.11 1.98±3.84 1.49±2.13 1.47±2.11 1.45±2.03 2.41±4.83a
Ferritin, µg/L 67.64±50.06 102.31±97.67b 68.87±43.86 102.06±93.80 67.03±53.15 102.53±101.56a
Table 2

Clinical and Biochemical Characteristics of Elderly Prediabetic Subjects with and without Metabolic Syndrome

Values are expressed as mean±SD. Two-hour glucose and 2-hour insulin represent glucose and insulin levels at 120 minutes after a glucose challenge.

MetS, metabolic syndrome; BMI, body mass index; WC, waist circumference; HC, hip circumference; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; QUICKI, quantitative insulin sensitivity check index; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; PWV, pulse-wave velocity; SBP, systolic blood pressure; DBP, diastolic blood pressure; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, gamma-glutamyl transpeptidase; hs-CRP, high-sensitivity C-reactive protein.

aP<0.05 vs. non-MetS; bP<0.01 vs. non-MetS.

Characteristic Non-MetS MetS
No. of subjects 85 35
Age, yr 67.33±1.91 66.89±1.51
BMI, kg/m2 23.16±2.59 27.08±2.58b
WC, cm 78.61±6.85 91.67±3.84b
HC, cm 90.42±5.68 98.49±4.69b
Waist-to-hip ratio 0.87±0.04 0.93±0.04b
Total body fat, kg 16.01±5.58 21.91±4.20b
Visceral fat, kg 1.98±0.70 3.29±0.67b
Total body fat ratio 27.43±6.95 31.20±6.44b
Visceral fat ratio 10.51±2.40 13.86±1.64b
Total muscle, kg 37.87±5.74 44.84±7.50b
Fasting glucose, mmol/L 5.30±0.50 5.56±0.62a
2-Hour glucose, mmol/L 8.11±1.66 8.09±1.94
Fasting insulin, pmol/L 56.39±27.15 83.62±47.16b
2-Hour insulin, pmol/L 305.72±211.27 498.65±419.96b
HbA1c, % 5.62±0.36 5.65±0.37
HOMA-IR index 1.92±0.96 3.04±1.91b
QUICKI 0.35±0.02 0.33±0.02b
TC, mmol/L 5.70±1.01 5.76±1.00
TG, mmol/L 1.89±1.14 2.41±1.25a
HDL-C, mmol/L 1.21±0.31 1.13±0.20
LDL-C, mmol/L 3.42±0.83 3.39±0.85
Adiponectin, µg/mL 11.10±4.62 8.61±3.48a
PWV, m/sec 16.31±3.55 15.71±3.00
SBP, mm Hg 136.20±17.05 138.49±15.60
DBP, mm Hg 84.36±10.15 89.23±9.40
AST, U/L 28.56±10.39 31.08±10.07
ALT, U/L 23.44±10.15 33.88±13.91b
γ-GTP, U/L 26.23±23.25 53.60±65.65a
hs-CRP, mg/dL 1.82±3.52 2.37±4.57
Ferritin, µg/L 87.33±87.53 138.71±111.95b
Table 3

Clinical and Biochemical Characteristics according to Plasma Adiponectin Level

Values are expressed as mean±SD. Two-hour glucose and 2-hour insulin represent glucose and insulin levels at 120 minutes after a glucose challenge.

BMI, body mass index; WC, waist circumference; HC, hip circumference; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; QUICKI, quantitative insulin sensitivity check index; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; PWV, pulse-wave velocity; SBP, systolic blood pressure; DBP, diastolic blood pressure; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, gamma-glutamyl transpeptidase; hs-CRP, high-sensitivity C-reactive protein.

aP<0.05 vs. low.

Characteristic Plasma adiponectin level
Low High
No. of subjects 36 36
Age, yr 66.94±1.63 67.14±1.80
BMI, kg/m2 24.88±2.95 24.16±3.31
WC, cm 84.24±8.85 81.40±8.85
HC, cm 92.94±6.15 92.96±7.31
Waist-to-hip ratio 0.90±0.06 0.87±0.05a
Total body fat, kg 18.65±5.08 18.09±7.23
Visceral fat, kg 2.61±0.86 2.33±0.96
Visceral fat ratio 12.13±2.16 11.58±3.11
Total muscle, kg 41.06±7.29 38.59±6.78
Fasting glucose, mmol/L 5.37±0.59 5.30±0.64
2-Hour glucose, mmol/L 8.25±1.74 7.80±1.86
Fasting insulin, pmol/L 72.99±47.85 67.37±36.46
2-Hour insulin, pmol/L 520.94±585.05 337.04±179.88a
HbA1c, % 5.68±0.41 5.70±0.30
HOMA-IR index 2.55±1.89 2.33±1.39
QUICKI 0.34±0.02 0.34±0.02
TC, mmol/L 5.83±0.96 5.77±0.97
TG, mmol/L 2.09±0.91 2.18±1.60
HDL-C, mmol/L 1.22±0.25 1.23±0.36
LDL-C, mmol/L 3.46±0.84 3.34±0.78
PWV, m/sec 16.29±3.55 16.14±4.15
SBP, mm Hg 140.03±18.17 137.47±14.35
DBP, mm Hg 88.28±11.14 86.47±8.19
AST, U/L 29.75±8.23 31.44±12.89
ALT, U/L 29.13±12.77 25.02±10.29
γ-GTP, U/L 38.00±35.40 35.19±59.99
hs-CRP, mg/dL 3.32±6.39 1.72±2.31
Ferritin, µg/L 111.76±95.52 90.74±79.92
Table 4

Pearson's Correlation Coefficients for the Relationships between Adiponectin Levels and the Clinical and Biochemical Characteristics of Elderly Prediabetic Patients and Elderly Subjects with Normal Glucose Tolerance

Two-hour glucose and 2-hour insulin represent glucose and insulin levels at 120 minutes after a glucose challenge. r refers to Pearson's correlation coefficient.

NGT, normal glucose tolerance; BMI, body mass index; WC, waist circumference; HC, hip circumference; SBP, systolic blood pressure; DBP, diastolic blood pressure; HbA1c, glycated hemoglobin; HOMA-IR, homeostasis model assessment of insulin resistance; QUICKI, quantitative insulin sensitivity check index; TC, total cholesterol; TG, triglyceride; HDL-C, high density lipoprotein cholesterol; LDL-C, low density lipoprotein cholesterol; AST, aspartate aminotransferase; ALT, alanine aminotransferase; γ-GTP, gamma-glutamyl transpeptidase; hs-CRP, high-sensitivity C-reactive protein.

aP<0.05; bP<0.01.

Characteristic r
NGT Prediabetes
BMI, kg/m2 -0.164 -0.249a
WC, cm -0.244 -0.282a
HC, cm -0.168 -0.132
Waist-to-hip ratio -0.182 -0.321b
Total body fat, kg -0.255a 0.046
Visceral fat, kg -0.309a -0.306b
Total body fat ratio -0.110 -0.138
Visceral fat ratio -0.268a -0.326b
Total muscle, kg -0.311a -0.219
SBP, mm Hg 0.280 0.088
DBP, mm Hg -0.149 -0.112
Fasting glucose, mmol/L -0.004 -0.185
2-Hour glucose, mmol/L 0.035 -0.134
Fasting insulin, pmol/L -0.190 -0.090
2-Hour insulin, pmol/L -0.009 -0.242a
HbA1c, % -0.181 -0.015
HOMA-IR index -0.184 -0.110
QUICKI 0.153 0.175
TC, mmol/L 0.117 -0.080
TG, mmol/L -0.355b 0.013
HDL-C, mmol/L 0.323a 0.038
LDL-C, mmol/L 0.125 -0.139
AST, U/L -0.049 0.047
ALT, U/L -0.308a -0.158
γ-GTP, U/L -0.229 -0.154
hs-CRP, mg/dL -0.211 -0.185
Ferritin, µg/L 0.162 -0.034


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