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American Journal of Clinical Nutrition, Vol. 88, No. 5, 1213-1224, November 2008
© 2008 American Society for Nutrition

ORIGINAL RESEARCH COMMUNICATION

Adherence to healthy eating patterns is associated with higher circulating total and high-molecular-weight adiponectin and lower resistin concentrations in women from the Nurses' Health Study1,2,3

Jessica L Fargnoli, Teresa T Fung, Deanna M Olenczuk, John P Chamberland, Frank B Hu and Christos S Mantzoros

1 From the Division of Endocrinology, Diabetes, & Metabolism, Department of Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (JLF, DMO, JPC, and CSM); the Department of Nutrition, Simmons College, Boston, MA (TTF); the Departments of Nutrition (TTF and FBH) and Epidemiology (FBH), Harvard School of Public Health, Boston, MA; and the Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA (FBH)

2 Supported by grants no. HL65582, HL60712, HL34594, DK58785, DK79929, and DK58845 from the National Institutes of Health; a discretionary grant from the Beth Israel Deaconess Medical Center; and the American Heart Association Established Investigator Award (to FBH).

3 Reprints not available. Address correspondence to C Mantzoros, Division of Endocrinology, Diabetes, & Metabolism, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, ST816, Boston, MA 02115. E-mail: cmantzor{at}bidmc.harvard.edu.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Adherence to a healthy dietary pattern, such as the Alternate Healthy Eating Index (AHEI), is associated with a lower risk of diabetes and atherosclerosis.

Objective: We aimed to determine whether adherence to the AHEI is associated with higher plasma total and high-molecular-weight (HMW) adiponectin concentrations and lower concentrations of resistin, as well as biomarkers of inflammation, endothelial dysfunction, and insulin resistance.

Design: The study evaluated 1922 women from the Nurses' Health Study (62% of whom were overweight) who had no history of diabetes or cardiovascular disease. Their plasma biomarker concentrations were measured in 1990, and data on dietary intake from semiquantitative food-frequency questionnaires administered in 1984, 1986, and 1990 were averaged to account for long-term dietary exposure and to reduce within-subject variability.

Results: After adjustment for age and energy intake, women with the highest adherence to the AHEI had 24% higher median total adiponectin and 32% higher median HMW adiponectin concentrations, as well as 16% lower resistin, 41% lower CRP, 19% lower sE-selectin, and 24% lower ferritin concentrations (P < 0.01 for all) than did women with the lowest adherence to the AHEI. These associations remained significant after adjustment for potential confounders. Inverse associations between the AHEI and soluble tumor necrosis factor-{alpha} receptor II, interleukin-6, soluble intercellular adhesion molecule 1, soluble vascular cell adhesion molecule 1, C-peptide, insulin, and glycated hemoglobin were evident, but they were not significant after adjustment for body mass index.

Conclusion: The preventive effects of healthier dietary patterns on risk for diabetes and atherosclerosis may be mediated by improvements in plasma concentrations of adipokines or other biomarkers of risk for diabetes and cardiovascular disease.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Adiponectin is an adipose tissue–secreted, metabolically active cytokine that is inversely associated with obesity and central adiposity and that has been shown to improve insulin sensitivity, to regulate glucose and lipid metabolism, and to have pronounced anti-atherosclerotic effects (1-4). Adiponectin is present in plasma in 3 forms: a trimer, a hexamer, and a high-molecular-weight (HMW) form, which has been proposed as the most active form (5). Prospective studies have shown that higher plasma adiponectin concentrations are associated with lower risks of diabetes mellitus and cardiovascular disease (CVD; 6-9); however, the relation between adiponectin and CVD has not been confirmed in all studies (10). Currently available data remain inconclusive as to whether plasma HMW adiponectin concentrations are an independent or more useful predictor (or both) of metabolic abnormalities and CVD than are total adiponectin concentrations (11, 12).

Resistin, another adipocyte-secreted hormone, was originally reported as a potential linkage between obesity and both insulin resistance and diabetes (13). Initial data in mice showing that resistin can induce insulin resistance or impair hepatic sensitivity to insulin (14) have not, however, been confirmed by all studies (15). Further studies in humans have questioned the relation between resistin expression and obesity, insulin resistance, or type 2 diabetes (16-18). Subsequent research has shown that resistin is structurally similar to proteins involved in the inflammatory process (19), and several cross-sectional and prospective studies suggested that resistin is an adipokine associated with a pro-inflammatory state and, possibly, atherosclerosis (20-22).

In women, lower plasma concentrations of several biomarkers of inflammation and endothelial dysfunction (23) and lower risks of type 2 diabetes (24) and CVD (25) are associated with higher scores on the Alternate Healthy Eating Index (AHEI), a measure of adherence to a healthy diet. These changes are independent of differences in body mass index (BMI) and could potentially be mediated through changes in plasma adipokine concentrations. Although concentrations of several adipokines were previously associated with modifiable lifestyle factors, including diet and exercise (26-28), and although adherence to healthy dietary patterns, including a Mediterranean dietary pattern, was previously shown to be independently associated with higher plasma adiponectin concentrations in diabetic women (29), healthy dietary patterns have not been previously studied in relation to HMW adiponectin and resistin. Moreover, associations between the AHEI and the concentrations of ferritin, insulin, C-peptide, and glycated hemoglobin (HbA1c) have not previously been studied.

We hypothesized that close adherence to a healthy dietary pattern, as measured by the AHEI, would be independently associated with higher plasma concentrations of total and HMW adiponectin and with lower concentrations of resistin and other biomarkers of inflammation, endothelial dysfunction, and insulin resistance.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Study population
The Nurses' Health Study began in 1976 when 121 700 female nurses aged 30–55 y and residing in 11 US states were enrolled. All participants received biennially mailed questionnaires regarding lifestyle factors and medical history. From 1989 to 1990, blood samples were obtained from 32 826 study participants who were free of diagnosed diabetes, coronary heart disease, stroke, or cancer. The current analysis includes 1922 women who were selected for a previous nested case-control study of diabetes and who had no history of CVD, cancer, or diabetes at the time the blood was drawn.

Written informed consent to participate in the Nurses’ Health Study was obtained. The study was approved by the committees for the protection of human subjects at the Harvard School of Public Health and the Brigham and Women's Hospital.

Assessment of dietary intake and diet scores
The dietary intake of Nurses' Health Study participants was assessed by using a semiquantitative food-frequency questionnaire (SFFQ), the validity and reliability of which were previously described (30, 31). Data used in the present study were obtained from the 1984, 1986, and 1990 SFFQs. Diet data were averaged to account for long-term dietary exposure and to reduce within-subject variability. For each food item in the questionnaire, study participants chose from 9 possible frequency responses ranging from "never" to "≥6 times/d."

The AHEI was scored on the basis of the intake levels of 9 components chosen for their proven associations with disease and mortality risk in epidemiologic and clinical studies (25). These components include fruit, vegetables, the ratio of white meat (seafood and poultry) to red meat, trans fat, the ratio of polyunsaturated fat to saturated fat (P:S), cereal fiber, nuts and soy, moderate alcohol consumption (0.5–1.5 servings/d), and long-term multivitamin use (<5 or >5 y). Each component had the potential to contribute 0–10 points to the total score, with the exception of multivitamin use, which contributed either 2.5 or 7.5 points to avoid overweighting of the dichotomous variable. Scores on the AHEI range from 2.5 to 87.5; higher scores represent a healthier diet.

Assessment of plasma biomarker concentrations
Blood samples were collected in 1989 and 1990 as previously described (32). Phlebotomy kits were sent to women consenting to provide blood samples. Participants made arrangements for their blood to be drawn, and samples were returned by overnight mail in a frozen container, centrifuged and separated into aliquots on arrival, and stored at temperatures of –130 °C or below in liquid nitrogen. Quality-control samples were routinely frozen along with study samples to monitor for plasma changes due to long-term storage and to monitor assay variability. The long-term stability of plasma samples collected and stored under these conditions was reported previously (33). Total adiponectin concentrations were measured by using a radioimmunoassay (Linco Research, St Charles, MO), which has a sensitivity of 2 µg/mL and an intraassay CV of 1.8–6.2% for adiponectin (34). Serum HMW adiponectin concentrations were determined by an enzyme-linked immunosorbent assay method (Millipore, St Charles, MO) with a sensitivity of 0.5 ng/mL.

Measurement of plasma adiponectin concentrations from a single blood sample was previously reported to be reasonably representative over a long period, with a high BMI-adjusted intraclass correlation coefficient (r = 0.73) over a 3-y period (35). Moreover, the stability of adiponectin in blood shipped on ice has been reported to be good (36). Resistin was assayed by using an enzyme-linked immunosorbent assay (Linco Research Inc). The minimum detectable range of this assay is 0.16 ng/mL; intraassay CVs were 3.2–7.0%. In this study, the CV for total adiponectin, HMW adiponectin, and resistin based on blinded quality-control samples was 8.9%, 9.9%, and 2.5%, respectively. Assays for tumor necrosis factor-{alpha} (TNF-{alpha}) receptor II (sTNF-{alpha}RII), C-reactive protein (CRP), interleukin-6 (IL-6), soluble intercellular adhesion molecule 1 (sICAM-1), soluble vascular cell adhesion molecule 1 (sVCAM-1), soluble E-selectin (sE-selectin), insulin, HbA1c, C-peptide, proinsulin, and ferritin were described in detail elsewhere (32, 37-39). The CVs for the analytes in the present study were 6.2% for sTNF-{alpha}RII, 3.8% for CRP, 5.9% for IL-6, 3.56% for sICAM-1, 8.5–10.2% for sVCAM-1, 6.6% for E-selectin, 9.5% for fasting insulin, 3.8% for HbA1c, 6.9% for C-peptide, 7.3% for proinsulin, and 3.75% for ferritin.

Assessment of covariates
Age, body weight, smoking status (current, past, or never), medication use, and occurrence of hypertension and hypercholesterolemia were determined in 1990 by a questionnaire that is updated every 2 y. A history of hypertension or hypercholesterolemia was determined on the basis of physician-diagnosed high blood pressure or high cholesterol, as reported by the subjects on the questionnaires. BMI (in kg/m2) was calculated. Waist-to-hip ratio was determined by using self-reported waist and hip circumference information from 1986. Self-reported waist circumference has been shown to have a strong correlation to measured waist circumference (r = 0.89) in the Nurses' Health Study cohort (32). A history of hypertension and a family history of myocardial infarction were determined from self-reports before blood collection (40). Total caloric intake was obtained from the abovementioned SFFQ (30).

Statistical analysis
Descriptive characteristics were compared across dietary pattern score groups by using one-way analysis of variance for continuous variables and chi-square tests for categorical variables. Associations of plasma biomarker concentrations across quintiles of AHEI score were determined by using simple linear regression models for crude analysis and multiple linear regression to adjust for possible confounders. Biomarker concentrations were logarithmically transformed to more closely approximate normal distribution. In multivariate analysis, we adjusted for potential confounders. Model 1 adjusted for total energy intake (by quintile) and age (<50, 50–54, 55–59, 60–64, 65–69, or ≥70 y). Model 2 included all variables from Model 1 and additionally adjusted for physical activity (by quintile) and smoking status (current, past, or never). Model 3 included all variables from Model 2 and additionally adjusted for BMI (<25, 25–29, 30–34, 35–39, or ≥40). During analysis, we performed additional adjustments for thiazide diuretics, other blood pressure medications, and cholesterol medications, but these variables did not affect the results and thus were not included in the final models. Biomarkers that were significantly associated with the AHEI were included in an additional model that adjusted for the other significant biomarkers. We examined the interaction between the AHEI score and physical activity level, age, BMI, smoking status, and history of hypertension and hypercholesterolemia. For biomarkers that were significantly associated with the AHEI, multivariate linear regression was conducted to examine their associations with the specific components of the dietary score. Additional analysis was conducted by using dietary data from 1990 only. Multivariate linear regression analyses were also performed to examine the relations between the biomarkers and quintiles of free and total choline intake. All analyses were conducted by using SAS for UNIX statistical software (version 9.0; SAS Institute, Cary, NC).


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Lifestyle and medical history characteristics of the study population by quintile of AHEI score are presented in Table 1Go. Women with the highest scores tended to be older and to have lower BMIs and waist-to-hip ratios and higher daily energy intake and weekly physical activity. They also were less likely to be current smokers and more likely to have a medical history of hypercholesterolemia but not hypertension. There were no significant differences across quintiles of AHEI score with respect to use of blood pressure–and cholesterol-lowering medications. Women with the highest scores had significantly higher mean total and HMW adiponectin concentrations and significantly lower concentrations of resistin, sTNF-{alpha}RII, IL-6, CRP, sE-selectin, sICAM-1, sVCAM-1, insulin, and HbA1c. No significant differences between quintiles of AHEI score were seen for ferritin or C-peptide.


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  		TABLE 1. Baseline characteristics and biomarker concentrations of 1922 women by quintile (Q) of average Alternate Healthy Eating Index (AHEI) score from 1984 to 19901

 
Spearman correlation coefficients for the associations between AHEI score, anthropometric and lifestyle characteristics, and the biomarkers of interest are shown in Table 2Go. The AHEI was most strongly correlated with physical activity (r = 0.31). Total and HMW adiponectin also were positively correlated with the AHEI (r = 0.14), as was age (r = 0.18). The AHEI was inversely correlated with BMI (r = –0.12), resistin (r = –0.12), TNF-{alpha}RII (r = –0.11), IL-6 (r = –0.08), CRP (r = –0.09), sE-selectin (r = –0.13), sICAM (r = –0.07), C-peptide (r = –0.14), insulin (r = –0.13), and HbA1c (r = –0.10).


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  		TABLE 2. Spearman correlation coefficients between diet-quality scores, covariates, and adipokines for 1922 women1

 
Modeled median biomarker concentrations across quintiles of AHEI score are presented in Table 3Go. Subjects with the highest adherence to the AHEI had significantly higher total and HMW adiponectin concentrations than did subjects with the lowest adherence. After adjustment for age and energy intake, women in the highest quintile of AHEI score had 24% higher median total adiponectin concentrations than did women in the lowest quintile (15.68 and 12.61 µg/mL, respectively) and 32% higher median HMW adiponectin concentrations (5.71 and 4.34 µg/mL, respectively). This association remained after adjustment for weekly physical activity, smoking status, and BMI. Further adjustment for history of hypertension and hypercholesterolemia did not alter the results (data not shown).


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  		TABLE 3. Modeled biomarker concentrations by quintile (Q) of average Alternate Healthy Eating Index (AHEI) score from 1984 to 1990 for 1922 women1

 
Higher scores on the AHEI also were significantly associated with lower plasma resistin concentrations. After adjustment for energy intake and age, those in the highest quintile of AHEI score had 16% lower plasma resistin concentrations than did those in the lowest quintile (15.19 and 18.06 ng/mL, respectively). This relation remained significant after full multivariate adjustment (17.54 and 19.41 ng/mL, respectively). The AHEI also was inversely associated with plasma CRP, sE-selectin, and ferritin concentrations. After adjustment for age and energy intake, women in the highest quintile had 41% lower median CRP concentrations, 19% lower sE-selectin concentrations, and 24% lower ferritin concentrations than did women in the lowest quintile. These associations remained statistically significant after further adjustment for physical activity, smoking status, and BMI and after further adjustment for history of hypertension and hypercholesterolemia.

An inverse relation between AHEI and the biomarkers of insulin resistance was shown after adjustment for age and energy intake. Women with the highest average adherence to the AHEI had 29% lower C-peptide, 21% lower insulin, and 10% lower HbA1c concentrations (P < 0.01 for all) than did those with the lowest average adherence, but the statistical significance of these associations was attenuated after adjustment for BMI. Nevertheless, there was suggestive evidence of a trend for C-peptide and HbA1c after multivariate adjustment (P = 0.06 and 0.07, respectively). After adjustment for age and energy intake, women with the highest average adherence to the AHEI had 10% lower sTNF-{alpha}RII, 22% lower IL-6, 9% lower sICAM-1, and 5% lower sVCAM-1 concentrations than did women with the lowest average adherence (P < 0.01 for all). The AHEI was inversely associated with plasma sTNF-{alpha}RII, IL-6, sICAM-1, and sVCAM-1 concentrations after adjustment for age, energy intake, physical activity, and smoking status; however, none of these relations remained significant after adjustment for BMI. An additional cross-sectional analysis was conducted with the use of dietary data from 1990 only; the direction and magnitude of the relations were similar for all biomarkers.

Each biomarker that was significantly associated with the AHEI after multivariate adjustment was included in a final model with adjustment for the other significant biomarkers. In the final model, total adiponectin and resistin remained significantly associated with the AHEI (P = 0.01 for both). The association of sE-selectin and ferritin with the AHEI became borderline (P = 0.08 for both). After adjustment for the other biomarkers, the statistical significance of a relation of the AHEI with CRP (P = 0.21) and HMW adiponectin (P = 0.13) was attenuated, and the effect estimates were reduced by 45.6% and 29.8%, respectively.

For biomarkers with a significant multivariate association with the AHEI, further analysis was conducted to investigate relations between the biomarkers and individual components of the dietary pattern (Table 4Go and Table 5Go). Both total and HMW adiponectin concentrations were significantly positively associated with multivitamin use and alcohol consumption, even after simultaneous adjustment for the other components of the dietary score. Women who used multivitamins for ≥5 y had 13% higher plasma total adiponectin and 16% higher HMW adiponectin concentrations in 1990, after adjustment for age and caloric intake, than did women who did not use multivitamins for 5 y. These associations remained statistically significant after adjustment for BMI and lifestyle and medical history variables. After adjustment for age and energy intake, women with the highest quintile of alcohol consumption had 28% higher plasma total adiponectin and 45% higher HMW adiponectin concentrations than did women who did not consume alcohol after adjustment for age and energy intake. There were few heavy drinkers in this cohort of women: median alcohol intake in the highest quintile was {approx}1 serving/d, which likely explains the linear association seen between alcohol consumption and adiponectin concentrations. After multivariate adjustment and adjustment for the other biomarkers, both total and HMW adiponectin remained significantly associated with alcohol consumption. Both total and HMW adiponectin were significantly inversely associated with P:S, but only total adiponectin showed a significant inverse association with the daily intake of trans fats.


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  		TABLE 4. Modeled biomarker concentrations for 1922 women by quintile (Q) of Alternate Healthy Eating Index (AHEI) score component1

 

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  		TABLE 5. Modeled biomarker concentrations for 1845 women by duration of multivitamin use1

 
Plasma resistin concentrations in the highest quintile of P:S were 14% lower than those in the lowest quintile. These associations remained significant after full multivariate adjustment. Plasma sE-selectin, CRP, and ferritin concentrations also were significantly inversely associated with the ratio of white meat to red meat consumption. Women in the highest quintile of this ratio had 9% lower sE-selectin, 28% lower CRP, and 31% lower ferritin concentrations after control for age and energy intake than did women in the lowest quintile. These relations remained statistically significant after multivariate adjustment.

Because the beneficial effects of the Mediterranean diet were recently associated with a higher intake of choline (41), additional analysis was performed among this sample of women to determine whether greater concentrations of free and total choline were associated with plasma adipokine concentrations (Table 6Go). In univariate analysis, free choline–contributing metabolite was significantly associated with higher concentrations of total and HMW adiponectin and lower concentrations of resistin. Women in the highest quintile of free choline intake had 20% higher median total adiponectin concentrations, 28% higher HMW adiponectin concentrations, 11% lower resistin concentrations, and 33% lower CRP concentrations, after adjustment for age and energy intake, than did women in the lowest quintile. Results for total and HMW adiponectin and CRP remained statistically significant after adjustment for weekly physical activity, smoking status, and BMI. None of the other biomarkers were significantly associated with free choline; nor were any of the biomarkers significantly associated with quintiles of total choline in univariate analysis (data not shown). These results were not significantly altered by multivariate adjustment.


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  		TABLE 6. Modeled biomarker concentrations for 1922 women by quintile (Q) of free choline intake1

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
We report that a higher AHEI score, which reflects a healthier dietary pattern, is positively and independently associated with total and HMW plasma adiponectin concentrations and inversely associated with plasma resistin, CRP, sE-selectin, and ferritin concentrations in women with no history of CVD or diabetes. In the present study of 1922 women, we found that closer adherence to the AHEI was associated with 24% higher median total adiponectin and 32% higher median HMW adiponectin concentrations, as well as 16% lower resistin concentrations, 41% lower CRP concentrations, 19% lower sE-selectin concentrations, and 24% lower ferritin concentrations, independent of energy intake and age. Control for anthropometric, lifestyle, and medical history covariates explained some of the observed associations, but the increase in total and HMW adiponectin concentrations and the decrease in resistin, CRP, sE-selectin, and ferritin concentrations in those closely adhering to the AHEI remained significant. Data also were suggestive of a trend for inverse associations between the AHEI and HbA1c, insulin, and C-peptide, all of which are biomarkers reflecting aspects of glycemic control and insulin resistance.

The associations between the AHEI and total and HMW adiponectin, resistin, and ferritin and the borderline inverse associations with insulin, C-peptide, and HbA1c are novel. We also confirm previously reported inverse relations with CRP and sE-selectin, which are independent of BMI and lifestyle and medical history variables (23). After mutual adjustment for the other biomarkers, the relation between the AHEI and total adiponectin and resistin remained statistically significant, whereas associations between the AHEI and sE-selectin, ferritin, CRP, and HMW adiponectin were attenuated. Thus, the observed relation with the biomarkers of inflammation, endothelial dysfunction, and insulin resistance may be mediated by an underlying association between diet quality (ie, AHEI scores) and total adiponectin and resistin. Healthy dietary patterns, such as a Mediterranean-type diet, were associated with higher total adiponectin concentrations in women in an observational study (29). An interventional study also found that adherence to a Mediterranean diet coupled with weight loss increased adiponectin concentrations in study subjects (42). In addition, our observation of an inverse association with resistin is consistent with and extends previously proven negative associations between the AHEI and other biomarkers of inflammation in multivariate models (23), independent of BMI. Although previous interventional studies did not result in lower plasma resistin concentrations after dietary interventions to decrease body weight and restrict caloric intake (27, 28, 43), consumption of a higher-quality diet, as expressed by the AHEI, appears to have a more direct effect on resistin concentrations than does reduction of daily caloric intake and body weight. Similarly, adherence to a healthy diet may have effects on plasma adiponectin, CRP, sE-selectin, and ferritin concentrations beyond the effects of improvement in BMI. In contrast, the inverse associations between the biomarkers of insulin resistance and soluble TNF-{alpha}RII, IL-6, sICAM-1, and sVCAM-1 were attenuated by adjustment for BMI, which suggests that the effects of a high-quality dietary pattern on these biomarkers may be mediated by that pattern's effects on obesity.

Although the results were not statistically significant, the present study showed a trend toward an inverse association between AHEI score and biomarkers of insulin resistance. These data are consistent with a recent report that higher AHEI scores are associated with a lower risk of type 2 diabetes in women (24). It remains to be studied whether the beneficial effects of closer adherence to the AHEI on diabetes risk and, possibly. cardiovascular risk would be mediated in part through an association with one or more of these biomarkers, independent of age, BMI, and other lifestyle factors.

Certain individual components of the AHEI may have influenced the observed relations with the studied biomarkers more than others. In particular, strong positive associations of alcohol intake with total and HMW adiponectin were observed, as were inverse associations of alcohol intake with resistin and sE-selectin. Alcohol consumption was previously associated with greater insulin sensitivity in a large prospective study (44), and that relation may be partially mediated by the biomarkers studied in the present study. Nonetheless, the effects of adherence to the AHEI on each of these biomarkers were greater than the effects of alcohol consumption. Similarly, lower resistin concentrations with higher AHEI scores were also partially mediated by a higher intake of cereal fiber and a higher P:S, but these associations were not greater than the effect of the dietary pattern. Beneficial effects of the AHEI on plasma adiponectin, resistin, CRP, and sE-selectin concentrations appear to be due to the dietary pattern as a whole and not to a single component; however, further interventional studies should be conducted to determine whether any one component or the AHEI dietary pattern most strongly affects circulating biomarker concentrations.

Elevated ferritin concentrations have been reported to increase the risk of type 2 diabetes (39) and may also be a marker of systemic inflammation in persons who are overweight. Women with the highest AHEI scores had lower plasma ferritin concentrations; however, this relation may largely be due to lower red meat consumption as evidenced by the 31% lower ferritin concentrations in women with the highest ratios of white to red meat intake. The association between ferritin and AHEI score also was partially attenuated by adjustment for BMI. Further research should be conducted to determine whether healthy dietary patterns, such as the AHEI, or a simple change, such as lower red meat intake, has the strongest effect on plasma ferritin concentrations.

The present study can show associations but cannot prove causality, and thus the results reported herein should be interpreted as being "hypothesis generating." A strength of the present study is its focus on clinically important biomarkers that have not previously been studied. Moreover, this analysis was conducted among a large sample of healthy women with the use of dietary data that had been collected in the 6 y before biomarkers were measured. We also had detailed information on potential confounders and were able to control for these confounders in multivariate analyses; however, the potential for residual confounding cannot be eliminated. The present study provides important information that advances our understanding of human physiology and that could prove useful for the prevention and, if confirmed by interventional studies, possibly also for the treatment of diabetes and CVD. The present study may have been limited by the fact that blood samples were stored over a long period; however, samples were stored at –130 °C, which makes degradation unlikely. This fact and the fact that analysis was based on a single blood measure of study outcome variables could potentially lead to random misclassification; random measurement error in the assessment of the exposures or outcomes may have attenuated reported associations, leading to suppressed effect estimates.

In conclusion, adherence to a healthier diet, as reflected by a higher AHEI score, is associated with higher plasma total and HMW adiponectin and lower plasma resistin, CRP, sE-selectin, and ferritin concentrations independent of obesity and lifestyle factors. In addition, women with a healthier diet as described by the AHEI may have improved plasma insulin, HbA1c, C-peptide, TNF-{alpha}RII, sICAM, and sVCAM concentrations mediated through improvements in BMI. This possibility supports the hypothesis that beneficial effects of healthier dietary patterns with respect to risk of insulin resistance, diabetes, and atherosclerosis may be partially mediated by improvements in plasma concentrations of adipokines or other biomarkers for diabetes and CVD risk. Future studies should extend these findings by investigating potential mechanisms underlying these relations and by examining whether prevention of the metabolic syndrome, diabetes, and atherosclerosis by lifestyle modifications is mediated through changes in clinically important biomarkers, including adiponectin and resistin concentrations.


   ACKNOWLEDGMENTS
 
The authors' responsibilities were as follows—JLF: analyzed the data, wrote the first draft of the manuscript, and finalized the manuscript; DMO and JC: conducted laboratory measurements; TTF and FBH: critically reviewed the manuscript draft and made suggestions for additional analysis; CSM: supervised laboratory measurements, guided the statistical analysis, wrote an outline of the draft of the manuscript and revised subsequent versions, and coordinated the study; and all authors: participated in manuscript revision and approved the final version. None of the authors had a personal or financial conflict of interest.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication June 2, 2008. Accepted for publication July 11, 2008.




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S. Li, H. J. Shin, E. L. Ding, and R. M. van Dam
Adiponectin Levels and Risk of Type 2 Diabetes: A Systematic Review and Meta-analysis
JAMA, July 8, 2009; 302(2): 179 - 188.
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