Insulin, C-Peptide, and Leptin Concentrations Predict Increased Visceral Adiposity at 5- and 10-Year Follow-Ups in Nondiabetic Japanese Amer
http://www.100md.com
糖尿病学杂志 2005年第4期
1 Division of Metabolism, Endocrinology and Nutrition, Department of Medicine, VA Puget Sound Health Care System and Harborview Medical Center, University of Washington, Seattle, Washington
2 Department of Medicine, University of Washington, Seattle, Washington
3 Department of Anthropology, University of Washington, Seattle, Washington
4 Research and Development Service, VA Puget Sound Health Care System, Seattle, Washington
5 Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington
ABSTRACT
We prospectively examined the relationship between leptin and markers of insulin resistance and secretion and future visceral adipose tissue accumulation. In this study, 518 nondiabetic Japanese-American men and women underwent the following measurements at baseline and at 5- and 10-year follow-ups: plasma glucose and insulin measured after an overnight fast and during a 75-g oral glucose tolerance test, insulin secretion ratio (ISR) [(30-min insulin eC fasting insulin)/30-min glucose], fasting C-peptide levels, plasma leptin (baseline only), and fat areas (intra-abdominal and subcutaneous) measured by computed tomography. Predictors of future intra-abdominal fat (IAF) were determined using multiple linear regression. Fasting insulin and C-peptide levels at baseline were significantly associated with IAF area at 5 years (coefficient = 0.041, P = 0.001 and coefficient = 1.283, P < 0.001, respectively) and 10 years (coefficient = 0.031, P = 0.020 and coefficient = 0.221, P = 0.035, respectively). ISR was not significantly associated with IAF at 5 or 10 years. Leptin level at baseline was positively associated with IAF at 5 years (coefficient = 0.055, P = 0.002) and 10 years (coefficient = 0.059, P = 0.003). In conclusion, higher levels of fasting insulin, C-peptide, and circulating leptin level predicted visceral fat accumulation independent from subcutaneous fat accumulation in nondiabetic Japanese-American men and women in both short-term (5 years) and long-term (10 years) follow-up.
Visceral adiposity plays an important role in the development of type 2 diabetes and metabolic syndrome (1,2). Its association with insulin resistance and hyperinsulinemia is particularly strong as demonstrated by several studies (3eC5). Imaging techniques such as computed tomography (CT) and magnetic resonance imaging allow the differentiation between accumulation of intra-abdominal (visceral) and subcutaneous abdominal fat, which may have distinct impacts on glucose and lipoprotein metabolism. Several analyses have shown that the effect of visceral fat on glucose tolerance is independent from total adiposity and subcutaneous fat (SCF) depots (6,7). Yet little is known about the cause and effect association between the two.
Obesity, genetic susceptibility, aging, and male sex were found to be associated with increased visceral fat accumulation (8eC10). Despite having lower average BMI than whites, Asian women have a higher degree of central adiposity for a given BMI (11), which confers an increased risk for metabolic syndrome, type 2 diabetes, and cardiovascular disease (1,12,13).
Leptin, a product of the obesity (ob) gene, is an adipocyte-derived peptide hormone (14). It regulates body weight through binding to receptors in the hypothalamus and regulates caloric intake and energy expenditure (15,16). In general, plasma leptin levels correlate positively with fat mass with most obese subjects having elevated leptin levels. Chessler et al. (17) have demonstrated in Japanese Americans that relatively increased plasma leptin levels are associated with greater subsequent gains in weight and total adiposity. However, regional fat area change over time was not examined independently from that of total fat areas in this study.
We previously demonstrated in a prospective study of 137 Japanese-American men that greater insulin resistance, represented by higher fasting insulin and C-peptide levels, and reduced insulin secretion, measured by stimulated incremental insulin response, predicted a positive change in intra-abdominal fat (IAF) accumulation over 5 years (18). We have since completed a 10-year follow-up of these 137 subjects and have 5- and 10-year follow-up data on additional male and female subjects, including plasma leptin levels at baseline. This report describes the association between IAF accumulation at 5- and 10-year follow-ups in relation to earlier measurements of fasting and stimulated insulin, C-peptide, and plasma leptin levels.
RESEARCH DESIGN AND METHODS
The study population consisted of 288 second-generation (Nisei; age 61.8 ± 5.9 [mean ± SD] years) and 230 third-generation (Sansei; age 40.1 ± 4.2 years) nondiabetic Japanese-American men and women enrolled in the Japanese-American Community Diabetes Study between 1983 and 1988. Details about selection and recruitment of the sample population have been described previously (19). In brief, subjects were chosen from volunteers and were representative of Japanese Americans in King County, Washington, with regard to age, residence, and parental immigration pattern. All subjects were of 100% Japanese ancestry. Nisei men returned for follow-up examinations 5 and 10eC11 years after a baseline evaluation. Nisei women and Sansei men and women returned at 6 and 10eC11 years after a baseline evaluation. Of the original 518 subjects, 465 (90%) completed the 5-year and 415 (80%) completed the 10-year follow-up evaluation.
All evaluations were performed at the General Clinical Research Center, University of Washington, using a protocol approved by the University of Washington Human Subjects Review Committee. Signed informed consent was obtained from all participants. A 75-g oral glucose tolerance test performed in the morning after a 10-h overnight fast was used to classify all subjects as having normal glucose tolerance (NGT), impaired glucose tolerance (IGT), or type 2 diabetes on the basis of the American Diabetes Association 1997 criteria (20). Diabetes was diagnosed if subjects reported a history of this condition and were taking oral hypoglycemic medication or insulin, if the fasting plasma glucose level was 126 mg/dl (7.0 mmol/l), or if the 2-h value was 200 mg/dl (11.1 mmol/l). Subjects with a fasting plasma glucose level <126 mg/dl (7.0 mmol/l) but a 2-h value from 140 mg/dl (7.8 mmol/l) to 199 mg/dl (11.1mmol/l) were defined as having IGT.
Serum glucose was assayed by an automated glucose oxidase method at 0, 30, and 120 min during the oral glucose tolerance test. Plasma insulin and C-peptide levels were measured by radioimmunoassay as previously described (18). The insulin secretion ratio (ISR) was calculated as (30- to 0-min plasma insulin)/30-min glucose, which correlates well with direct measures of stimulated insulin secretion (21,22). Leptin measurements were obtained from frozen plasma of the 409 subjects who completed the 5-year follow-up. Plasma leptin levels were determined in duplicate using a radioimmunoassay kit (Linco Research, St. Charles, MO) (23). Plasma from fasting morning blood samples (7:30eC8:30 A.M.) was stored at eC80°C and thawed just before use for leptin measurement.
Body regional fat distribution was quantified by CT (24,25). Single 10-mm slices of the thorax on inspiration at the level of the nipples, the abdomen at the level of the umbilicus, and the mid-thigh at a level halfway between the greater trochanter and the superior margin of the patella were analyzed for cross-sectional area of adipose tissue (centimeters squared). IAF was measured using the transversalis fascia as the outer boundary at the umbilicus level. Total SCF area equaled the sum of the SCF areas from the thorax, abdomen, and midthigh. BMI was computed as weight (kilograms) divided by height (meters) squared.
Subjects were questioned regarding cigarette smoking status, amount smoked per day, duration of smoking in years, average daily consumption of alcoholic beverages, and weekly work and recreational activity levels.
Statistical analysis.
Paired and unpaired t tests were used to compare mean values. A univariate linear regression model was used to estimate the association between baseline and future IAF. Multiple linear regression analyses was used to model IAF measured at follow-up as a function of other variables of interest, such as fasting insulin, C-peptide, ISR, or leptin. Because insulin and C-peptide are highly correlated, they were entered into separate regression models. Leptin models included SCF changes and fasting insulin level in addition to baseline IAF, age, and sex due to the reported associations between this adipose depot and plasma leptin (4,26,27) and plasma insulin levels (27eC29). Because SCF would be expected to increase in absolute terms by a greater degree than IAF, we performed adjustments for changes in SCF in determining predictors of IAF accumulation in Tables 3 and 4. This adjustment also permits assessment of changes in IAF in relation to predictors independent of changes in SCF. Models that included ISR were adjusted for fasting insulin level, because a significant association exists between fasting insulin level and insulin secretion (30).
When used as the dependent variable, IAF underwent square root transformation to satisfy the normality assumptions. To examine whether observed associations varied by IGT status, first-degree interactions between IGT status and main effects of interest were tested. Analysis of residuals was performed to test for model fit and regression assumptions. All P values reported are two-sided. Mean values were reported as means ± SE unless specified. All statistics were calculated using Stata version 8.0 (College Station, TX).
RESULTS
A total of 518 subjects (age 52.2 ± 12.0 years [mean ± SE]; 51.0% males) were eligible for this study. Fifty-three subjects were lost to follow-up after 5 years and another 50 subjects were lost to follow-up after 10 years due to death or illness, inability to locate the subjects, or withdrawal from the study.
Baseline characteristics of the study subjects grouped by follow-up status are shown in Table 1. Subjects who completed 5- or 10-year follow-up had similar body composition and metabolic parameters compared with all subjects eligible for the study, as well as subjects who were lost to follow-up at either 5 or 10 years (P > 0.05). Serum leptin concentrations exhibited the expected sexual dimorphism in our study population: mean baseline plasma leptin level for men was 4.0 ± 2.7 (mean ± SD) pmol/l and 11.6 ± 7.3 pmol/l for women. A total of 211 (40.7%) subjects had IGT at baseline. Subjects with IGT were older; had higher BMI, IAF, and SCF areas; had higher fasting insulin, C-peptide, and leptin levels (P < 0.05); and had lower ISR (P < 0.05) compared with those who had NGT. Sixty-two subjects met the 1997 American Diabetes Association diagnostic criteria for diabetes at the 5-year follow-up and an additional 64 subjects met the diagnostic criteria at the 10-year follow-up.
Table 2 lists the changes in weight and adipose tissue measurements over the 10-year study periods. Average baseline BMI for the study population was 24.1 ± 3.2 (mean ± SD) kg/m2, with men having a higher mean BMI (25.2 ± 3.0 kg/m2) than women (22.9 ± 3.1 kg/m2). Of all of the CT fat areas, the largest increase occurred in IAF area from baseline to 5 years (13%). Despite the larger absolute increase in SCF area over time, the relative increase in fat area was larger for IAF compared with SCF. Most of the weight and adipose tissue area increase occurred during the first 5 years of follow-up. Only subjects who had both 5- and 10-year follow-up data were included in the analysis.
In separate analyses using baseline IAF to predict IAF at follow-up, IAF at baseline was a strong predictor of future IAF. The correlation coefficients between baseline IAF and IAF measured at 5 and 10 years were r = 0.82 and r = 0.76, respectively (data not shown). Correlations between baseline IAF and fasting insulin and C-peptide are moderate (0.314eC0.415), between IAF and leptin are weak (0.140), and between IAF and ISR are close to zero (0.049).
Multiple linear regression analysis was used to estimate the associations between fasting insulin, ISR, C-peptide, or leptin and later measurements of IAF while adjusting for baseline IAF, age, sex, and SCF area change. Significant positive associations were found between baseline fasting insulin, C-peptide, leptin, and IAF at 5 years (Table 3). No significant association was seen between ISR and IAF.
Similar analysis was performed to evaluate the association between insulin measures obtained at 5 years and IAF measured at 10 years (results not shown). We again observed positive and significant associations between C-peptide and IAF ( = 0.192, P = 0.005) after adjusting for SCF change, sex, and age. The association between fasting insulin and IAF had a trend toward significance (P = 0.064). The association between ISR and IAF was not statistically significant. Leptin analyses were not performed due to the unavailability of these measurements at 5-year follow-up.
Analyses of baseline measurements in relation to IAF measured at the 10- to 11-year follow-up are shown in Table 4. We observed positive significant associations between baseline fasting insulin, C-peptide, plasma leptin, and 10-year IAF (P = 0.020, P = 0.035, and P = 0.003, respectively). ISR was not significantly associated with IAF at 10 years in these models.
First-order interactions between IGT status and main effects and sex and main effects were tested in all models but were not found to be statistically significant, indicating that the associations of interest did not differ significantly on the basis of IGT status or sex. BMI change was inserted in all leptin models instead of SCF change but did not have any significant impact on the association between baseline leptin level and future IAF (result not shown). Adjustment for BMI change in model 1 in Table 3 did, however, reveal significant associations between future IAF and both fasting insulin and ISR. The potential for effect modification by sex on the association between leptin and IAF was tested by inserting an interaction term (leptinsex) in the multivariate regression models. No significant interaction between leptin and sex was detected using this method ( = 0.027, P = 0.52 for the interaction variable in the 0- to 5-year model and = eC0.0002, P = 0.996 in the 0- to 10-year model). The results of the models shown in Tables 3 and 4 did not substantially change when smoking status, amount smoked per week, amount of alcohol consumed per week, and weekly energy expenditure were entered into these models as additional covariates (data not shown).
DISCUSSION
These results confirm that associations exist between future IAF accumulation in relation to fasting insulin and C-peptide levels and insulin secretion. We found that fasting insulin and C-peptide levels were positively associated with IAF accumulation over 5 and 10 years. These associations appeared to be independent of SCF change. No significant association was found between ISR and later IAF accumulation in models adjusted for SCF change. These results extend our previous findings in elderly Japanese-American men of associations between IAF accumulation at 5-year follow-up in relation to fasting insulin and C-peptide levels and insulin secretion to younger men and both younger and older women. In addition, these results show an association between higher leptin level and future IAF accumulation independent of either change in BMI or SCF over the same time frame. Thus, leptin appears related to gain not only in adiposity but also site of adipose deposition.
The mechanism responsible for the increased IAF in Japanese Americans cannot be ascertained from the results of this study. Higher fasting insulin and C-peptide levels seemed to predict future IAF independent of SCF accumulation in this population. Baseline IAF area remains the best predictor for future IAF accumulation in all of our prediction models. Although the percentage change in IAF area over the study period was greater than that in SCF as shown in Table 2, the absolute change in SCF may still be much larger depending on the relative size of the adipose tissue depots. The correlation analysis suggests that the biochemical measures used as predictors for IAF accumulation did not have strong associations with IAF at baseline. Therefore, they are not likely to be surrogate markers for IAF in predicting future IAF gain. The distribution of IAF proportionate to the overall adiposity in this population is probably genetically determined (31). The reason for the stronger association between C-peptide with IAF accumulation compared with fasting insulin and ISR is unclear. Fasting C-peptide level may be more strongly associated with insulin sensitivity than fasting insulin levels in the Japanese-American population (32). C-peptide does not undergo hepatic extraction like insulin and therefore may be less likely to be affected by changes in hepatic insulin extraction related to adiposity and insulin sensitivity (33).
Another key finding of our study was that the plasma leptin level measured at baseline was positively associated with IAF accumulation at 5- and 10-year follow-ups. This association remained significant after adjusting for total SCF or BMI change and was not modified by sex. Plasma leptin concentration has been found to be associated with female sex, total and SCF volume in population as well as cohort studies (34). It has been postulated as a sensor of fat mass and a hormonal signal that exerts its effect on energy regulation through its hypothalamic receptor (15,16). Because the adipocyte is the only source of ob gene products, serum leptin level has a strong positive association with the amount of body fat and adipocyte leptin mRNA in humans as in rodents (35eC37). Several studies have examined serum leptin level and future weight gain, but few have examined change in regional adiposity (17,38,39). Our study demonstrated that higher leptin level predicts future IAF accumulation as measured by CT independent from total and subcutaneous adiposity or fasting insulin levels or from concurrent increase in BMI or SCF.
Despite the difference in mean leptin levels between males and females (11.6 vs. 4 pmol/l), we did not observe differences in the association between leptin levels and IAF accumulation by sex as seen in nonsignificant interaction terms in regression models between leptin and sex as predictors of future IAF accumulation. It is possible that such a difference, if it exists, may have been detectable with a larger sample size.
We observed stronger associations between fasting insulin or C-peptide and IAF at 5-year follow-up than 10-year follow-up, but similar magnitude associations were observed at both follow-up intervals for the associations between leptin (or SCF change) and IAF. The more consistent leptin effect may be due to smaller variation in leptin levels over time compared with fasting insulin and C-peptide levels, a phenomenon that has been referred to as "regression dilution" (40).
One plausible explanation of our findings may be that our baseline data may not represent the "real" baseline measurements of metabolic parameters for each individual at the onset of our study. It is possible that we obtained our measurements on study subjects when they already had some weight gain and had already begun the journey along the path to body fat accumulation, insulin resistance, and eventually, diabetes. Thus, the baseline hormone levels associated with later visceral fat accumulation may represent markers for an underlying unidentified cause or causes of this outcome. We also propose the hypothesis that insulin and leptin resistance result in both increased baseline levels of insulin and leptin in the periphery and a diminished satiety signal in the central nervous system. The diminished satiety signal would cause a slight positive energy balance that, over time, would lead to obesity and increased IAF. In addition, other adipokines such as adiponectin may also play a role in the associations that we observed (41,42). Plasma adiponectin levels were not measured for these subjects. Future studies are needed to provide a better understanding of the causal relationships between metabolic parameters and adipose tissue accumulation.
Several prospective studies have examined the association between insulin resistance, insulin secretion, and weight gain and/or IAF accumulation. A study of middle-aged Caucasians with NGT found that reduced first-phase insulin secretion was associated with increased risk of future weight gain, whereas fasting hyperinsulinemia was associated with increased waist-to-hip ratio over time in women (43). Researchers reported that fasting hyperinsulinemia was a predictor of increased weight gain and overall future obesity among Pima Indian children (44). In a prospective study of nondiabetic Asian Indian, Creole, and Chinese Mauritians, insulin resistance predicted weight gain but not waist-to-hip ratio change in Chinese men independently of baseline age and BMI (45). None of the above-mentioned studies used CT scan as a measurement of IAF area. Other studies have shown no ability of hyperinsulinemia to predict weight gain in both children (46) and adults. Three longitudinal studies of Pima Indians and of Hispanic and non-Hispanic whites (47eC49) found markers of insulin resistance (euglycemic clamp or fasting insulin) among nondiabetic subjects to be inversely associated with the rate of weight gain. Researchers have also shown that lower insulin secretion predicted future weight gain in a prospective study of young, obese Pima Indians (50). Very few studies have specifically examined the temporal relationship between insulin resistance, insulin secretion, and future IAF change using a measurement of regional adiposity obtained from imaging technology.
There are several limitations to our study. We used surrogate markers such as fasting insulin and C-peptide levels to measure insulin resistance instead of the more quantitative approaches such as the hyperinsulinemic-euglycemic clamp or minimal model (51). This can potentially introduce measurement error. If the error in these surrogate measures was random, we would be more likely to underestimate the true association between insulin resistance, insulin secretion, and future IAF accumulation. Visceral fat volume was measured using single-slice CT imaging at the umbilicus level, but this method has been shown to have a high correlation with directly ascertained total visceral fat volume by CT or magnetic resonance imaging (52,53). Our study subjects were middle-aged, nonobese, nondiabetic Japanese Americans at high risk for type 2 diabetes. The ability to generalize our study findings to other populations is unclear. We cannot exclude the possibility of residual confounding causing bias in our results due to unmeasured or inaccurately measured covariates.
In conclusion, the presence of greater insulin resistance as reflected by higher fasting insulin and C-peptide levels was positively associated with future IAF accumulation in initially nondiabetic Japanese Americans. These associations were present in both shorter (5-year) and longer (10-year) follow-up. Higher plasma leptin level also predicted increased future visceral adiposity. The above associations were independent from intra-abdominal adiposity at baseline and change in subcutaneous adiposity over time. These results suggest that the metabolic changes associated with visceral fat may precede its accumulation or act in a positive feedback manner to perpetuate or exacerbate this condition. If these results represent causal associations, they would therefore suggest that interventions that target insulin resistance and leptin signaling and/or resistance might result in lower IAF accumulation. Further confirmation of these findings is needed from studies that measure the visceral adipose tissue depot using direct imaging technology over time.
ACKNOWLEDGMENTS
This work was supported by National Institutes of Health Grants DK-55460 and DK-02860. We thank Pam Yang at the University of Washington for her technical assistance.
CT, computed tomography; IAF, intra-abdominal fat; IGT, impaired glucose tolerance; ISR, insulin secretion ratio; NGT, normal glucose tolerance; SCF, subcutaneous fat
REFERENCES
Boyko EJ, Fujimoto WY, Leonetti DL, Newell-Morris L: Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans. Diabetes Care23 :465 eC471,2000
Bjorntorp P: Abdominal obesity and the development of noninsulin-dependent diabetes mellitus. Diabetes Metab Rev4 :615 eC622,1988
Despres JP: Abdominal obesity as important component of insulin-resistance syndrome. Nutrition9 :452 eC459,1993
Cnop M, Landchild MJ, Vidal J, Havel PJ, Knowles NG, Carr DR, Wang F, Hull RL, Boyko EJ, Retzlaff BM, Walden CE, Knopp RH, Kahn SE: The concurrent accumulation of intra-abdominal and subcutaneous fat explains the association between insulin resistance and plasma leptin concentrations: distinct metabolic effects of two fat compartments. Diabetes51 :1005 eC1015,2002
Carey DG, Jenkins AB, Campbell LV, Freund J, Chisholm DJ: Abdominal fat and insulin resistance in normal and overweight women: direct measurements reveal a strong relationship in subjects at both low and high risk of NIDDM. Diabetes45 :633 eC638,1996
Pouliot MC, Despres JP, Nadeau A, Moorjani S, Prud’Homme D, Lupien PJ, Tremblay A, Bouchard C: Visceral obesity in men: associations with glucose tolerance, plasma insulin, and lipoprotein levels. Diabetes41 :826 eC834,1992
Despres JP, Nadeau A, Tremblay A, Ferland M, Moorjani S, Lupien PJ, Theriault G, Pinault S, Bouchard C: Role of deep abdominal fat in the association between regional adipose tissue distribution and glucose tolerance in obese women. Diabetes38 :304 eC309,1989
Yamashita S, Nakamura T, Shimomura I, Nishida M, Yoshida S, Kotani K, Kameda-Takemuara K, Tokunaga K, Matsuzawa Y: Insulin resistance and body fat distribution. Diabetes Care19 :287 eC291,1996
Bjorntorp P: The regulation of adipose tissue distribution in humans. Int J Obes Relat Metab Disord20 :291 eC302,1996
Bouchard C, Despres JP, Mauriege P: Genetic and nongenetic determinants of regional fat distribution. Endocr Rev14 :72 eC93,1993
Park YW, Allison DB, Heymsfield SB, Gallagher D: Larger amounts of visceral adipose tissue in Asian Americans. Obes Res9 :381 eC387,2001
Fujimoto WY, Bergstrom RW, Boyko EJ, Chen KW, Leonetti DL, Newell-Morris L, Shofer JB, Wahl PW: Visceral adiposity and incident coronary heart disease in Japanese-American men: the 10-year follow-up results of the Seattle Japanese-American Community Diabetes Study. Diabetes Care22 :1808 eC1812,1999
Hayashi T, Boyko EJ, Leonetti DL, McNeely MJ, Newell-Morris L, Kahn SE, Fujimoto WY: Visceral adiposity and the risk of impaired glucose tolerance: a prospective study among Japanese Americans. Diabetes Care26 :650 eC655,2003
Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM: Positional cloning of the mouse obese gene and its human homologue. Nature372 :425 eC432,1994
Campfield LA, Smith FJ, Guisez Y, Devos R, Burn P: Recombinant mouse OB protein: evidence for a peripheral signal linking adiposity and central neural networks. Science269 :546 eC549,1995
Schwartz MW, Seeley RJ, Campfield LA, Burn P, Baskin DG: Identification of targets of leptin action in rat hypothalamus. J Clin Invest98 :1101 eC1106,1996
Chessler SD, Fujimoto WY, Shofer JB, Boyko EJ, Weigle DS: Increased plasma leptin levels are associated with fat accumulation in Japanese Americans. Diabetes47 :239 eC243,1998
Boyko EJ, Leonetti DL, Bergstrom RW, Newell-Morris L, Fujimoto WY: Low insulin secretion and high fasting insulin and C-peptide levels predict increased visceral adiposity: 5-year follow-up among initially nondiabetic Japanese-American men. Diabetes45 :1010 eC1015,1996
Fujimoto WY, Leonetti DL, Kinyoun JL, Newell-Morris L, Shuman WP, Stolov WC, Wahl PW: Prevalence of diabetes mellitus and impaired glucose tolerance among second-generation Japanese-American men. Diabetes36 :721 eC729,1987
Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care20 :1183 eC1197,1997
Phillips DI, Clark PM, Hales CN, Osmond C: Understanding oral glucose tolerance: comparison of glucose or insulin measurements during the oral glucose tolerance test with specific measurements of insulin resistance and insulin secretion. Diabet Med11 :286 eC292,1994
Wareham NJ, Phillips DI, Byrne CD, Hales CN: The 30 minute insulin incremental response in an oral glucose tolerance test as a measure of insulin secretion. Diabet Med12 :931 ,1995
Ma Z, Gingerich RL, Santiago JV, Klein S, Smith CH, Landt M: Radioimmunoassay of leptin in human plasma. Clin Chem42 :942 eC946,1996
Borkan GA, Gerzof SG, Robbins AH, Hults DE, Silbert CK, Silbert JE: Assessment of abdominal fat content by computed tomography. Am J Clin Nutr36 :172 eC177,1982
Shuman WP, Morris LL, Leonetti DL, Wahl PW, Moceri VM, Moss AA, Fujimoto WY: Abnormal body fat distribution detected by computed tomography in diabetic men. Invest Radiol21 :483 eC487,1986
Masuzaki H, Ogawa Y, Isse N, Satoh N, Okazaki T, Shigemoto M, Mori K, Tamura N, Hosoda K, Yoshimasa Y, et al.: Human obese gene expression. Adipocyte-specific expression and regional differences in the adipose tissue. Diabetes44 :855 eC858,1995
Muzumdar R, Ma X, Yang X, Atzmon G, Bernstein J, Karkanias G, Barzilai N: Physiologic effect of leptin on insulin secretion is mediated mainly through central mechanisms. FASEB J17 :1130 eC1132,2003
Larsson H, Elmstahl S, Ahren B: Plasma leptin levels correlate to islet function independently of body fat in postmenopausal women. Diabetes45 :1580 eC1584,1996
Ahren B, Havel PJ: Leptin inhibits insulin secretion induced by cellular cAMP in a pancreatic B cell line (INS-1 cells). Am J Physiol277 :R959 eCR966,1999
Boyko EJ, Leonetti DL, Bergstrom RW, Fujimoto WY: Fasting insulin level underestimates risk of non-insulin-dependent diabetes mellitus due to confounding by insulin secretion. Am J Epidemiol145 :18 eC23,1997
Fujimoto WY, Bergstrom RW, Boyko EJ, Leonetti DL, Newell-Morris LL, Wahl PW: Susceptibility to development of central adiposity among populations. Obes Res3 (Suppl. 2) :179S eC186S,1995
Bergstrom RW, Newell-Morris LL, Leonetti DL, Shuman WP, Wahl PW, Fujimoto WY: Association of elevated fasting C-peptide level and increased intra-abdominal fat distribution with development of NIDDM in Japanese-American men. Diabetes39 :104 eC111,1990
Peiris AN, Mueller RA, Smith GA, Struve MF, Kissebah AH: Splanchnic insulin metabolism in obesity. Influence of body fat distribution. J Clin Invest78 :1648 eC1657,1986
Ruhl CE, Everhart JE: Leptin concentrations in the United States: relations with demographic and anthropometric measures. Am J Clin Nutr74 :295 eC301,2001
Zhang Y, Guo KY, Diaz PA, Heo M, Leibel RL: Determinants of leptin gene expression in fat depots of lean mice. Am J Physiol Regul Integr Comp Physiol282 :R226 eCR234,2002
Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR, Ohannesian JP, Marco CC, McKee LJ, Bauer TL: Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med334 :292 eC295,1996
Montague CT, Prins JB, Sanders L, Digby JE, O’Rahilly S: Depot- and sex-specific differences in human leptin mRNA expression: implications for the control of regional fat distribution. Diabetes46 :342 eC347,1997
Chu NF, Spiegelman D, Yu J, Rifai N, Hotamisligil GS, Rimm EB: Plasma leptin concentrations and four-year weight gain among US men. Int J Obes Relat Metab Disord25 :346 eC353,2001
Savoye M, Dziura J, Castle J, DiPietro L, Tamborlane WV, Caprio S: Importance of plasma leptin in predicting future weight gain in obese children: a two-and-a-half-year longitudinal study. Int J Obes Relat Metab Disord26 :942 eC946,2002
Clarke R, Shipley M, Lewington S, Youngman L, Collins R, Marmot M, Peto R: Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies. Am J Epidemiol150 :341 eC353,1999
Cnop M, Havel PJ, Utzschneider KM, Carr DB, Sinha MK, Boyko EJ, Retzlaff BM, Knopp RH, Brunzell JD, Kahn SE: Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia46 :459 eC469,2003
Ryan AS, Berman DM, Nicklas BJ, Sinha M, Gingerich RL, Meneilly GS, Egan JM, Elahi D: Plasma adiponectin and leptin levels, body composition, and glucose utilization in adult women with wide ranges of age and obesity. Diabetes Care26 :2383 eC2388,2003
Gould AJ, Williams DE, Byrne CD, Hales CN, Wareham NJ: Prospective cohort study of the relationship of markers of insulin resistance and secretion with weight gain and changes in regional adiposity. Int J Obes Relat Metab Disord23 :1256 eC1261,1999
Odeleye OE, de Courten M, Pettitt DJ, Ravussin E: Fasting hyperinsulinemia is a predictor of increased body weight gain and obesity in Pima Indian children. Diabetes46 :1341 eC1345,1997
Hodge AM, Dowse GK, Alberti KG, Tuomilehto J, Gareeboo H, Zimmet PZ: Relationship of insulin resistance to weight gain in nondiabetic Asian Indian, Creole, and Chinese Mauritians: Mauritius Non-communicable Disease Study Group. Metabolism45 :627 eC633,1996
Travers SH, Jeffers BW, Eckel RH: Insulin resistance during puberty and future fat accumulation. J Clin Endocrinol Metab87 :3814 eC3818,2002
Hoag S, Marshall JA, Jones RH, Hamman RF: High fasting insulin levels associated with lower rates of weight gain in persons with normal glucose tolerance: the San Luis Valley Diabetes Study. Int J Obes Relat Metab Disord19 :175 eC180,1995
Swinburn BA, Nyomba BL, Saad MF, Zurlo F, Raz I, Knowler WC, Lillioja S, Bogardus C, Ravussin E: Insulin resistance associated with lower rates of weight gain in Pima Indians. J Clin Invest88 :168 eC173,1991
Valdez R, Mitchell BD, Haffner SM, Hazuda HP, Morales PA, Monterrosa A, Stern MP: Predictors of weight change in a bi-ethnic population: the San Antonio Heart Study. Int J Obes Relat Metab Disord18 :85 eC91,1994
Schwartz MW, Boyko EJ, Kahn SE, Ravussin E, Bogardus C: Reduced insulin secretion: an independent predictor of body weight gain. J Clin Endocrinol Metab80 :1571 eC1576,1995
DeFronzo RA, Tobin JD, Andres R: Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol237 :E214 eCE223,1979
Han TS, Kelly IE, Walsh K, Greene RM, Lean ME: Relationship between volumes and areas from single transverse scans of intra-abdominal fat measured by magnetic resonance imaging. Int J Obes Relat Metab Disord21 :1161 eC1166,1997
Schoen RE, Thaete FL, Sankey SS, Weissfeld JL, Kuller LH: Sagittal diameter in comparison with single slice CT as a predictor of total visceral adipose tissue volume. Int J Obes Relat Metab Disord22 :338 eC342,1998(Jenny Tong, Wilfred Y. Fu)
2 Department of Medicine, University of Washington, Seattle, Washington
3 Department of Anthropology, University of Washington, Seattle, Washington
4 Research and Development Service, VA Puget Sound Health Care System, Seattle, Washington
5 Epidemiologic Research and Information Center, VA Puget Sound Health Care System, Seattle, Washington
ABSTRACT
We prospectively examined the relationship between leptin and markers of insulin resistance and secretion and future visceral adipose tissue accumulation. In this study, 518 nondiabetic Japanese-American men and women underwent the following measurements at baseline and at 5- and 10-year follow-ups: plasma glucose and insulin measured after an overnight fast and during a 75-g oral glucose tolerance test, insulin secretion ratio (ISR) [(30-min insulin eC fasting insulin)/30-min glucose], fasting C-peptide levels, plasma leptin (baseline only), and fat areas (intra-abdominal and subcutaneous) measured by computed tomography. Predictors of future intra-abdominal fat (IAF) were determined using multiple linear regression. Fasting insulin and C-peptide levels at baseline were significantly associated with IAF area at 5 years (coefficient = 0.041, P = 0.001 and coefficient = 1.283, P < 0.001, respectively) and 10 years (coefficient = 0.031, P = 0.020 and coefficient = 0.221, P = 0.035, respectively). ISR was not significantly associated with IAF at 5 or 10 years. Leptin level at baseline was positively associated with IAF at 5 years (coefficient = 0.055, P = 0.002) and 10 years (coefficient = 0.059, P = 0.003). In conclusion, higher levels of fasting insulin, C-peptide, and circulating leptin level predicted visceral fat accumulation independent from subcutaneous fat accumulation in nondiabetic Japanese-American men and women in both short-term (5 years) and long-term (10 years) follow-up.
Visceral adiposity plays an important role in the development of type 2 diabetes and metabolic syndrome (1,2). Its association with insulin resistance and hyperinsulinemia is particularly strong as demonstrated by several studies (3eC5). Imaging techniques such as computed tomography (CT) and magnetic resonance imaging allow the differentiation between accumulation of intra-abdominal (visceral) and subcutaneous abdominal fat, which may have distinct impacts on glucose and lipoprotein metabolism. Several analyses have shown that the effect of visceral fat on glucose tolerance is independent from total adiposity and subcutaneous fat (SCF) depots (6,7). Yet little is known about the cause and effect association between the two.
Obesity, genetic susceptibility, aging, and male sex were found to be associated with increased visceral fat accumulation (8eC10). Despite having lower average BMI than whites, Asian women have a higher degree of central adiposity for a given BMI (11), which confers an increased risk for metabolic syndrome, type 2 diabetes, and cardiovascular disease (1,12,13).
Leptin, a product of the obesity (ob) gene, is an adipocyte-derived peptide hormone (14). It regulates body weight through binding to receptors in the hypothalamus and regulates caloric intake and energy expenditure (15,16). In general, plasma leptin levels correlate positively with fat mass with most obese subjects having elevated leptin levels. Chessler et al. (17) have demonstrated in Japanese Americans that relatively increased plasma leptin levels are associated with greater subsequent gains in weight and total adiposity. However, regional fat area change over time was not examined independently from that of total fat areas in this study.
We previously demonstrated in a prospective study of 137 Japanese-American men that greater insulin resistance, represented by higher fasting insulin and C-peptide levels, and reduced insulin secretion, measured by stimulated incremental insulin response, predicted a positive change in intra-abdominal fat (IAF) accumulation over 5 years (18). We have since completed a 10-year follow-up of these 137 subjects and have 5- and 10-year follow-up data on additional male and female subjects, including plasma leptin levels at baseline. This report describes the association between IAF accumulation at 5- and 10-year follow-ups in relation to earlier measurements of fasting and stimulated insulin, C-peptide, and plasma leptin levels.
RESEARCH DESIGN AND METHODS
The study population consisted of 288 second-generation (Nisei; age 61.8 ± 5.9 [mean ± SD] years) and 230 third-generation (Sansei; age 40.1 ± 4.2 years) nondiabetic Japanese-American men and women enrolled in the Japanese-American Community Diabetes Study between 1983 and 1988. Details about selection and recruitment of the sample population have been described previously (19). In brief, subjects were chosen from volunteers and were representative of Japanese Americans in King County, Washington, with regard to age, residence, and parental immigration pattern. All subjects were of 100% Japanese ancestry. Nisei men returned for follow-up examinations 5 and 10eC11 years after a baseline evaluation. Nisei women and Sansei men and women returned at 6 and 10eC11 years after a baseline evaluation. Of the original 518 subjects, 465 (90%) completed the 5-year and 415 (80%) completed the 10-year follow-up evaluation.
All evaluations were performed at the General Clinical Research Center, University of Washington, using a protocol approved by the University of Washington Human Subjects Review Committee. Signed informed consent was obtained from all participants. A 75-g oral glucose tolerance test performed in the morning after a 10-h overnight fast was used to classify all subjects as having normal glucose tolerance (NGT), impaired glucose tolerance (IGT), or type 2 diabetes on the basis of the American Diabetes Association 1997 criteria (20). Diabetes was diagnosed if subjects reported a history of this condition and were taking oral hypoglycemic medication or insulin, if the fasting plasma glucose level was 126 mg/dl (7.0 mmol/l), or if the 2-h value was 200 mg/dl (11.1 mmol/l). Subjects with a fasting plasma glucose level <126 mg/dl (7.0 mmol/l) but a 2-h value from 140 mg/dl (7.8 mmol/l) to 199 mg/dl (11.1mmol/l) were defined as having IGT.
Serum glucose was assayed by an automated glucose oxidase method at 0, 30, and 120 min during the oral glucose tolerance test. Plasma insulin and C-peptide levels were measured by radioimmunoassay as previously described (18). The insulin secretion ratio (ISR) was calculated as (30- to 0-min plasma insulin)/30-min glucose, which correlates well with direct measures of stimulated insulin secretion (21,22). Leptin measurements were obtained from frozen plasma of the 409 subjects who completed the 5-year follow-up. Plasma leptin levels were determined in duplicate using a radioimmunoassay kit (Linco Research, St. Charles, MO) (23). Plasma from fasting morning blood samples (7:30eC8:30 A.M.) was stored at eC80°C and thawed just before use for leptin measurement.
Body regional fat distribution was quantified by CT (24,25). Single 10-mm slices of the thorax on inspiration at the level of the nipples, the abdomen at the level of the umbilicus, and the mid-thigh at a level halfway between the greater trochanter and the superior margin of the patella were analyzed for cross-sectional area of adipose tissue (centimeters squared). IAF was measured using the transversalis fascia as the outer boundary at the umbilicus level. Total SCF area equaled the sum of the SCF areas from the thorax, abdomen, and midthigh. BMI was computed as weight (kilograms) divided by height (meters) squared.
Subjects were questioned regarding cigarette smoking status, amount smoked per day, duration of smoking in years, average daily consumption of alcoholic beverages, and weekly work and recreational activity levels.
Statistical analysis.
Paired and unpaired t tests were used to compare mean values. A univariate linear regression model was used to estimate the association between baseline and future IAF. Multiple linear regression analyses was used to model IAF measured at follow-up as a function of other variables of interest, such as fasting insulin, C-peptide, ISR, or leptin. Because insulin and C-peptide are highly correlated, they were entered into separate regression models. Leptin models included SCF changes and fasting insulin level in addition to baseline IAF, age, and sex due to the reported associations between this adipose depot and plasma leptin (4,26,27) and plasma insulin levels (27eC29). Because SCF would be expected to increase in absolute terms by a greater degree than IAF, we performed adjustments for changes in SCF in determining predictors of IAF accumulation in Tables 3 and 4. This adjustment also permits assessment of changes in IAF in relation to predictors independent of changes in SCF. Models that included ISR were adjusted for fasting insulin level, because a significant association exists between fasting insulin level and insulin secretion (30).
When used as the dependent variable, IAF underwent square root transformation to satisfy the normality assumptions. To examine whether observed associations varied by IGT status, first-degree interactions between IGT status and main effects of interest were tested. Analysis of residuals was performed to test for model fit and regression assumptions. All P values reported are two-sided. Mean values were reported as means ± SE unless specified. All statistics were calculated using Stata version 8.0 (College Station, TX).
RESULTS
A total of 518 subjects (age 52.2 ± 12.0 years [mean ± SE]; 51.0% males) were eligible for this study. Fifty-three subjects were lost to follow-up after 5 years and another 50 subjects were lost to follow-up after 10 years due to death or illness, inability to locate the subjects, or withdrawal from the study.
Baseline characteristics of the study subjects grouped by follow-up status are shown in Table 1. Subjects who completed 5- or 10-year follow-up had similar body composition and metabolic parameters compared with all subjects eligible for the study, as well as subjects who were lost to follow-up at either 5 or 10 years (P > 0.05). Serum leptin concentrations exhibited the expected sexual dimorphism in our study population: mean baseline plasma leptin level for men was 4.0 ± 2.7 (mean ± SD) pmol/l and 11.6 ± 7.3 pmol/l for women. A total of 211 (40.7%) subjects had IGT at baseline. Subjects with IGT were older; had higher BMI, IAF, and SCF areas; had higher fasting insulin, C-peptide, and leptin levels (P < 0.05); and had lower ISR (P < 0.05) compared with those who had NGT. Sixty-two subjects met the 1997 American Diabetes Association diagnostic criteria for diabetes at the 5-year follow-up and an additional 64 subjects met the diagnostic criteria at the 10-year follow-up.
Table 2 lists the changes in weight and adipose tissue measurements over the 10-year study periods. Average baseline BMI for the study population was 24.1 ± 3.2 (mean ± SD) kg/m2, with men having a higher mean BMI (25.2 ± 3.0 kg/m2) than women (22.9 ± 3.1 kg/m2). Of all of the CT fat areas, the largest increase occurred in IAF area from baseline to 5 years (13%). Despite the larger absolute increase in SCF area over time, the relative increase in fat area was larger for IAF compared with SCF. Most of the weight and adipose tissue area increase occurred during the first 5 years of follow-up. Only subjects who had both 5- and 10-year follow-up data were included in the analysis.
In separate analyses using baseline IAF to predict IAF at follow-up, IAF at baseline was a strong predictor of future IAF. The correlation coefficients between baseline IAF and IAF measured at 5 and 10 years were r = 0.82 and r = 0.76, respectively (data not shown). Correlations between baseline IAF and fasting insulin and C-peptide are moderate (0.314eC0.415), between IAF and leptin are weak (0.140), and between IAF and ISR are close to zero (0.049).
Multiple linear regression analysis was used to estimate the associations between fasting insulin, ISR, C-peptide, or leptin and later measurements of IAF while adjusting for baseline IAF, age, sex, and SCF area change. Significant positive associations were found between baseline fasting insulin, C-peptide, leptin, and IAF at 5 years (Table 3). No significant association was seen between ISR and IAF.
Similar analysis was performed to evaluate the association between insulin measures obtained at 5 years and IAF measured at 10 years (results not shown). We again observed positive and significant associations between C-peptide and IAF ( = 0.192, P = 0.005) after adjusting for SCF change, sex, and age. The association between fasting insulin and IAF had a trend toward significance (P = 0.064). The association between ISR and IAF was not statistically significant. Leptin analyses were not performed due to the unavailability of these measurements at 5-year follow-up.
Analyses of baseline measurements in relation to IAF measured at the 10- to 11-year follow-up are shown in Table 4. We observed positive significant associations between baseline fasting insulin, C-peptide, plasma leptin, and 10-year IAF (P = 0.020, P = 0.035, and P = 0.003, respectively). ISR was not significantly associated with IAF at 10 years in these models.
First-order interactions between IGT status and main effects and sex and main effects were tested in all models but were not found to be statistically significant, indicating that the associations of interest did not differ significantly on the basis of IGT status or sex. BMI change was inserted in all leptin models instead of SCF change but did not have any significant impact on the association between baseline leptin level and future IAF (result not shown). Adjustment for BMI change in model 1 in Table 3 did, however, reveal significant associations between future IAF and both fasting insulin and ISR. The potential for effect modification by sex on the association between leptin and IAF was tested by inserting an interaction term (leptinsex) in the multivariate regression models. No significant interaction between leptin and sex was detected using this method ( = 0.027, P = 0.52 for the interaction variable in the 0- to 5-year model and = eC0.0002, P = 0.996 in the 0- to 10-year model). The results of the models shown in Tables 3 and 4 did not substantially change when smoking status, amount smoked per week, amount of alcohol consumed per week, and weekly energy expenditure were entered into these models as additional covariates (data not shown).
DISCUSSION
These results confirm that associations exist between future IAF accumulation in relation to fasting insulin and C-peptide levels and insulin secretion. We found that fasting insulin and C-peptide levels were positively associated with IAF accumulation over 5 and 10 years. These associations appeared to be independent of SCF change. No significant association was found between ISR and later IAF accumulation in models adjusted for SCF change. These results extend our previous findings in elderly Japanese-American men of associations between IAF accumulation at 5-year follow-up in relation to fasting insulin and C-peptide levels and insulin secretion to younger men and both younger and older women. In addition, these results show an association between higher leptin level and future IAF accumulation independent of either change in BMI or SCF over the same time frame. Thus, leptin appears related to gain not only in adiposity but also site of adipose deposition.
The mechanism responsible for the increased IAF in Japanese Americans cannot be ascertained from the results of this study. Higher fasting insulin and C-peptide levels seemed to predict future IAF independent of SCF accumulation in this population. Baseline IAF area remains the best predictor for future IAF accumulation in all of our prediction models. Although the percentage change in IAF area over the study period was greater than that in SCF as shown in Table 2, the absolute change in SCF may still be much larger depending on the relative size of the adipose tissue depots. The correlation analysis suggests that the biochemical measures used as predictors for IAF accumulation did not have strong associations with IAF at baseline. Therefore, they are not likely to be surrogate markers for IAF in predicting future IAF gain. The distribution of IAF proportionate to the overall adiposity in this population is probably genetically determined (31). The reason for the stronger association between C-peptide with IAF accumulation compared with fasting insulin and ISR is unclear. Fasting C-peptide level may be more strongly associated with insulin sensitivity than fasting insulin levels in the Japanese-American population (32). C-peptide does not undergo hepatic extraction like insulin and therefore may be less likely to be affected by changes in hepatic insulin extraction related to adiposity and insulin sensitivity (33).
Another key finding of our study was that the plasma leptin level measured at baseline was positively associated with IAF accumulation at 5- and 10-year follow-ups. This association remained significant after adjusting for total SCF or BMI change and was not modified by sex. Plasma leptin concentration has been found to be associated with female sex, total and SCF volume in population as well as cohort studies (34). It has been postulated as a sensor of fat mass and a hormonal signal that exerts its effect on energy regulation through its hypothalamic receptor (15,16). Because the adipocyte is the only source of ob gene products, serum leptin level has a strong positive association with the amount of body fat and adipocyte leptin mRNA in humans as in rodents (35eC37). Several studies have examined serum leptin level and future weight gain, but few have examined change in regional adiposity (17,38,39). Our study demonstrated that higher leptin level predicts future IAF accumulation as measured by CT independent from total and subcutaneous adiposity or fasting insulin levels or from concurrent increase in BMI or SCF.
Despite the difference in mean leptin levels between males and females (11.6 vs. 4 pmol/l), we did not observe differences in the association between leptin levels and IAF accumulation by sex as seen in nonsignificant interaction terms in regression models between leptin and sex as predictors of future IAF accumulation. It is possible that such a difference, if it exists, may have been detectable with a larger sample size.
We observed stronger associations between fasting insulin or C-peptide and IAF at 5-year follow-up than 10-year follow-up, but similar magnitude associations were observed at both follow-up intervals for the associations between leptin (or SCF change) and IAF. The more consistent leptin effect may be due to smaller variation in leptin levels over time compared with fasting insulin and C-peptide levels, a phenomenon that has been referred to as "regression dilution" (40).
One plausible explanation of our findings may be that our baseline data may not represent the "real" baseline measurements of metabolic parameters for each individual at the onset of our study. It is possible that we obtained our measurements on study subjects when they already had some weight gain and had already begun the journey along the path to body fat accumulation, insulin resistance, and eventually, diabetes. Thus, the baseline hormone levels associated with later visceral fat accumulation may represent markers for an underlying unidentified cause or causes of this outcome. We also propose the hypothesis that insulin and leptin resistance result in both increased baseline levels of insulin and leptin in the periphery and a diminished satiety signal in the central nervous system. The diminished satiety signal would cause a slight positive energy balance that, over time, would lead to obesity and increased IAF. In addition, other adipokines such as adiponectin may also play a role in the associations that we observed (41,42). Plasma adiponectin levels were not measured for these subjects. Future studies are needed to provide a better understanding of the causal relationships between metabolic parameters and adipose tissue accumulation.
Several prospective studies have examined the association between insulin resistance, insulin secretion, and weight gain and/or IAF accumulation. A study of middle-aged Caucasians with NGT found that reduced first-phase insulin secretion was associated with increased risk of future weight gain, whereas fasting hyperinsulinemia was associated with increased waist-to-hip ratio over time in women (43). Researchers reported that fasting hyperinsulinemia was a predictor of increased weight gain and overall future obesity among Pima Indian children (44). In a prospective study of nondiabetic Asian Indian, Creole, and Chinese Mauritians, insulin resistance predicted weight gain but not waist-to-hip ratio change in Chinese men independently of baseline age and BMI (45). None of the above-mentioned studies used CT scan as a measurement of IAF area. Other studies have shown no ability of hyperinsulinemia to predict weight gain in both children (46) and adults. Three longitudinal studies of Pima Indians and of Hispanic and non-Hispanic whites (47eC49) found markers of insulin resistance (euglycemic clamp or fasting insulin) among nondiabetic subjects to be inversely associated with the rate of weight gain. Researchers have also shown that lower insulin secretion predicted future weight gain in a prospective study of young, obese Pima Indians (50). Very few studies have specifically examined the temporal relationship between insulin resistance, insulin secretion, and future IAF change using a measurement of regional adiposity obtained from imaging technology.
There are several limitations to our study. We used surrogate markers such as fasting insulin and C-peptide levels to measure insulin resistance instead of the more quantitative approaches such as the hyperinsulinemic-euglycemic clamp or minimal model (51). This can potentially introduce measurement error. If the error in these surrogate measures was random, we would be more likely to underestimate the true association between insulin resistance, insulin secretion, and future IAF accumulation. Visceral fat volume was measured using single-slice CT imaging at the umbilicus level, but this method has been shown to have a high correlation with directly ascertained total visceral fat volume by CT or magnetic resonance imaging (52,53). Our study subjects were middle-aged, nonobese, nondiabetic Japanese Americans at high risk for type 2 diabetes. The ability to generalize our study findings to other populations is unclear. We cannot exclude the possibility of residual confounding causing bias in our results due to unmeasured or inaccurately measured covariates.
In conclusion, the presence of greater insulin resistance as reflected by higher fasting insulin and C-peptide levels was positively associated with future IAF accumulation in initially nondiabetic Japanese Americans. These associations were present in both shorter (5-year) and longer (10-year) follow-up. Higher plasma leptin level also predicted increased future visceral adiposity. The above associations were independent from intra-abdominal adiposity at baseline and change in subcutaneous adiposity over time. These results suggest that the metabolic changes associated with visceral fat may precede its accumulation or act in a positive feedback manner to perpetuate or exacerbate this condition. If these results represent causal associations, they would therefore suggest that interventions that target insulin resistance and leptin signaling and/or resistance might result in lower IAF accumulation. Further confirmation of these findings is needed from studies that measure the visceral adipose tissue depot using direct imaging technology over time.
ACKNOWLEDGMENTS
This work was supported by National Institutes of Health Grants DK-55460 and DK-02860. We thank Pam Yang at the University of Washington for her technical assistance.
CT, computed tomography; IAF, intra-abdominal fat; IGT, impaired glucose tolerance; ISR, insulin secretion ratio; NGT, normal glucose tolerance; SCF, subcutaneous fat
REFERENCES
Boyko EJ, Fujimoto WY, Leonetti DL, Newell-Morris L: Visceral adiposity and risk of type 2 diabetes: a prospective study among Japanese Americans. Diabetes Care23 :465 eC471,2000
Bjorntorp P: Abdominal obesity and the development of noninsulin-dependent diabetes mellitus. Diabetes Metab Rev4 :615 eC622,1988
Despres JP: Abdominal obesity as important component of insulin-resistance syndrome. Nutrition9 :452 eC459,1993
Cnop M, Landchild MJ, Vidal J, Havel PJ, Knowles NG, Carr DR, Wang F, Hull RL, Boyko EJ, Retzlaff BM, Walden CE, Knopp RH, Kahn SE: The concurrent accumulation of intra-abdominal and subcutaneous fat explains the association between insulin resistance and plasma leptin concentrations: distinct metabolic effects of two fat compartments. Diabetes51 :1005 eC1015,2002
Carey DG, Jenkins AB, Campbell LV, Freund J, Chisholm DJ: Abdominal fat and insulin resistance in normal and overweight women: direct measurements reveal a strong relationship in subjects at both low and high risk of NIDDM. Diabetes45 :633 eC638,1996
Pouliot MC, Despres JP, Nadeau A, Moorjani S, Prud’Homme D, Lupien PJ, Tremblay A, Bouchard C: Visceral obesity in men: associations with glucose tolerance, plasma insulin, and lipoprotein levels. Diabetes41 :826 eC834,1992
Despres JP, Nadeau A, Tremblay A, Ferland M, Moorjani S, Lupien PJ, Theriault G, Pinault S, Bouchard C: Role of deep abdominal fat in the association between regional adipose tissue distribution and glucose tolerance in obese women. Diabetes38 :304 eC309,1989
Yamashita S, Nakamura T, Shimomura I, Nishida M, Yoshida S, Kotani K, Kameda-Takemuara K, Tokunaga K, Matsuzawa Y: Insulin resistance and body fat distribution. Diabetes Care19 :287 eC291,1996
Bjorntorp P: The regulation of adipose tissue distribution in humans. Int J Obes Relat Metab Disord20 :291 eC302,1996
Bouchard C, Despres JP, Mauriege P: Genetic and nongenetic determinants of regional fat distribution. Endocr Rev14 :72 eC93,1993
Park YW, Allison DB, Heymsfield SB, Gallagher D: Larger amounts of visceral adipose tissue in Asian Americans. Obes Res9 :381 eC387,2001
Fujimoto WY, Bergstrom RW, Boyko EJ, Chen KW, Leonetti DL, Newell-Morris L, Shofer JB, Wahl PW: Visceral adiposity and incident coronary heart disease in Japanese-American men: the 10-year follow-up results of the Seattle Japanese-American Community Diabetes Study. Diabetes Care22 :1808 eC1812,1999
Hayashi T, Boyko EJ, Leonetti DL, McNeely MJ, Newell-Morris L, Kahn SE, Fujimoto WY: Visceral adiposity and the risk of impaired glucose tolerance: a prospective study among Japanese Americans. Diabetes Care26 :650 eC655,2003
Zhang Y, Proenca R, Maffei M, Barone M, Leopold L, Friedman JM: Positional cloning of the mouse obese gene and its human homologue. Nature372 :425 eC432,1994
Campfield LA, Smith FJ, Guisez Y, Devos R, Burn P: Recombinant mouse OB protein: evidence for a peripheral signal linking adiposity and central neural networks. Science269 :546 eC549,1995
Schwartz MW, Seeley RJ, Campfield LA, Burn P, Baskin DG: Identification of targets of leptin action in rat hypothalamus. J Clin Invest98 :1101 eC1106,1996
Chessler SD, Fujimoto WY, Shofer JB, Boyko EJ, Weigle DS: Increased plasma leptin levels are associated with fat accumulation in Japanese Americans. Diabetes47 :239 eC243,1998
Boyko EJ, Leonetti DL, Bergstrom RW, Newell-Morris L, Fujimoto WY: Low insulin secretion and high fasting insulin and C-peptide levels predict increased visceral adiposity: 5-year follow-up among initially nondiabetic Japanese-American men. Diabetes45 :1010 eC1015,1996
Fujimoto WY, Leonetti DL, Kinyoun JL, Newell-Morris L, Shuman WP, Stolov WC, Wahl PW: Prevalence of diabetes mellitus and impaired glucose tolerance among second-generation Japanese-American men. Diabetes36 :721 eC729,1987
Report of the Expert Committee on the Diagnosis and Classification of Diabetes Mellitus. Diabetes Care20 :1183 eC1197,1997
Phillips DI, Clark PM, Hales CN, Osmond C: Understanding oral glucose tolerance: comparison of glucose or insulin measurements during the oral glucose tolerance test with specific measurements of insulin resistance and insulin secretion. Diabet Med11 :286 eC292,1994
Wareham NJ, Phillips DI, Byrne CD, Hales CN: The 30 minute insulin incremental response in an oral glucose tolerance test as a measure of insulin secretion. Diabet Med12 :931 ,1995
Ma Z, Gingerich RL, Santiago JV, Klein S, Smith CH, Landt M: Radioimmunoassay of leptin in human plasma. Clin Chem42 :942 eC946,1996
Borkan GA, Gerzof SG, Robbins AH, Hults DE, Silbert CK, Silbert JE: Assessment of abdominal fat content by computed tomography. Am J Clin Nutr36 :172 eC177,1982
Shuman WP, Morris LL, Leonetti DL, Wahl PW, Moceri VM, Moss AA, Fujimoto WY: Abnormal body fat distribution detected by computed tomography in diabetic men. Invest Radiol21 :483 eC487,1986
Masuzaki H, Ogawa Y, Isse N, Satoh N, Okazaki T, Shigemoto M, Mori K, Tamura N, Hosoda K, Yoshimasa Y, et al.: Human obese gene expression. Adipocyte-specific expression and regional differences in the adipose tissue. Diabetes44 :855 eC858,1995
Muzumdar R, Ma X, Yang X, Atzmon G, Bernstein J, Karkanias G, Barzilai N: Physiologic effect of leptin on insulin secretion is mediated mainly through central mechanisms. FASEB J17 :1130 eC1132,2003
Larsson H, Elmstahl S, Ahren B: Plasma leptin levels correlate to islet function independently of body fat in postmenopausal women. Diabetes45 :1580 eC1584,1996
Ahren B, Havel PJ: Leptin inhibits insulin secretion induced by cellular cAMP in a pancreatic B cell line (INS-1 cells). Am J Physiol277 :R959 eCR966,1999
Boyko EJ, Leonetti DL, Bergstrom RW, Fujimoto WY: Fasting insulin level underestimates risk of non-insulin-dependent diabetes mellitus due to confounding by insulin secretion. Am J Epidemiol145 :18 eC23,1997
Fujimoto WY, Bergstrom RW, Boyko EJ, Leonetti DL, Newell-Morris LL, Wahl PW: Susceptibility to development of central adiposity among populations. Obes Res3 (Suppl. 2) :179S eC186S,1995
Bergstrom RW, Newell-Morris LL, Leonetti DL, Shuman WP, Wahl PW, Fujimoto WY: Association of elevated fasting C-peptide level and increased intra-abdominal fat distribution with development of NIDDM in Japanese-American men. Diabetes39 :104 eC111,1990
Peiris AN, Mueller RA, Smith GA, Struve MF, Kissebah AH: Splanchnic insulin metabolism in obesity. Influence of body fat distribution. J Clin Invest78 :1648 eC1657,1986
Ruhl CE, Everhart JE: Leptin concentrations in the United States: relations with demographic and anthropometric measures. Am J Clin Nutr74 :295 eC301,2001
Zhang Y, Guo KY, Diaz PA, Heo M, Leibel RL: Determinants of leptin gene expression in fat depots of lean mice. Am J Physiol Regul Integr Comp Physiol282 :R226 eCR234,2002
Considine RV, Sinha MK, Heiman ML, Kriauciunas A, Stephens TW, Nyce MR, Ohannesian JP, Marco CC, McKee LJ, Bauer TL: Serum immunoreactive-leptin concentrations in normal-weight and obese humans. N Engl J Med334 :292 eC295,1996
Montague CT, Prins JB, Sanders L, Digby JE, O’Rahilly S: Depot- and sex-specific differences in human leptin mRNA expression: implications for the control of regional fat distribution. Diabetes46 :342 eC347,1997
Chu NF, Spiegelman D, Yu J, Rifai N, Hotamisligil GS, Rimm EB: Plasma leptin concentrations and four-year weight gain among US men. Int J Obes Relat Metab Disord25 :346 eC353,2001
Savoye M, Dziura J, Castle J, DiPietro L, Tamborlane WV, Caprio S: Importance of plasma leptin in predicting future weight gain in obese children: a two-and-a-half-year longitudinal study. Int J Obes Relat Metab Disord26 :942 eC946,2002
Clarke R, Shipley M, Lewington S, Youngman L, Collins R, Marmot M, Peto R: Underestimation of risk associations due to regression dilution in long-term follow-up of prospective studies. Am J Epidemiol150 :341 eC353,1999
Cnop M, Havel PJ, Utzschneider KM, Carr DB, Sinha MK, Boyko EJ, Retzlaff BM, Knopp RH, Brunzell JD, Kahn SE: Relationship of adiponectin to body fat distribution, insulin sensitivity and plasma lipoproteins: evidence for independent roles of age and sex. Diabetologia46 :459 eC469,2003
Ryan AS, Berman DM, Nicklas BJ, Sinha M, Gingerich RL, Meneilly GS, Egan JM, Elahi D: Plasma adiponectin and leptin levels, body composition, and glucose utilization in adult women with wide ranges of age and obesity. Diabetes Care26 :2383 eC2388,2003
Gould AJ, Williams DE, Byrne CD, Hales CN, Wareham NJ: Prospective cohort study of the relationship of markers of insulin resistance and secretion with weight gain and changes in regional adiposity. Int J Obes Relat Metab Disord23 :1256 eC1261,1999
Odeleye OE, de Courten M, Pettitt DJ, Ravussin E: Fasting hyperinsulinemia is a predictor of increased body weight gain and obesity in Pima Indian children. Diabetes46 :1341 eC1345,1997
Hodge AM, Dowse GK, Alberti KG, Tuomilehto J, Gareeboo H, Zimmet PZ: Relationship of insulin resistance to weight gain in nondiabetic Asian Indian, Creole, and Chinese Mauritians: Mauritius Non-communicable Disease Study Group. Metabolism45 :627 eC633,1996
Travers SH, Jeffers BW, Eckel RH: Insulin resistance during puberty and future fat accumulation. J Clin Endocrinol Metab87 :3814 eC3818,2002
Hoag S, Marshall JA, Jones RH, Hamman RF: High fasting insulin levels associated with lower rates of weight gain in persons with normal glucose tolerance: the San Luis Valley Diabetes Study. Int J Obes Relat Metab Disord19 :175 eC180,1995
Swinburn BA, Nyomba BL, Saad MF, Zurlo F, Raz I, Knowler WC, Lillioja S, Bogardus C, Ravussin E: Insulin resistance associated with lower rates of weight gain in Pima Indians. J Clin Invest88 :168 eC173,1991
Valdez R, Mitchell BD, Haffner SM, Hazuda HP, Morales PA, Monterrosa A, Stern MP: Predictors of weight change in a bi-ethnic population: the San Antonio Heart Study. Int J Obes Relat Metab Disord18 :85 eC91,1994
Schwartz MW, Boyko EJ, Kahn SE, Ravussin E, Bogardus C: Reduced insulin secretion: an independent predictor of body weight gain. J Clin Endocrinol Metab80 :1571 eC1576,1995
DeFronzo RA, Tobin JD, Andres R: Glucose clamp technique: a method for quantifying insulin secretion and resistance. Am J Physiol237 :E214 eCE223,1979
Han TS, Kelly IE, Walsh K, Greene RM, Lean ME: Relationship between volumes and areas from single transverse scans of intra-abdominal fat measured by magnetic resonance imaging. Int J Obes Relat Metab Disord21 :1161 eC1166,1997
Schoen RE, Thaete FL, Sankey SS, Weissfeld JL, Kuller LH: Sagittal diameter in comparison with single slice CT as a predictor of total visceral adipose tissue volume. Int J Obes Relat Metab Disord22 :338 eC342,1998(Jenny Tong, Wilfred Y. Fu)