| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Endocrine Care |
Departments of Medicine (F.S.F., N.H., F.A., G.M.R.), Stanford University, School of Medicine Stanford, California 94305; and San Francisco General Hospital (F.S.F.), University of California–San Francisco, San Francisco, California 94110
Address all correspondence and requests for reprints to: G. M. Reaven, M.D., 213 East Grand Avenue, South San Francisco, California 94080. E-mail: greaven{at}shaman.com
Abstract
The current study was initiated to evaluate the ability of insulin resistance to predict a variety of age-related diseases. Baseline measurements of insulin resistance and related variables were made between 1988–1995 in 208 apparently healthy, nonobese (body mass index < 30 kg/m2) individuals, who were then evaluated 4–11 yr later (mean ± SEM = 6.3 ± 0.2 yr) for the appearance of the following age-related diseases: hypertension, coronary heart disease, stroke, cancer, and type 2 diabetes. The effect of insulin resistance on the development of clinical events was evaluated by dividing the study group into tertiles of insulin resistance at baseline and comparing the events in these 3 groups. Clinical endpoints (n = 40) were identified in 37 individuals (18%) of those evaluated, including 12 with hypertension, 3 with hypertension + type 2 diabetes, 9 with cancer, 7 with coronary heart disease, 4 with stroke, and 2 with type 2 diabetes. Twenty-eight out of the total 40 clinical events were seen in 25 individuals (36%) in the most insulin-resistant tertile, with the other 12 occurring in the group with an intermediate degree of insulin resistance. Furthermore, insulin resistance was an independent predictor of all clinical events, using both multiple logistic regression and Cox’s proportional hazards analysis. The fact that an age-related clinical event developed in approximately 1 out of 3 healthy individuals in the upper tertile of insulin resistance at baseline, followed for an average of 6 yr, whereas no clinical events were observed in the most insulin-sensitive tertile, should serve as a strong stimulus to further efforts to define the role of insulin resistance in the genesis of age-related diseases.
WE HAVE RECENTLY shown (1), in a prospective study, that resistance to insulin-mediated glucose disposal predicted cardiovascular morbidity in a group of 147 healthy volunteers, with an average age of 50 yr at baseline, followed for 4.7 yr. The focus of the initial study was on cardiovascular disease, in light of the many observations linking insulin resistance and/or its manifestations to this clinical endpoint (2, 3, 4, 5, 6, 7, 8, 9). The current study was initiated to extend our earlier observations, expanded to include a total of 208 individuals evaluated between 1988–1995, and the clinical endpoints enlarged to include type 2 diabetes and cancer as additional outcome events to be evaluated. Although evidence from human and animal studies has led to the suggestion that insulin resistance, or hyperinsulinemia, may play a role in the development of cancer (10, 11, 12, 13), we are not aware of any prospective studies that have examined this view. The results to be presented are based upon study of 208 individuals, with no apparent disease at baseline, evaluated 4–11 yr after their initial assessment of degree of insulin resistance.
Materials and Methods
To select apparently healthy individuals for this prospective study, the population to be evaluated was limited to volunteers recruited during the period from 1988–1995, who met the following criteria: more than 30 yr of age; body mass index (BMI) less than 30 kg/m2; no history of hypertension (HT), and blood pressure less than 145/90 mm Hg, normal physical examination and routine clinical chemistries, and a normal oral glucose tolerance test (OGTT) (14).
Measurements at baseline included weight, height, sitting blood pressure, and fasting lipid and lipoprotein concentrations (1). In addition, level of habitual physical activity was assessed by questionnaire based on reporting the number of activities per week that resulted in sweating (15).
Evaluation of glucose and insulin metabolism at baseline included a standard 75-g OGTT, with blood samples for measurement of plasma glucose and insulin concentration obtained before, and 30, 60, 120, and 180 min after the oral glucose load. The area under the curve was calculated by the trapezoidal formula to estimate the postload glucose and insulin areas (1). Insulin resistance was measured at baseline by the insulin suppression test as in our earlier study. Briefly, subjects were continuously infused for 180 min with somatostatin (250 µg/h), insulin (25 mU/m2·min), and glucose (240 mg/m2·min). Blood was drawn for measurement of plasma glucose and insulin concentrations every 10 min during the last 30 min of the infusion, and the average of these four values (150, 160, 170, 180 min) was used to define the steady-state plasma glucose (SSPG) and steady-state plasma insulin concentrations. Plasma glucose and insulin concentrations reached a plateau by 120 min, and the steady-state plasma insulin concentrations were essentially identical in all individuals. Therefore, the SSPG concentrations provide an estimate of how effective the same amount of insulin is in mediating disposal of the infused glucose load; the higher the SSPG, the more insulin resistant the individual. Insulin resistance determined with this method correlates almost perfectly (r > 0.9) with values obtained by the insulin clamp technique (16).
Follow-up evaluation was performed 4–11 yr after the baseline studies, with a mean (±SEM) duration of 6.3 ± 0.2 yr. All subjects were asked about their current status of health; medication usage; whether or not they had developed cancer, diabetes, or high blood pressure; and to complete the Rose questionnaire on chest pain (17). All positive reportings were verified by examination of the medical record, with the cooperation of the primary care physician in each instance, and included tissue evidence in the case of a diagnosis of cancer. For those who could not be contacted, it was assumed that either they had moved away or died. The names of these individuals were submitted to the Office of State Registrar in California for search against the death registry.
The study endpoints were the development of HT, coronary heart disease (CHD), stroke, type 2 diabetes, or cancer. HT was defined as the use of antihypertensive medication; CHD included chest pain with positive stress test, coronary angiography (with or without revascularization), coronary bypass surgery, or documented myocardial infarction; stroke included documented clinical neurological deficit lasting over 24 h, with or without confirmatory neuroimaging [cerebrovascular accident (CVA)]; diabetes (type 2) was assumed to be present in subjects treated with at least one oral hypoglycemic agent; and cancer was defined by history of specific treatment (radio-, chemo-, or palliative therapy or a combination of the above), and tissue diagnosis.
Results are expressed as mean ± SEM, and statistical significance was evaluated by ANOVA and contingency table, as appropriate. Nonparametric variables: triglycerides (TG), postload insulin area, and SSPG concentration were log-transformed before analysis. Univariate, multivariate, and logistic regression analysis were used to assess the relationships and interactions of baseline variables, with age-related diseases considered as categorical outcome variable(s). The proportional hazards model (Cox regression) was also used to evaluate relationships among study variables and clinical outcomes in a time-independent manner. All the calculations were performed with a commercial statistical software (Statistica, Statsoft Inc., Tulsa, OK) for the MacIntosh computer (mod. iBook, Apple Computers, Cupertino, CA).
Results
During the period of 1988–1995, 290 healthy volunteers met all of the criteria for inclusion into this study, and we were able to obtain follow-up data on 208 (98 males, 110 females) of these individuals (72%). Baseline demographic characteristics of those available for evaluation were quite similar to those individuals lost to follow-up (age, 50 vs. 48 yr; BMI, approximately 24.7 vs. 24.5 kg/m2).
Clinical endpoints (n = 40) were identified in 37 individuals of those evaluated, including 12 with HT, 9 with cancer, 7 with CHD, and 5 with type 2 diabetes, 3 of which also had high blood pressure, and 4 with stroke. The cancers were distributed as follows: 3 prostate, 2 gastric, 1 breast, 1 colon, 1 bladder, and 1 renal. There were six deaths reported: 2 cardiovascular, 3 cancer related, and 1 due to infection. Search through the State of California Death Registry was negative for those individuals lost to follow-up. It should be emphasized that the period of observation after baseline was 6.2 ± 0.2 yr, 6.3 ± 0.2 yr, and 6.5 ± 0.2 yr in tertile 1, 2, and 3, respectively.
The 208 subjects were divided into tertiles on the basis of their SSPG
concentrations. The baseline clinical characteristics of the 3 groups
are given in Table 1
. Subjects in the
highest SSPG tertile were older and had a higher BMI, diastolic blood
pressure, plasma TG, total cholesterol, and low-density lipoprotein
(LDL) cholesterol concentrations. In addition, high-density lipoprotein
(HDL) cholesterol concentrations were lower, and these individuals were
less physically active. The male-to-female ratios were similar in each
tertile (31/38, 34/35, and 33/37, respectively, for the low, mid, and
top tertile), as well as the number of smokers (
10%).
|
illustrates the number of clinical
events in the 3 SSPG tertiles. The most striking observation is that
none of the 5 endpoints occurred in the most insulin-sensitive tertile.
In marked contrast, 25 individuals in the most insulin-resistant
tertile (36% of the group) had a total of 28 clinical events. Clinical
endpoints were also observed in 12 individuals in the middle SSPG
tertile, but it should be noted that only 1 individual in this group
(1.4%) had CHD, compared with 6 of those in the most insulin-resistant
tertile (8.6%). The rate of developing age-related diseases was
significantly different in the 3 tertiles (P < 0.002).
Deaths were also confined to the 2 most resistant tertiles, with 2
observed in the middle (infection and cancer), and 4 in the upper (2
cardiovascular and 2 cancer-related).
|
, and it is apparent that the
relationships between SSPG concentration and diastolic blood pressure
concentration of cholesterol, LDL cholesterol, HDL cholesterol, and TG,
and both the plasma glucose and insulin responses during the OGTT, were
all statistically significant and were independent of age, gender, BMI,
smoking status, and level of physical activity.
|
emphasize the well-established covariance of the
multiple variables related to insulin resistance and compensatory
hyperinsulinemia (4, 6, 9), and the difficulty of
establishing the nature of the relationship between them and various
clinical outcomes. In approaching this problem, we initially used
univariate logistic regression analysis. These results are shown in
Table 3; and it can be seen that SSPG
concentrations, diastolic blood pressure, HDL cholesterol and TG
concentrations, and the plasma glucose and insulin responses were all
statistically related to the aggregate of clinical events. However,
neither systolic blood pressure nor LDL cholesterol concentrations
retained statistical significance.
|
presents the results of multiple
logistic regression analysis evaluating the independence of the
relationship between the variables identified in the univariate
analysis as being associated with the appearance of all age-related
diseases. It is apparent that, when taken as an aggregate, only insulin
resistance (SSPG concentration) was an independent predictor of the 40
age-related clinical events. Although the number of individual events
were relatively small, we also defined the relationship between them
and the various risk factors identified in Table 3. Because stroke was
observed only in 4 subjects, it was combined with CHD for this
analysis. These results show that insulin resistance (SSPG
concentration) was also the only independent predictor of CHD + stroke
and cancer. SSPG concentration and both glucose and insulin responses
were correlated with the development of type 2 diabetes in a univariate
analysis, but when all 3 were entered into the multiple regression
analysis, none of them emerged as being independent. This finding was
not surprising, given how closely these 3 variables are related. In the
case of HT, both diastolic blood pressure and plasma TG concentration
were independent predictors.
|
, and they again document the
highly significant relationship between insulin resistance (SSPG
concentration) and the aggregate of clinical events (P
< 0.02), CHD +stroke (P < 0.02), and cancer
(P < 0.05). It is also clear, from these data, that
the impact of insulin resistance on all of these outcomes is
independent of BMI.
|
This study was initiated to evaluate the hypothesis that insulin resistance would predict the development, over time, of clinical syndrome that might be best subsumed under the heading of age-related diseases (HT, CHD, stroke, cancer, and type 2 diabetes). Although the results provide substantial support for this point of view, perhaps the most striking finding was that none of these events were seen in the third of the population that was most insulin-sensitive. Given the fact that the period of observation ranged from 4–11 yr, with an average follow-up of 6.3 yr, the fact that not one clinical event took place in the insulin-sensitive tertile seems to be truly remarkable. If the ability of insulin sensitivity to decrease risk of developing age-related diseases can be confirmed in subsequent studies, the public health implications are enormous. For example, it has been shown (18) that approximately 50% of the variability in insulin-mediated glucose disposal between apparently healthy individuals is related to life-style (25% to differences in weight and 25% to differences in level of habitual physical activity). As a corollary, the ability of life-style interventions to improve insulin sensitivity and to reduce risk of age-related diseases is self-evident. If 50% of the variability in insulin-mediated glucose disposal is related to life-style, it is likely that the remaining 50% is attributable to genetic differences. In support of this view is evidence that this variable is certainly familial (19). Thus, recognition of families sharing insulin resistance would permit an even more intensive attempt at life-style intervention to improve insulin sensitivity.
The observation that development of type 2 diabetes, HT, and cardiovascular disease was more common in the most insulin-resistant tertile is not surprising. The presence of insulin resistance has been well recognized for approximately 25 yr (20, 21), and insulin resistance and/or compensatory hyperinsulinemia have been shown to predict type 2 diabetes in several prospective studies (22, 23, 24, 25). Similarly, the existence of insulin resistance and/or compensatory hyperinsulinemia in patients with essential HT has been extensively documented (26), and hyperinsulinemia as a surrogate measure of insulin resistance has also been shown to be an independent predictor of essential HT (27, 28, 29, 30). There is also considerable evidence that insulin resistance and/or hyperinsulinemia predict the development of cardiovascular disease (1, 2, 3, 4, 5, 6), but controversy continues as to the validity of this association (31, 32).
In contrast to the association between insulin resistance and the
clinical syndromes discussed above, the possibility that abnormalities
of insulin metabolism might be linked to the risk of cancer has
received much less attention. However, the fact that its prevalence
increases with age, and the existence of published reports suggesting
that hyperinsulinemia might increase cancer risk (10, 11, 12, 13),
led to its inclusion in this study as one of the endpoints to be
evaluated. The results showed that cancer was diagnosed in nine
subjects over an average period of 6 yr. Not surprisingly, the subjects
who developed cancer were somewhat older at baseline (61 ± 2 yr),
compared with those who had either a noncancer (53 ± 2 yr) or no
(50 ± 1 yr) events, but the three groups were similar in terms of
period of observation, BMI, or history of smoking. Furthermore, the
relationship between insulin resistance and cancer defined in Table 4
was present, when age-adjusted, and the results of the Cox proportional
hazard analysis in Table 5 also document a statistically significant
and independent relationship between insulin resistance and cancer.
However, it should be emphasized that the cases of cancer were confined
to the upper two tertiles, and a wide variety of different cancers were
observed. Thus, in the case of cancer, it could be argued that the more
appropriate conclusion is that insulin sensitivity decreases cancer
risk, rather than insulin resistance increasing it. The fact that we
cannot differentiate between these two alternatives at this time does
not negate the potential importance of our findings nor the need to
pursue this issue more vigorously.
Although the experimental findings we have presented are relatively straight-forward, we can only speculate as to why a variety of age-related diseases might be linked to insulin resistance and/or hyperinsulinemia. In this context, it is worth noting that caloric restriction, in both invertebrates and mammals, leads to a decrease in age-related morbidities and enhanced life span, associated with enhanced insulin sensitivity, and lower glucose and insulin concentrations (33, 34, 35, 36, 37). An age-related decline in insulin sensitivity in rats allowed free access to food would result in an elevation in ambient glucose concentrations, which could lead to higher rates of protein glycation and glycoxidation, with production of carbonyls, advanced glycation end-products, and protein cross-linking (38, 39, 40, 41, 42). Such products of carbohydrate and protein modification can initiate lipid peroxidation (43), with production of genotoxic, atherogenic, and diabetogenic aldehydes (44, 45, 46, 47, 48). It should be noted that other explanations have been proposed to account for the observation that caloric restriction can prolong life span. For example, in a recent review article, it was suggested that the benefit of caloric restriction on life span is attributable to the associated reduced fat mass, and a consequent decrease in the secretion of various peptides, cytokines, couplement factors, and substrate (49). Finally, evidence has also recently been summarized implicating an increase in levels of IGF-1 as playing a role as a risk factor for several forms of cancer (50), and this offers another possible mechanistic link between insulin resistance/hyperinsulinemia and cancer. Whether any of these possibilities have relevance to our results is clearly conjectural, but they may serve to provide some framework with which to pursue future studies of the association between insulin resistance and age-related diseases.
In conclusion, an age-related disease developed in approximately one out of three healthy individuals who were in the upper tertile of insulin resistance at baseline, followed for an average of 6 yr. In contrast, no clinical event was seen in the most insulin-sensitive tertile. These data should serve as a strong stimulus for further efforts to define the role of insulin resistance in the genesis of age-related diseases.
Footnotes
This work was supported by Research Grants HL-08506 and RR-0007 from the NIH.
Abbreviations: BMI, Body mass index; CHD, coronary heart disease; CVA, cerebrovascular accident; HDL, high-density lipoprotein; HT, hypertension; LDL, low-density lipoprotein; SSPG, steady-state plasma glucose; OGTT, oral glucose tolerance test; TG, triglycerides.
Received July 12, 2000.
Accepted April 4, 2001.
References
This article has been cited by other articles:
 |
|
 |
|
  M. Barbieri, M. R. Rizzo, M. Papa, V. Boccardi, A. Esposito, M. F. White, and G. Paolisso The IRS2 Gly1057Asp Variant Is Associated With Human Longevity J Gerontol A Biol Sci Med Sci, November 3, 2009; (2009) glp154v1. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Schenk, M. P. Harber, C. R. Shrivastava, C. F. Burant, and J. F. Horowitz Improved insulin sensitivity after weight loss and exercise training is mediated by a reduction in plasma fatty acid mobilization, not enhanced oxidative capacity J. Physiol., October 15, 2009; 587(20): 4949 - 4961. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 B. A. Irving, J. Y. Weltman, J. T. Patrie, C. K. Davis, D. W. Brock, D. Swift, E. J. Barrett, G. A. Gaesser, and A. Weltman Effects of Exercise Training Intensity on Nocturnal Growth Hormone Secretion in Obese Adults with the Metabolic Syndrome J. Clin. Endocrinol. Metab., June 1, 2009; 94(6): 1979 - 1986. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 W T. Cade Diabetes-Related Microvascular and Macrovascular Diseases in the Physical Therapy Setting Physical Therapy, November 1, 2008; 88(11): 1322 - 1335. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 S. Kidambi and S. B. Patel Diabetes Mellitus: Considerations for Dentistry J Am Dent Assoc, October 1, 2008; 139(suppl_5): 8S - 18S. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 C. A Conover, M. A Mason, J. A Levine, and C. M Novak Metabolic consequences of pregnancy-associated plasma protein-A deficiency in mice: exploring possible relationship to the longevity phenotype J. Endocrinol., September 1, 2008; 198(3): 599 - 605. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 X. Xiao, Z.-X. Zhang, H. J. Cohen, H. Wang, W. Li, T. Wang, T. Xu, A. Liu, M.-Y. Gai, S. Ying, et al. Evidence of a Relationship Between Infant Birth Weight and Later Diabetes and Impaired Glucose Regulation in a Chinese Population Diabetes Care, March 1, 2008; 31(3): 483 - 487. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 E. Lurbe, I. Torro, F. Aguilar, J. Alvarez, J. Alcon, J. M. Pascual, and J. Redon Added Impact of Obesity and Insulin Resistance in Nocturnal Blood Pressure Elevation in Children and Adolescents Hypertension, March 1, 2008; 51(3): 635 - 641. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. W. J. Leunissen, P. Oosterbeek, L. K. M. Hol, A. A. Hellingman, T. Stijnen, and A. C. S. Hokken-Koelega Fat Mass Accumulation during Childhood Determines Insulin Sensitivity in Early Adulthood J. Clin. Endocrinol. Metab., February 1, 2008; 93(2): 445 - 451. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. H. Kim and G. M. Reaven Isolated Impaired Fasting Glucose and Peripheral Insulin Sensitivity: Not a simple relationship Diabetes Care, February 1, 2008; 31(2): 347 - 352. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. H. Shanik, Y. Xu, J. Skrha, R. Dankner, Y. Zick, and J. Roth Insulin Resistance and Hyperinsulinemia: Is hyperinsulinemia the cart or the horse? Diabetes Care, February 1, 2008; 31(Supplement_2): S262 - S268. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. Muniyappa, S. Lee, H. Chen, and M. J. Quon Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage Am J Physiol Endocrinol Metab, January 1, 2008; 294(1): E15 - E26. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
E. B. Arias and G. D. Cartee In vitro simulation of calorie restriction-induced decline in glucose and insulin leads to increased insulin-stimulated glucose transport in rat skeletal muscle Am J Physiol Endocrinol Metab, December 1, 2007; 293(6): E1782 - E1788. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. Musso, R. Gambino, F. De Michieli, G. Biroli, A. Premoli, G. Pagano, S. Bo, M. Durazzo, and M. Cassader Nitrosative stress predicts the presence and severity of nonalcoholic fatty liver at different stages of the development of insulin resistance and metabolic syndrome: possible role of vitamin A intake Am. J. Clinical Nutrition, September 1, 2007; 86(3): 661 - 671. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. McLaughlin, S. Carter, C. Lamendola, F. Abbasi, P. Schaaf, M. Basina, and G. Reaven Clinical Efficacy of Two Hypocaloric Diets That Vary in Overweight Patients With Type 2 Diabetes: Comparison of moderate fat versus carbohydrate reductions Diabetes Care, July 1, 2007; 30(7): 1877 - 1879. [Full Text] [PDF]
|
|
|
|
 |
|
 A. L. Carrel, R. R. Clark, S. Peterson, J. Eickhoff, and D. B. Allen School-Based Fitness Changes Are Lost During the Summer Vacation Arch Pediatr Adolesc Med, June 1, 2007; 161(6): 561 - 564. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. Jeppesen, T. W. Hansen, S. Rasmussen, H. Ibsen, C. Torp-Pedersen, and S. Madsbad Insulin Resistance, the Metabolic Syndrome, and Risk of Incident Cardiovascular Disease: A Population-Based Study J. Am. Coll. Cardiol., May 29, 2007; 49(21): 2112 - 2119. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T. McLaughlin, F. Abbasi, C. Lamendola, and G. Reaven Heterogeneity in the Prevalence of Risk Factors for Cardiovascular Disease and Type 2 Diabetes Mellitus in Obese Individuals: Effect of Differences in Insulin Sensitivity Arch Intern Med, April 9, 2007; 167(7): 642 - 648. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Abbasi, H. M. F. Farin, C. Lamendola, T. McLaughlin, E. A. Schwartz, G. M. Reaven, and P. D. Reaven The Relationship between Plasma Adiponectin Concentration and Insulin Resistance Is Altered in Smokers J. Clin. Endocrinol. Metab., December 1, 2006; 91(12): 5002 - 5007. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. A. Neville, R. J. Cohn, K. S. Steinbeck, K. Johnston, and J. L. Walker Hyperinsulinemia, Impaired Glucose Tolerance, and Diabetes Mellitus in Survivors of Childhood Cancer: Prevalence and Risk Factors J. Clin. Endocrinol. Metab., November 1, 2006; 91(11): 4401 - 4407. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. McLaughlin, S. Carter, C. Lamendola, F. Abbasi, G. Yee, P. Schaaf, M. Basina, and G. Reaven Effects of moderate variations in macronutrient composition on weight loss and reduction in cardiovascular disease risk in obese, insulin-resistant adults. Am. J. Clinical Nutrition, October 1, 2006; 84(4): 813 - 821. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. Reinehr, G. de Sousa, A. M. Toschke, and W. Andler Long-term follow-up of cardiovascular disease risk factors in children after an obesity intervention. Am. J. Clinical Nutrition, September 1, 2006; 84(3): 490 - 496. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. J. Koopman, A. G. Mainous III, H. A. Liszka, J. A. Colwell, E. H. Slate, M. A. Carnemolla, and C. J. Everett Evidence of Nephropathy and Peripheral Neuropathy in US Adults With Undiagnosed Diabetes. Ann. Fam. Med, September 1, 2006; 4(5): 427 - 432. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Z. T. Bloomgarden Third Annual World Congress on the Insulin Resistance Syndrome: Mediators, antecedents, and measurement Diabetes Care, July 1, 2006; 29(7): 1700 - 1706. [Full Text] [PDF]
|
|
|
|
|
|
G. M Reaven The metabolic syndrome: is this diagnosis necessary? Am. J. Clinical Nutrition, June 1, 2006; 83(6): 1237 - 1247. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. McLaughlin, M. Stuhlinger, C. Lamendola, F. Abbasi, J. Bialek, G. M. Reaven, and P. S. Tsao Plasma Asymmetric Dimethylarginine Concentrations Are Elevated in Obese Insulin-Resistant Women and Fall with Weight Loss J. Clin. Endocrinol. Metab., May 1, 2006; 91(5): 1896 - 1900. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. K. Rutter, J. B. Meigs, L. M. Sullivan, R. B. D'Agostino Sr, and P. W. Wilson Insulin Resistance, the Metabolic Syndrome, and Incident Cardiovascular Events in the Framingham Offspring Study Diabetes, November 1, 2005; 54(11): 3252 - 3257. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. Reaven All obese individuals are not created equal: insulin resistance is the major determinant of cardiovascular disease in overweight/obese individuals Diabetes and Vascular Disease Research, October 1, 2005; 2(3): 105 - 112. [Abstract] [PDF]
|
|
|
|
|
|
R. Kahn, J. Buse, E. Ferrannini, and M. Stern The Metabolic Syndrome: Time for a Critical Appraisal: Joint statement from the American Diabetes Association and the European Association for the Study of Diabetes Diabetes Care, September 1, 2005; 28(9): 2289 - 2304. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Bartke Minireview: Role of the Growth Hormone/Insulin-Like Growth Factor System in Mammalian Aging Endocrinology, September 1, 2005; 146(9): 3718 - 3723. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. M. Reaven The Metabolic Syndrome: Requiescat in Pace Clin. Chem., June 1, 2005; 51(6): 931 - 938. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. Mancia, R. Facchetti, M. Bombelli, H. P. Friz, G. Grassi, C. Giannattasio, and R. Sega Relationship of Office, Home, and Ambulatory Blood Pressure to Blood Glucose and Lipid Variables in the PAMELA Population Hypertension, June 1, 2005; 45(6): 1072 - 1077. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. P. Gardner, S. Li, S. R. Srinivasan, W. Chen, M. Kimura, X. Lu, G. S. Berenson, and A. Aviv Rise in Insulin Resistance Is Associated With Escalated Telomere Attrition Circulation, May 3, 2005; 111(17): 2171 - 2177. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 R. Sukhija, W. S. Aronow, D. Nayak, C. Ahn, and M. B. Weiss Increased Fasting Plasma Insulin Concentrations are Associated with the Severity of Angiographic Coronary Artery Disease Angiology, May 1, 2005; 56(3): 249 - 251. [Abstract] [PDF]
|
|
|
|
 |
|
 J. A. Lemon, D. R. Boreham, and C. D. Rollo A Complex Dietary Supplement Extends Longevity of Mice J. Gerontol. A Biol. Sci. Med. Sci., March 1, 2005; 60(3): 275 - 279. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. L. Hofman, F. Regan, W. E. Jackson, C. Jefferies, D. B. Knight, E. M. Robinson, and W. S. Cutfield Premature Birth and Later Insulin Resistance N. Engl. J. Med., November 18, 2004; 351(21): 2179 - 2186. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. L. Cheal, F. Abbasi, C. Lamendola, T. McLaughlin, G. M. Reaven, and E. S. Ford Relationship to Insulin Resistance of the Adult Treatment Panel III Diagnostic Criteria for Identification of the Metabolic Syndrome Diabetes, May 1, 2004; 53(5): 1195 - 1200. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 T Reinehr and W Andler Changes in the atherogenic risk factor profile according to degree of weight loss Arch. Dis. Child., May 1, 2004; 89(5): 419 - 422. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Abbasi, J. W. Chu, C. Lamendola, T. McLaughlin, J. Hayden, G. M. Reaven, and P. D. Reaven Discrimination Between Obesity and Insulin Resistance in the Relationship With Adiponectin Diabetes, March 1, 2004; 53(3): 585 - 590. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. Z. Lewanczuk, B. W. Paty, and E. L. Toth Comparison of the [13C]Glucose Breath Test to the Hyperinsulinemic-Euglycemic Clamp When Determining Insulin Resistance Diabetes Care, February 1, 2004; 27(2): 441 - 447. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 G. Reaven, F. Abbasi, and T. McLaughlin Obesity, Insulin Resistance, and Cardiovascular Disease Recent Prog. Horm. Res., January 1, 2004; 59(1): 207 - 223. [Abstract] [Full Text]
|
|
|
|
 |
|
 D. B. Boyd Insulin and Cancer Integr Cancer Ther, December 1, 2003; 2(4): 315 - 329. [Abstract] [PDF]
|
|
|
|
 |
|
 T. McLaughlin, F. Abbasi, K. Cheal, J. Chu, C. Lamendola, and G. Reaven Use of Metabolic Markers To Identify Overweight Individuals Who Are Insulin Resistant Ann Intern Med, November 18, 2003; 139(10): 802 - 809. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. B. Davidson Is Treatment of Insulin Resistance Beneficial Independent of Glycemia? Diabetes Care, November 1, 2003; 26(11): 3184 - 3186. [Full Text] [PDF]
|
|
|
|
|
|
M. Barbieri, M. Bonafe, C. Franceschi, and G. Paolisso Insulin/IGF-I-signaling pathway: an evolutionarily conserved mechanism of longevity from yeast to humans Am J Physiol Endocrinol Metab, November 1, 2003; 285(5): E1064 - E1071. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. Komninou, A. Ayonote, J. P. Richie Jr., and B. Rigas Insulin Resistance and Its Contribution to Colon Carcinogenesis Experimental Biology and Medicine, April 1, 2003; 228(4): 396 - 405. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. Chen, G. Sullivan, L. Q. Yue, A. Katz, and M. J. Quon QUICKI is a useful index of insulin sensitivity in subjects with hypertension Am J Physiol Endocrinol Metab, April 1, 2003; 284(4): E804 - E812. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
G. M. Reaven Importance of Identifying the Overweight Patient Who Will Benefit the Most by Losing Weight Ann Intern Med, March 4, 2003; 138(5): 420 - 423. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Endocrinology | Endocrine Reviews | J. Clin. End. & Metab. |
| Molecular Endocrinology | Recent Prog. Horm. Res. | All Endocrine Journals |
