AJCN North Carolina Research Campus
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
QUICK SEARCH:   [advanced]


     

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Pischon, T.
Right arrow Articles by Rimm, E. B
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pischon, T.
Right arrow Articles by Rimm, E. B
Agricola
Right arrow Articles by Pischon, T.
Right arrow Articles by Rimm, E. B
American Journal of Clinical Nutrition, Vol. 81, No. 4, 780-786, April 2005
© 2005 American Society for Clinical Nutrition

ORIGINAL RESEARCH COMMUNICATION

Association between dietary factors and plasma adiponectin concentrations in men1,2,3

Tobias Pischon, Cynthia J Girman, Nader Rifai, Gokhan S Hotamisligil and Eric B Rimm

1 From the Departments of Nutrition and Epidemiology, Harvard School of Public Health, Boston, MA (TP, GSH, and EBR); the Channing Laboratory, Harvard Medical School and Brigham & Women’s Hospital, Boston, MA (EBR); the Department of Laboratory Medicine, Children’s Hospital and the Department of Pathology, Harvard Medical School, Boston, MA (NR); the Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke, Germany (TP); and the Department of Epidemiology, Merck Research Laboratories, West Point, PA (CJG).

2 Supported by grants HL35464, CA55075, and AA11181 from the NIH and by a research grant from Merck & Co, Inc (West Point, PA). TP is a Jetson Lincoln fellow, supported in part by an unrestricted gift from J Lincoln.

3 Reprints not available. Address correspondence to T Pischon, Department of Epidemiology, German Institute of Human Nutrition, Potsdam-Rehbruecke, Arthur-Scheunert Allee 114-116, 14558 Nuthetal, Germany. E-mail: pischon{at}mail.dife.de.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Adiponectin, an adipocyte-derived peptide, improves insulin sensitivity, has antiinflammatory and antiatherogenic effects, and is associated with a lower risk of ischemic heart disease (IHD) and type 2 diabetes. However, little is known about dietary predictors of plasma adiponectin concentrations in humans.

Objective: Our objective was to examine cross-sectionally the association between dietary factors and plasma adiponectin in men.

Design: Our study included 532 male participants of the Health Professionals Follow-Up Study who were selected as control subjects for an investigation of biological predictors of IHD. Diet, lifestyle, and anthropometric data were assessed by questionnaires.

Results: After multivariable adjustment, adiponectin was significantly inversely related to glycemic load (–1.3 mg/L per 1-SD increase; P = 0.02) and tended to be positively associated with total fat intake (0.7 mg/L per 0.5% of energy from fat instead of carbohydrates; P = 0.06). We also found a significant nonlinear association between plasma adiponectin concentrations and alcohol intake (P for quadratic trend = 0.01). Thus, whereas nondrinkers had mean plasma adiponectin concentrations of 16.48 mg/L, those who consumed 0.1–4.9, 5.0–14.9, 15.0–29.9, or ≥30 g alcohol/d had mean concentrations of 16.79 (P = 0.77 compared with nondrinkers), 18.97 (P = 0.02), 19.11 (P = 0.01), and 18.39 (P = 0.10) mg/L, respectively.

Conclusions: Moderate alcohol intake is associated with higher adiponectin concentrations, whereas a carbohydrate-rich diet with a high glycemic load is associated with lower adiponectin concentrations in men with no history of cardiovascular disease. Although the strength of these associations was modest, our observations highlight the hypothesis that dietary factors may modulate plasma adiponectin concentrations—a potential mediator related to a reduced IHD risk.

Key Words: Obesity • nutrition • risk factors • cardiovascular disease • ischemic heart disease


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Adiponectin, a recently discovered circulating hormone secreted by the adipose tissue, is involved in glucose and lipid metabolism (1, 2). Contrary to other adipose-derived hormones, adiponectin concentrations are reduced in subjects with obesity, insulin resistance, or type 2 diabetes (1, 2). Adiponectin treatment improves insulin sensitivity in animal models, and low concentrations have been shown to predict type 2 diabetes in humans (3–7). Adiponectin is inversely associated with several traditional cardiovascular disease risk factors, such as hypertension, hypertriglyceridemia, and low HDL-cholesterol concentrations (2), and animal data suggest that adiponectin may have antiatherogenic and antiinflammatory properties (8–11). In line with these reports, high plasma concentrations were recently shown to be associated with a lower risk of ischemic heart disease (IHD) in humans, which suggests that adiponectin may be a protective mediator for this disease (12, 13).

Although studies suggest that caloric restriction, weight loss, and activation of the peroxisome-proliferator activated receptor {gamma} is associated with higher adiponectin concentrations (14, 15), little is known about dietary predictors of plasma adiponectin concentrations. Therefore, the aim of our study was to examine cross-sectionally the association between dietary factors and plasma adiponectin concentrations.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study population
The study population comprised 532 male participants in the Health Professionals Follow-Up Study (HPFS) who were selected as control subjects in a nested case-control study of biological predictors of IHD (13). The HPFS is a prospective cohort investigation of 51 529 US male health professionals, aged 40–75 y at baseline in 1986, designed primarily to evaluate associations between diet and chronic disease incidence (16). Information about health and disease is assessed biennially, and diet is assessed every 4 y by self-administered questionnaires (17). Between 1993 and 1995, a blood sample was requested from all subjects; 18 225 participants provided samples. Men who provided samples were somewhat younger and smoked less, but otherwise were similar to those who did not provide samples. After exclusion of subjects with a history of cardiovascular disease before 1994, 266 subjects with incident nonfatal myocardial infarction or fatal IHD were identified during 6 y of follow-up. The control subjects were randomly selected 2:1 matched for age, date of blood drawing, and smoking status from participants with a blood sample and with no history of cardiovascular disease at the time of case ascertainment (risk-set sampling) (18). We also examined the associations between dietary factors and plasma adiponectin concentrations among cases (data not shown); however, we found no substantive differences between cases and control subjects. Because of the potential bias due to associations of adiponectin and dietary factors with IHD risk, we restricted the present analysis to the control subjects. The study protocol was approved by the Harvard School of Public Health Human Subjects Committee Review Board.

Assessment of diet, alcohol consumption, lifestyle factors, and anthropometric data
Average nutrient intakes were computed from semiquantitative food-frequency questionnaires (SFFQs) with the use of composition values primarily from US Department of Agriculture sources (19). The SFFQ used was previously evaluated for reproducibility and validity within the HPFS (17). The correlation for nutrients estimated with the SFFQs and for those measured with a 2-wk diet record ranged from 0.37 for polyunsaturated fat to 0.92 for vitamin C with supplements (average 0.65) (17). The correlations for whole foods were in a similar range. For the macronutrient intakes we used the average from the SFFQs obtained in 1986, 1990, and 1994 to minimize measurement error. The effect estimates were similar when we used information from the 1994 SFFQ only.

The average dietary glycemic index for each participant was calculated by summing the products of the carbohydrate content per serving for each food, times the average number of servings of that food per day, times its glycemic index derived from published data (20, 21), divided by the total amount of daily carbohydrate intake. The glycemic load was derived according to a similar principle, but without dividing by the total amount of carbohydrate. The performance of the SFFQ in assessing the individual foods from which the glycemic index and load were derived was previously documented (22). Furthermore, the average glycemic index and glycemic load—as assessed with these questionnaires—was previously shown to be closely related to type 2 diabetes and IHD (23, 24).

Alcohol intake was calculated by summing the frequency and amount of the alcoholic content of beer, red and white wine, and spirits as reported by the participants on the SFFQ in 1994. The alcohol content was estimated as 12.8 g/bottle or can of beer (360 mL), 11.0 g for a glass of wine (118 mL), and 14.0 g for spirits (45 mL). The reproducibility and validity of alcohol consumption measured with a self-administered questionnaire was evaluated in detail within the HPFS. Alcohol intake reported over the previous year on the SFFQ was highly correlated with the intake assessed with two 1-wk diet records (r = 0.86) (25).

Anthropometric data and smoking status were derived from the 1994 questionnaire. Physical activity was computed as the average metabolic equivalent hours, on the basis of the types and durations of activities over the previous year reported biennially on the questionnaires between 1986 and 1994. The types of activities included jogging; running; bicycling; swimming laps; playing tennis, squash, and racquetball; performing calisthenics or rowing; walking; heavy outdoor work; and weightlifting. The questionnaire included 13 response categories, ranging from 0 to 40 h/wk. One MET-h is equivalent to energy expenditure when sitting quietly for 1 h (26). Medical history was derived from the questionnaires between 1986 and 1994. Validity and reproducibility of the questionnaires and the collected data and measurements were reported in detail elsewhere (27, 28).

Measurement of biochemical variables
On arrival at our laboratory, the blood samples were centrifuged (1530 x g, 4 °C); separated into plasma, white blood cells, and red blood cells; and stored at –130 °C (or colder) in continuously alarmed and monitored liquid nitrogen freezers. Plasma adiponectin concentrations were measured by competitive radioimmunoassay (Linco Research Inc, St Charles, MO) with a CV of 3.4% (n = 39). Within the HPFS we found that adiponectin concentrations had excellent intraclass correlation coefficients over a period of 1 y and were not substantially affected by transport conditions (29). Furthermore, we found no significant correlation between plasma adiponectin concentrations and storage time (r = 0.03, P = 0.34).

Statistical analyses
Spearman’s age-adjusted partial correlation coefficients and multivariable linear regression with robust variance were used to evaluate the associations between adiponectin concentrations and dietary factors without the need of normal distribution assumptions (30). We adjusted for age (5-y categories), smoking status (never, past, nonsmoker with unknown past history, current smoker, and unknown), history of diabetes, history of hypertension, alcohol consumption (nondrinkers, 0.1–4.9 g/d, 5.0–14.9 g/d, 15.0–29.9 g/d, and ≥30 g/d), and physical activity, with and without further adjustment for body mass index (in kg/m2: <20, 20–24, 25–29, 30–34, and ≥35). In multivariate energy-density models, we additionally included total energy intake and the percentages of energy derived from protein and fat (or carbohydrate). The coefficients from these models reflect the estimated change in plasma adiponectin concentration that would result from substituting a specific percentage of energy from fat for carbohydrate (or vice versa). Dietary glycemic index and load were energy-adjusted with the use of the residual method (31) and examined in similar models that included total energy intake and energy derived from protein. The nutrients under investigation were considered as continuous variables and covariates as categorical variables (quintiles). In similar models we examined the association between alcohol consumption and plasma adiponectin concentrations by computing least-squares means. Polynomial regression and log-likelihood ratio testing were used to examine quadratic trends. The analyses were conducted with SAS (version 8.2; SAS Institute, Cary, NC), and all P values presented are two-tailed.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Subjects in the highest quintile of adiponectin concentrations (≥24.9 mg/L) had a lower body mass index, were physically more active, and had a higher alcohol consumption than the subjects in the lowest quintile (<10.6 mg/L) (Table 1Go). The prevalence of diabetes was slightly lower in subjects in the highest quintile of adiponectin concentrations. Protein and carbohydrate intakes and glycemic load were lower in the subjects in the highest than in the lowest adiponectin quintile. We found significant or borderline significant trends across quintiles for these variables in this age-adjusted analysis, although the mean concentrations (as shown in Table 1Go) suggest some deviation from linear trends.


View this table:
[in this window]
[in a new window]
  		TABLE 1 Characteristics of 532 men who participated in the Health Professionals Follow-Up Study by quintiles of adiponectin concentration1

 
In nonparametric correlation analyses adjusted for age (Table 2Go), we found a small but significant correlation for protein intake (r = –0.10, P = 0.02) and alcohol consumption (r = 0.14, P = 0.002) and borderline significant correlations for glycemic index (r = –0.08, P = 0.08) and glycemic load (r = –0.07, P = 0.09) with adiponectin concentrations.


View this table:
[in this window]
[in a new window]
  		TABLE 2 Age-adjusted Spearman partial correlation coefficients between dietary factors and adiponectin concentrations in 532 men who participated in the Health Professionals Follow-Up Study1

 
After adjustment for age, smoking, history of diabetes and hypertension, alcohol consumption, physical activity, body mass index, energy intake, and protein intake (Table 3Go), a 5% increase in energy derived from carbohydrate in exchange for energy derived from fat was associated with a 0.59 mg/L decrease in plasma adiponectin concentrations (P = 0.05). An increase in glycemic load of 1 SD was associated with a 1.32 mg/L decrease in adiponectin concentration (P = 0.02).


View this table:
[in this window]
[in a new window]
  		TABLE 3 Multivariable-adjusted associations between macronutrient intakes and plasma adiponectin concentrations in 532 men who participated in the Health Professionals Follow-Up Study1

 
In a similar multivariable-adjusted model, we found a nonlinear association between alcohol intake and plasma adiponectin concentration (P for quadratic trend = 0.01; Figure 1Go). Thus, whereas nondrinkers (n = 122) had mean plasma adiponectin concentrations of 16.48 mg/L (95% CI: 15.18, 17.78), those who consumed 0.1–4.9 (n = 116), 5.0–14.9 (n = 123), 15.0–29.9 (n = 88), or ≥30 (n = 83) g alcohol/d had mean concentrations of 16.79 (95% CI: 15.24, 18.33; P = 0.77 compared with nondrinkers), 18.97 (95% CI: 17.23, 20.71; P = 0.02), 19.11 (95% CI: 17.47, 20.76; P = 0.01), and 18.39 (95% CI: 16.59, 20.18; P = 0.10) mg/L, respectively. These results were similar when we excluded the subjects whose alcohol intake was >50 g/d.



View larger version (21K):
[in this window]
[in a new window]
  		FIGURE 1. Mean (±SEM) plasma adiponectin concentrations in relation to alcohol consumption, with and without further adjustment for BMI in 532 men who participated in the Health Professionals Follow-Up Study. The multivariable model was adjusted for age, smoking, hypertension, diabetes, physical activity, and total energy, total fat, and protein intakes. The results were obtained by calculating least-squares means with the use of multivariable linear regression with robust variance (30). The number of subjects per alcohol category was 122 for nondrinkers, 116 for subjects consuming 0.1–4.9 g alcohol/d, 123 for those consuming 5.0–14.9 g alcohol/d, 88 for those consuming 15.0–29.9 g alcohol/d, and 83 for those consuming ≥35.0 g alcohol/d. P for quadratic trend < 0.05 for all models. P value obtained by log-likelihood ratio testing of hierarchical polynomial regression models. *Significantly different from nondrinkers, P < 0.05.

 
We also examined the relation between individual types of beverages and plasma adiponectin concentrations, with control for the other types of beverages in the multivariable-adjusted model. In this analysis, we found a pattern similar to that for total alcohol consumption for alcohol from beer and liquor but a weaker association for alcohol from wine. There were no significant interactions of any of the macronutrients with age (≥ or <65 y) or body mass index (≥ or <25) on plasma adiponectin concentrations.

In a further analysis, we examined the interrelation between alcohol consumption, adiponectin, and HDL-cholesterol concentrations. Additional adjustment for HDL-cholesterol concentrations slightly attenuated the nonlinear multivariable-adjusted association between alcohol consumption and plasma adiponectin concentrations (P for quadratic trend = 0.05). Thus, whereas nondrinkers had mean plasma adiponectin concentrations of 17.76 mg/L, those who consumed 0.1–4.9, 5.0–14.9, 15.0–29.9, or ≥30 g alcohol/d had mean concentrations of 18.02 (P = 0.80 compared with nondrinkers), 18.65 (P = 0.40), 18.01 (P = 0.81), and 16.31 mg/L (P = 0.22), respectively. HDL cholesterol significantly predicted adiponectin concentrations in this model (P for linear trend < 0.001).

Additionally, we examined the established association between alcohol consumption and HDL-cholesterol concentrations to determine how strongly attenuated it might be after adjustment for adiponectin. After multivariable adjustment, there was a significant association between alcohol consumption and plasma HDL-cholesterol concentrations (P for linear trend < 0.001); mean HDL-cholesterol concentrations in the aforementioned alcohol consumption categories were as follows: 40.9 mg/dL (reference), 41.5 mg/dL (P = 0.62), 46.8 mg/dL (P < 0.001), 51.0 mg/dL (P < 0.001), and 52.4 mg/dL (P < 0.001). Further adjustment for adiponectin did not substantially change this association (P for linear trend < 0.001); the mean plasma HDL-cholesterol concentrations in the respective alcohol consumption categories were as follows: 41.6 mg/dL (reference), 42.2 mg/dL (P = 0.62), 46.4 mg/dL (P < 0.001), 50.5 mg/dL (P < 0.001), and 51.5 mg/dL (P < 0.001). In this model, adiponectin independently predicted HDL-cholesterol concentrations (P for linear trend < 0.001).


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
In this cross-sectional study, moderate alcohol consumption was significantly associated with higher plasma adiponectin concentrations, whereas a diet with a high glycemic load was significantly related to lower adiponectin concentrations. Carbohydrate intake also tended to be inversely related to adiponectin concentrations. Although the strength of these associations was modest, our results suggest that dietary factors are related to plasma adiponectin concentrations and support the hypothesis that dietary factors may modulate adiponectin concentrations, a potential mediator related to decreased IHD risk.

Dietary factors play an important role in the development of type 2 diabetes and IHD (32, 33). Excess caloric intake contributes to the development of obesity, a major risk factor for these diseases (34). Furthermore, diets high in saturated and trans fats and with a high glycemic load (indicating a large amount of processed refined carbohydrates) increase cardiovascular disease and diabetes risk, whereas diets high in polyunsaturated fatty acids and unprocessed carbohydrates and fiber decrease such risks (35, 36). Furthermore, observational and experimental data also suggest that moderate alcohol intake reduces the risk of type 2 diabetes and IHD (37–39). Changes in blood lipid composition, which are well-established risk factors for IHD, only partially explain the effects of diet and alcohol on IHD risk (40). Our observations highlight adiponectin as one novel mediator for the effects of diet on chronic diseases.

Thus far, few studies on the dietary predictors of plasma adiponectin concentrations have been conducted. In animal models, caloric restriction and weight loss were associated with an increase in plasma adiponectin concentrations (41), and it was recently reported that conjugated linoleic acid increases adipose tissue messenger RNA expression and plasma concentrations of adiponectin in obese animal models after 8 wk of feeding (42). In contrast, Polson and Thompson (43) found no effect of diet macronutrient composition on adiponectin messenger RNA expression in white adipose tissue of rats. Xu et al (44) found that chronic intake of high amounts of alcohol, which lead to alcoholic liver disease, may decrease adiponectin concentrations in mice. In our analysis, adiponectin tended to be slightly lower in subjects who consumed >15.0 g alcohol/d than in those who consumed 5.0–14.9 g/d; however, because our study included only a limited number of subjects with a very high alcohol consumption, it is not clear whether a high alcohol intake is associated with a further decrease in adiponectin concentrations.

In humans, Esposito et al (14) found in a randomized controlled trial that a Mediterranean-style diet and increased physical activity, aimed at reducing body weight, significantly decreased body mass index and concomitantly increased plasma adiponectin concentrations in postmenopausal obese women.

Yannakoulia et al (45) found no significant association between macronutrient intake and plasma adiponectin concentrations in a cross-sectional analysis of 114 students after multivariable adjustment. However, food intake in their study was measured by using 3-d food records, which may be less accurate in reflecting long-term dietary intake. Arvidsson et al (46) found no significant differences in adiponectin concentrations between obese women who consumed for 10 wk a hypocaloric moderate-fat, moderate-carbohydrate diet and those who consumed a low-fat, high-carbohydrate diet. However, despite reductions in body weight, this study also failed to show significant accompanying changes in adiponectin concentrations, which may have been due to the limited power of the study or to the fact that the intervention in this study was too short.

Adiponectin shows only a small degree of circadian variability (47) and, therefore, is supposedly involved in long-term rather than short-term regulatory mechanisms (48). In line with these observations, there is only limited within-person variation in plasma adiponectin concentrations over time (29). Also consistent with these findings are data from Peake et al (49), who reported no changes in plasma adiponectin concentrations during the 6 h after intake of a high-fat low-carbohydrate meal. Recently, Sierksma et al (50) examined the effect of alcohol consumption (40 g whiskey/d) on plasma adiponectin concentrations in a randomized crossover trial. They found significantly greater plasma adiponectin concentrations after the consumption, for 17 d, of whiskey (8.78 mg/L) than of water (7.94 mg/L). Taken together, these data and the results of the present study suggest that adiponectin concentrations are unlikely to be affected by acute dietary changes, but rather reflect dietary intakes over more chronic time periods.

Our study had some limitations. The cross-sectional design limited causal inferences; however, the SFFQ was obtained before the blood samples were drawn; thus, reverse causality seems unlikely. The mechanisms that link moderate alcohol consumption to increased adiponectin concentrations are unclear. Although this association was somewhat attenuated after adjustment for HDL-cholesterol concentrations in our cross-sectional analysis, data from Sierksma et al (50) suggest that adiponectin concentrations change independently of HDL-cholesterol concentrations in response to alcohol intake, which indicates that adiponectin is not just a marker of HDL-cholesterol concentrations. Furthermore, we cannot exclude the possibility that adiponectin is merely a marker of insulin sensitivity; however, as indicated above, experimental data suggest that it is rather upstream of insulin resistance in the metabolic pathway. We used body mass index instead of waist-hip ratio to assess abdominal obesity; therefore, we cannot exclude the possibility of residual confounding. Dietary intake was based on self-report; however, measurement error from using self-reported dietary intake and lifestyle variables has been shown to be relatively small (17, 28) and likely does not bias our results because reporting error is not likely associated with the biological measurements. Although the present study does not represent a random sample of the US population, the ranges of anthropometric variables and the biological measures are quite broad and comparable with those of the general male population. Nevertheless, future studies should address dietary predictors of adiponectin concentrations in women. It is currently unknown whether the long-term storage of blood samples affects plasma adiponectin concentrations; however, adiponectin concentrations were not significantly related to storage time in our population, and storage time is unlikely to be related to dietary factors. Adiponectin concentrations may be elevated in patients with overt diabetic nephropathy (51); however, our analysis included a minority of men with diabetes (4.5%), we adjusted for the history of diabetes, and we found essentially the same results when we excluded men with diabetes from our analysis.

In conclusion, we found that moderate alcohol intake is associated with significantly higher adiponectin concentrations, whereas a diet with a high glycemic load was significantly associated and carbohydrate intake tended to be associated with lower adiponectin concentrations. Although the strength of these associations was modest, our observations highlight the hypothesis that dietary factors may modulate plasma concentrations of adiponectin, a potential mediator related to reduced IHD risk.


   ACKNOWLEDGMENTS
 
TP contributed to the study concept and design, the analysis and interpretation of data, the writing and critical revision of the manuscript, and the statistical analysis. CJG contributed to the interpretation of data, the critical revision of the manuscript, and the statistical analysis and helped obtain funds. NR contributed to the interpretation of data, the critical revision of the manuscript, and the acquisition of data (laboratory measurement). GSM contributed to the interpretation of data and the critical revision of the manuscript and helped supervise the progress of the study. EBR contributed to the study concept and design, the acquisition of data, the analysis and interpretation of data, the critical revision of the manuscript, and the statistical analysis; helped obtain funds; and helped supervise the progress of the study. None of the authors had any financial or personal interest in any company or organization sponsoring this research, including advisory board affiliations. CJG is an employee of Merck Research Laboratories, West Point, PA.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

  1. Berg AH, Combs TP, Scherer PE. ACRP30/adiponectin: an adipokine regulating glucose and lipid metabolism. Trends Endocrinol Metab 2002;13:84–9.[Medline]
  2. Chandran M, Phillips SA, Ciaraldi T, Henry RR. Adiponectin: more than just another fat cell hormone? Diabetes Care 2003;26:2442–50.[Free Full Text]
  3. Yamauchi T, Kamon J, Waki H, et al. The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat Med 2001;7:941–6.[Medline]
  4. Berg AH, Combs TP, Du X, Brownlee M, Scherer PE. The adipocyte-secreted protein Acrp30 enhances hepatic insulin action. Nat Med 2001;7:947–53.[Medline]
  5. Maeda N, Shimomura I, Kishida K, et al. Diet-induced insulin resistance in mice lacking adiponectin/ACRP30. Nat Med 2002;8:731–7.[Medline]
  6. Lindsay RS, Funahashi T, Hanson RL, et al. Adiponectin and development of type 2 diabetes in the Pima Indian population. Lancet 2002;360:57–8.[Medline]
  7. Spranger J, Kroke A, Mohlig M, et al. Adiponectin and protection against type 2 diabetes mellitus. Lancet 2003;361:226–8.[Medline]
  8. Kubota N, Terauchi Y, Yamauchi T, et al. Disruption of adiponectin causes insulin resistance and neointimal formation. J Biol Chem 2002;277:25863–6.[Abstract/Free Full Text]
  9. Ouchi N, Kihara S, Arita Y, et al. Adiponectin, an adipocyte-derived plasma protein, inhibits endothelial NF-kappaB signaling through a cAMP-dependent pathway. Circulation 2000;102:1296–301.[Abstract/Free Full Text]
  10. Ouchi N, Kihara S, Arita Y, et al. Adipocyte-derived plasma protein, adiponectin, suppresses lipid accumulation and class A scavenger receptor expression in human monocyte-derived macrophages. Circulation 2001;103:1057–63.[Abstract/Free Full Text]
  11. Arita Y, Kihara S, Ouchi N, et al. Adipocyte-derived plasma protein adiponectin acts as a platelet-derived growth factor-BB-binding protein and regulates growth factor-induced common postreceptor signal in vascular smooth muscle cell. Circulation 2002;105:2893–8.[Abstract/Free Full Text]
  12. Kumada M, Kihara S, Sumitsuji S, et al. Association of hypoadiponectinemia with coronary artery disease in men. Arterioscler Thromb Vasc Biol 2003;23:85–9.[Abstract/Free Full Text]
  13. Pischon T, Girman CJ, Hotamisligil GS, Rifai N, Hu FB, Rimm EB. Plasma adiponectin levels and risk of myocardial infarction in men. JAMA 2004;291:1730–7.[Abstract/Free Full Text]
  14. Esposito K, Pontillo A, Di Palo C, et al. Effect of weight loss and lifestyle changes on vascular inflammatory markers in obese women: a randomized trial. JAMA 2003;289:1799–804.[Abstract/Free Full Text]
  15. Combs TP, Wagner JA, Berger J, et al. Induction of adipocyte complement-related protein of 30 kilodaltons by PPARgamma agonists: a potential mechanism of insulin sensitization. Endocrinology 2002;143:998–1007.[Abstract/Free Full Text]
  16. Rimm EB, Giovannucci EL, Willett WC, et al. Prospective study of alcohol consumption and risk of coronary disease in men. Lancet 1991;338:464–8.[Medline]
  17. Rimm EB, Giovannucci EL, Stampfer MJ, Colditz GA, Litin LB, Willett WC. Reproducibility and validity of an expanded self-administered semiquantitative food frequency questionnaire among male health professionals. Am J Epidemiol 1992;135:1114–26 (discussion 1127–36).[Abstract/Free Full Text]
  18. Prentice RL, Breslow NE. Retrospective studies and failure time models. Biometrika 1978;65:153–8.[Abstract/Free Full Text]
  19. US Department of Agriculture. Composition of foods: raw, processed and prepared, 1966–1991. Washington, DC: US Government Printing Office, 1992.
  20. Wolever TM, Katzman-Relle L, Jenkins AL, Vuksan V, Josse R, Jenkins DJ. Glycemic index of 102 complex carbohydrate foods in patients with diabetes. Nutr Res 1994;14:651–69.
  21. Wolever TM. The glycemic index. World Rev Nutr Diet 1990;62:120–85.[Medline]
  22. Feskanich D, Rimm EB, Giovannucci EL, et al. Reproducibility and validity of food intake measurements from a semiquantitative food frequency questionnaire. J Am Diet Assoc 1993;93:790–6.[Medline]
  23. Salmeron J, Ascherio A, Rimm EB, et al. Dietary fiber, glycemic load, and risk of NIDDM in men. Diabetes Care 1997;20:545–50.[Abstract]
  24. Liu S, Willett WC, Stampfer MJ, et al. A prospective study of dietary glycemic load, carbohydrate intake, and risk of coronary heart disease in US women. Am J Clin Nutr 2000;71:1455–61.[Abstract/Free Full Text]
  25. Giovannucci E, Colditz G, Stampfer MJ, et al. The assessment of alcohol consumption by a simple self-administered questionnaire. Am J Epidemiol 1991;133:810–7.[Abstract/Free Full Text]
  26. Ainsworth BE, Haskell WL, Leon AS, et al. Compendium of physical activities: classification of energy costs of human physical activities. Med Sci Sports Exerc 1993;25:71–80.[Medline]
  27. Rimm EB, Stampfer MJ, Colditz GA, Chute CG, Litin LB, Willett WC. Validity of self-reported waist and hip circumferences in men and women. Epidemiology 1990;1:466–73.[Medline]
  28. Chasan-Taber S, Rimm EB, Stampfer MJ, et al. Reproducibility and validity of a self-administered physical activity questionnaire for male health professionals. Epidemiology 1996;7:81–6.[Medline]
  29. Pischon T, Hotamisligil GS, Rimm EB. Adiponectin: stability in plasma over 36 hours and within-person variation over 1 year. Clin Chem 2003;49:650–2.[Free Full Text]
  30. White H. A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 1980;48:817–38.
  31. Willett W, Stampfer M. Implications of total energy intake for epidemiologic analyses. In: Willett W, ed. Nutritional epidemiology. 2nd ed. New York: Oxford University Press, 1998:273–301.
  32. Krauss RM, Eckel RH, Howard B, et al. AHA dietary guidelines: revision 2000. A statement for healthcare professionals from the Nutrition Committee of the American Heart Association. Circulation 2000;102:2284–99.[Free Full Text]
  33. Franz MJ, Bantle JP, Beebe CA, et al. Evidence-based nutrition principles and recommendations for the treatment and prevention of diabetes and related complications. Diabetes Care 2002;25:148–98.[Free Full Text]
  34. Hill JO, Wyatt HR, Reed GW, Peters JC. Obesity and the environment: where do we go from here? Science 2003;299:853–5.[Abstract/Free Full Text]
  35. Hu FB, Willett WC. Optimal diets for prevention of coronary heart disease. JAMA 2002;288:2569–78.[Abstract/Free Full Text]
  36. Hu FB, van Dam RM, Liu S. Diet and risk of type II diabetes: the role of types of fat and carbohydrate. Diabetologia 2001;44:805–17.[Medline]
  37. Rimm EB, Klatsky A, Grobbee D, Stampfer MJ. Review of moderate alcohol consumption and reduced risk of coronary heart disease: is the effect due to beer, wine, or spirits. BMJ 1996;312:731–6.[Abstract/Free Full Text]
  38. Wannamethee SG, Camargo CA Jr, Manson JE, Willett WC, Rimm EB. Alcohol drinking patterns and risk of type 2 diabetes mellitus among younger women. Arch Intern Med 2003;163:1329–36.[Abstract/Free Full Text]
  39. Howard AA, Arnsten JH, Gourevitch MN. Effect of alcohol consumption on diabetes mellitus: a systematic review. Ann Intern Med 2004;140:211–9.[Abstract/Free Full Text]
  40. Rimm EB, Williams P, Fosher K, Criqui M, Stampfer MJ. Moderate alcohol intake and lower risk of coronary heart disease: meta-analysis of effects on lipids and haemostatic factors. BMJ 1999;319:1523–8.[Abstract/Free Full Text]
  41. Combs TP, Berg AH, Rajala MW, et al. Sexual differentiation, pregnancy, calorie restriction, and aging affect the adipocyte-specific secretory protein adiponectin. Diabetes 2003;52:268–76.[Abstract/Free Full Text]
  42. Nagao K, Inoue N, Wang YM, Yanagita T. Conjugated linoleic acid enhances plasma adiponectin level and alleviates hyperinsulinemia and hypertension in Zucker diabetic fatty (fa/fa) rats. Biochem Biophys Res Commun 2003;310:562–6.[Medline]
  43. Polson DA, Thompson MP. Macronutrient composition of the diet differentially affects leptin and adiponutrin mRNA expression in response to meal feeding. J Nutr Biochem 2004;15:242–6.[Medline]
  44. Xu A, Wang Y, Keshaw H, Xu LY, Lam KS, Cooper GJ. The fat-derived hormone adiponectin alleviates alcoholic and nonalcoholic fatty liver diseases in mice. J Clin Invest 2003;112:91–100.[Medline]
  45. Yannakoulia M, Yiannakouris N, Bluher S, Matalas AL, Klimis-Zacas D, Mantzoros CS. Body fat mass and macronutrient intake in relation to circulating soluble leptin receptor, free leptin index, adiponectin, and resistin concentrations in healthy humans. J Clin Endocrinol Metab 2003;88:1730–6.[Abstract/Free Full Text]
  46. Arvidsson E, Viguerie N, Andersson I, Verdich C, Langin D, Arner P. Effects of different hypocaloric diets on protein secretion from adipose tissue of obese women. Diabetes 2004;53:1966–71.[Abstract/Free Full Text]
  47. Gavrila A, Peng CK, Chan JL, Mietus JE, Goldberger AL, Mantzoros CS. Diurnal and ultradian dynamics of serum adiponectin in healthy men: comparison with leptin, circulating soluble leptin receptor, and cortisol patterns. J Clin Endocrinol Metab 2003;88:2838–43.[Abstract/Free Full Text]
  48. Hotta K, Funahashi T, Arita Y, et al. Plasma concentrations of a novel, adipose-specific protein, adiponectin, in type 2 diabetic patients. Arterioscler Thromb Vasc Biol 2000;20:1595–9.[Abstract/Free Full Text]
  49. Peake PW, Kriketos AD, Denyer GS, Campbell LV, Charlesworth JA. The postprandial response of adiponectin to a high-fat meal in normal and insulin-resistant subjects. Int J Obes Relat Metab Disord 2003;27:657–62.[Medline]
  50. Sierksma A, Patel H, Ouchi N, et al. Effect of moderate alcohol consumption on adiponectin, tumor necrosis factor-alpha, and insulin sensitivity. Diabetes Care 2004;27:184–9.[Abstract/Free Full Text]
  51. Koshimura J, Fujita H, Narita T, et al. Urinary adiponectin excretion is increased in patients with overt diabetic nephropathy. Biochem Biophys Res Commun 2004;316:165–9.[Medline]
Received for publication August 5, 2004. Accepted for publication November 19, 2004.




This article has been cited by other articles:


Home page
 Eur J EndocrinolHome page
M. Yannakoulia, N. Yiannakouris, L. Melistas, E. Fappa, N. Vidra, M. D Kontogianni, and C. S Mantzoros
Dietary factors associated with plasma high molecular weight and total adiponectin levels in apparently healthy women
Eur. J. Endocrinol., October 1, 2008; 159(4): R5 - R10.
[Abstract] [Full Text] [PDF]

Home page
 Diabetes CareHome page
J. W.J. Beulens, E. B. Rimm, F. B. Hu, H. F.J. Hendriks, and K. J. Mukamal
Alcohol Consumption, Mediating Biomarkers, and Risk of Type 2 Diabetes Among Middle-Aged Women
Diabetes Care, October 1, 2008; 31(10): 2050 - 2055.
[Abstract] [Full Text] [PDF]

Home page
 J. Nutr.Home page
P. Perez-Martinez, J. Lopez-Miranda, C. Cruz-Teno, J. Delgado-Lista, Y. Jimenez-Gomez, J. M. Fernandez, M. J. Gomez, C. Marin, F. Perez-Jimenez, and J. M. Ordovas
Adiponectin Gene Variants Are Associated with Insulin Sensitivity in Response to Dietary Fat Consumption in Caucasian Men
J. Nutr., September 1, 2008; 138(9): 1609 - 1614.
[Abstract] [Full Text] [PDF]

Home page
 Clin. Chem.Home page
S. de Ferranti and D. Mozaffarian
The Perfect Storm: Obesity, Adipocyte Dysfunction, and Metabolic Consequences
Clin. Chem., June 1, 2008; 54(6): 945 - 955.
[Abstract] [Full Text] [PDF]

Home page
 Am. J. Clin. Nutr.Home page
M. Kratz, M. M Swarbrick, H. S Callahan, C. C Matthys, P. J Havel, and D. S Weigle
Effect of dietary n-3 polyunsaturated fatty acids on plasma total and high-molecular-weight adiponectin concentrations in overweight to moderately obese men and women
Am. J. Clinical Nutrition, February 1, 2008; 87(2): 347 - 353.
[Abstract] [Full Text] [PDF]

Home page
 J EndocrinolHome page
B. Beck and S. Richy
Differential long-term dietary regulation of adipokines, ghrelin, or corticosterone: impact on adiposity
J. Endocrinol., January 1, 2008; 196(1): 171 - 179.
[Abstract] [Full Text] [PDF]

Home page
 Am. J. Clin. Nutr.Home page
D. Barb, C. J Williams, A. K Neuwirth, and C. S Mantzoros
Adiponectin in relation to malignancies: a review of existing basic research and clinical evidence
Am. J. Clinical Nutrition, September 1, 2007; 86(3): 858S - 866S.
[Abstract] [Full Text] [PDF]

Home page
 NeurologyHome page
O. Y. Bang, J. L. Saver, B. Ovbiagele, Y. J. Choi, S. R. Yoon, and K. H. Lee
Adiponectin levels in patients with intracranial atherosclerosis
Neurology, May 29, 2007; 68(22): 1931 - 1937.
[Abstract] [Full Text] [PDF]

Home page
 J. Clin. Endocrinol. Metab.Home page
A. E. Cust, R. Kaaks, C. Friedenreich, F. Bonnet, M. Laville, A. Lukanova, S. Rinaldi, L. Dossus, N. Slimani, E. Lundin, et al.
Plasma Adiponectin Levels and Endometrial Cancer Risk in Pre- and Postmenopausal Women
J. Clin. Endocrinol. Metab., January 1, 2007; 92(1): 255 - 263.
[Abstract] [Full Text] [PDF]

Home page
 Eur J EndocrinolHome page
J. J. Hernandez-Morante, F. Milagro, J. A. Gabaldon, J. A. Martinez, S. Zamora, and M. Garaulet
Effect of DHEA-sulfate on adiponectin gene expression in adipose tissue from different fat depots in morbidly obese humans.
Eur. J. Endocrinol., October 1, 2006; 155(4): 593 - 600.
[Abstract] [Full Text] [PDF]

Home page
 Diabetes CareHome page
L. Qi, J. B. Meigs, S. Liu, J. E. Manson, C. Mantzoros, and F. B. Hu
Dietary Fibers and Glycemic Load, Obesity, and Plasma Adiponectin Levels in Women With Type 2 Diabetes
Diabetes Care, July 1, 2006; 29(7): 1501 - 1505.
[Abstract] [Full Text] [PDF]

Home page
 Clin. Chem.Home page
T. Pischon and E. B. Rimm
Adiponectin: a promising marker for cardiovascular disease.
Clin. Chem., May 1, 2006; 52(5): 797 - 799.
[Full Text] [PDF]

Home page
 Am. J. Clin. Nutr.Home page
S. E Kasim-Karakas, A. Tsodikov, U. Singh, and I. Jialal
Responses of inflammatory markers to a low-fat, high-carbohydrate diet: effects of energy intake.
Am. J. Clinical Nutrition, April 1, 2006; 83(4): 774 - 779.
[Abstract] [Full Text] [PDF]

Home page
 Am. J. Clin. Nutr.Home page
E. K Kabagambe, A. Baylin, E. Ruiz-Narvaez, E. B Rimm, and H. Campos
Alcohol intake, drinking patterns, and risk of nonfatal acute myocardial infarction in Costa Rica
Am. J. Clinical Nutrition, December 1, 2005; 82(6): 1336 - 1345.
[Abstract] [Full Text] [PDF]

Home page
 CirculationHome page
K. J. Mukamal, M. K. Jensen, M. Gronbaek, M. J. Stampfer, J. E. Manson, T. Pischon, and E. B. Rimm
Drinking Frequency, Mediating Biomarkers, and Risk of Myocardial Infarction in Women and Men
Circulation, September 6, 2005; 112(10): 1406 - 1413.
[Abstract] [Full Text] [PDF]

This Article
Right arrow Abstract Freely available
Right arrow Full Text (PDF)
Right arrow Purchase Article
Right arrow View Shopping Cart
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Right arrow Citation Map
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Pischon, T.
Right arrow Articles by Rimm, E. B
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Pischon, T.
Right arrow Articles by Rimm, E. B
Agricola
Right arrow Articles by Pischon, T.
Right arrow Articles by Rimm, E. B

HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS