OBJECTIVE

We examined the impact of adherence to the Alternative Healthy Eating Index (AHEI), a set of dietary guidelines targeting major chronic diseases, on metabolic syndrome (MetS) reversion in a middle-aged population.

RESEARCH DESIGN AND METHODS

Analyses were carried out on the 339 participants (28% women, mean age 56.4 years) from the Whitehall II study with MetS as defined by the National Cholesterol Education Program Adult Treatment Panel III criteria. Reversion was defined as not having MetS after 5 years of follow-up (158 case subjects).

RESULTS

After controlling for potential confounders, adherence to AHEI was associated with MetS reversion (odds ratio 1.88 [95% CI 1.04–3.41]), predominantly in participants with central obesity and in those with high triglyceride.

CONCLUSIONS

Our findings support the benefit of adherence to AHEI dietary guidelines for individuals with MetS, especially those with central obesity or high triglyceride levels.

The metabolic syndrome (MetS), prevalence estimated at between 10 and 25% in adult populations worldwide (1), is associated with an increased risk of type 2 diabetes and cardiovascular diseases (CVDs). Lifestyle modification, such as increased physical exercise (2) and diet therapies (3,4), may have a beneficial impact on MetS. We examined a set of dietary guidelines targeting major chronic diseases known as the Alternative Healthy Eating Index (AHEI) (5). Our goal was to examine whether adherence to AHEI was associated with reversion of the MetS over a 5-year period in a middle-aged population.

Data came from phases 3 (1991–1993), 5 (1997–1999), and 7 (2002–2004) of the Whitehall II study of London-based office workers (6). From the 3,698 participants with complete data on MetS at phases 3 and 5, diet and covariates at phase 5, and MetS reversion between phases 5 and 7, the 339 case subjects with MetS at phase 5 formed the study population for the main analysis.

At each phase, MetS was defined using the National Cholesterol Education Program Adult Treatment Panel III criteria (7). The definition of each MetS component and details of other measurements are given in the footnote of Table 1 and have been described previously (8). The 5-year reversion of MetS was defined as not having MetS at phase 7.

Table 1

Association between adherence to the AHEI and 5-year reversion of the MetS

Model 1*Model 2
Total 339   
    Low AHEI score 115 (48) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 111 (50) 1.20 (0.69–2.08) 1.15 (0.65–2.05) 
    High AHEI score 113 (60) 1.73 (0.99–3.02) 1.88 (1.04– 3.41) 
P  0.05 0.04 
Subcohort with central obesity 212   
    Low AHEI score 71 (25) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 76 (30) 1.34 (0.67–2.67) 1.29 (0.61–2.76) 
    High AHEI score 65 (33) 2.35 (1.12–4.96) 2.77 (1.19–6.44) 
P  0.025 0.02 
Subcohort with high triglycerides 294   
    Low AHEI score 103 (43) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 92 (38) 1.07 (0.58–1.94) 1.01 (0.54–1.89) 
    High AHEI score 99 (54) 1.92 (1.06–3.49) 1.94 (1.04–3.65) 
P  0.03 0.04 
Subcohort with low HDL cholesterol 198   
    Low AHEI score 65 (28) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 60 (27) 1.00 (0.47–2.12) 1.03 (0.45–2.36) 
    High AHEI score 73 (38) 1.37 (0.67–2.81) 1.58 (0.70–3.55) 
P  0.36 0.26 
Subcohort with hypertension 279   
    Low AHEI score 98 (45) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 90 (42) 1.09 (0.60–1.99) 1.08 (0.57–2.02) 
    High AHEI score 91 (48) 1.48 (0.80–2.73) 1.61 (0.84–3.08) 
P  0.21 0.15 
Subcohort with high glucose 131   
    Low AHEI score 39 (13) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 51 (22) 1.48 (0.59–3.70) 1.41 (0.51–3.89) 
    High AHEI score 41 (21) 2.08 (0.80–5.43) 2.52 (0.81–7.88) 
P  0.13 0.11 
Model 1*Model 2
Total 339   
    Low AHEI score 115 (48) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 111 (50) 1.20 (0.69–2.08) 1.15 (0.65–2.05) 
    High AHEI score 113 (60) 1.73 (0.99–3.02) 1.88 (1.04– 3.41) 
P  0.05 0.04 
Subcohort with central obesity 212   
    Low AHEI score 71 (25) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 76 (30) 1.34 (0.67–2.67) 1.29 (0.61–2.76) 
    High AHEI score 65 (33) 2.35 (1.12–4.96) 2.77 (1.19–6.44) 
P  0.025 0.02 
Subcohort with high triglycerides 294   
    Low AHEI score 103 (43) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 92 (38) 1.07 (0.58–1.94) 1.01 (0.54–1.89) 
    High AHEI score 99 (54) 1.92 (1.06–3.49) 1.94 (1.04–3.65) 
P  0.03 0.04 
Subcohort with low HDL cholesterol 198   
    Low AHEI score 65 (28) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 60 (27) 1.00 (0.47–2.12) 1.03 (0.45–2.36) 
    High AHEI score 73 (38) 1.37 (0.67–2.81) 1.58 (0.70–3.55) 
P  0.36 0.26 
Subcohort with hypertension 279   
    Low AHEI score 98 (45) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 90 (42) 1.09 (0.60–1.99) 1.08 (0.57–2.02) 
    High AHEI score 91 (48) 1.48 (0.80–2.73) 1.61 (0.84–3.08) 
P  0.21 0.15 
Subcohort with high glucose 131   
    Low AHEI score 39 (13) 1.00 (reference) 1.00 (reference) 
    Intermediate AHEI score§ 51 (22) 1.48 (0.59–3.70) 1.41 (0.51–3.89) 
    High AHEI score 41 (21) 2.08 (0.80–5.43) 2.52 (0.81–7.88) 
P  0.13 0.11 

Data are n, number of participants (number of reversion cases), or odds ratio (95% CI) for MetS reversion. MetS was defined using the NCEP definition (7) based on the presence of three or more of the following: waist circumference (men >102 cm, women >88 cm), serum triglycerides (≥1.7 mmol/l), HDL cholesterol (men <1.04 mmol/l, women <1.29 mmol/l), blood pressure (≥130/≥85 mmHg systolic over diastolic pressure), fasting glucose (≥6.1 mmol/l), or presence of type 2 diabetes. Waist circumference was taken as the smallest circumference at or below the costal margin. Resting blood pressure was measured with the participant seated using the Hawksley random zero sphygmomanometer (phases 3 and 5) and the OMRON HEM 907 (phase 7). Serum triglycerides, HDL cholesterol, and fasting blood glucose were analyzed as previously described (8).

*Model 1: adjusted for sex, age, ethnicity, and energy intake.

†Model 2: model 1 additionally adjusted for education, marital status, smoking habits, physical activity, persistence of MetS, and depressive symptoms.

‡Low AHEI adherence: median (range), 39.5 (3.5–43.5).

§Intermediate AHEI adherence: 50.5 (44.5–55.5).

‖High AHEI adherence: 62.5 (56.5—76.5).

P value of the comparison between high vs. low AHEI score.

Dietary intake data were collected via a validated 127-item food frequency questionnaire (FFQ) (910) at both phases 3 and 5. AHEI score (5) was created by summing its nine component scores (1/fruits, 2/vegetables, 3/ratio of white to red meat, 4/trans fat, 5/ratio of polyunsaturated to saturated fat, 6/total fiber, 7/nuts and soy, 8/alcohol consumption, and 9/long-term multivitamin use); a higher score corresponded to greater adherence (online appendix Table A1, available at http://care.diabetesjournals.org/cgi/content/full/dc09-2200/DC1). We used the AHEI measures in two ways: the phase 5 score was used for the main analysis, and the average AHEI score across phases 3 and 5 was used to take into account longer-term adherence to AHEI in a subsidiary analysis on the 337 participants with complete dietary data from phases 3 and 5. Levels of AHEI adherence at phase 5 were comparable to those reported in two large American cohorts (5) (online appendix Table A2).

Logistic regression models examined the association between tertiles of the AHEI scores at phase 5 and reversion of MetS and of its components at phase 7, sequentially adjusted for age, sex, ethnicity (White, non-White) and total energy intake (kcal/day) (model 1) and additionally for educational attainment (no academic qualification, lower secondary, higher secondary, university degree, higher university degree), marital status (married or cohabiting, living alone), smoking (current, former, nonsmoker), persistence of MetS at phase 5 (having MetS at both phases 3 and 5), depressive symptoms, and intensity of physical activity (high, medium, low) (8) (model 2). No significant interaction between AHEI scores and covariates (including sex) was observed. Analysis was conducted using the SAS software, version 9.1 (SAS Institute).

Among the 339 participants with MetS at phase 5, 158 (46.6%) recovered by phase 7. Characteristics of the participants (as a function of MetS reversion and AHEI category) are shown in online appendix Tables A3 and A4. After controlling for potential confounders, adherence to AHEI was associated with increased odds of MetS reversion over the 5-year follow-up (Table 1). This association was stronger among participants with MetS at both phases 3 and 5 (n of reversions/total n = 56/155, odds ratio 3.74 [95% CI 1.37–10.2]). The AHEI-to-MetS reversion association was particularly evident among participants with central obesity and among those with high triglycerides (Table 1). Furthermore, adherence to AHEI was associated with a 5-year reversion of the high triglyceride component (n = 276/767, 1.61 [1.12–2.33]) but the association with reversion of central obesity did not reach statistical significance (n = 75/481, 1.42 [0.75–2.68]). Analyses with average AHEI score across phases 3 and 5 as the exposure largely replicated these findings (online appendix Table A5).

In the present report, we show that adherence to dietary guidance for healthy eating, the AHEI, is associated with reversion of the MetS in a middle-aged population. Although several studies have investigated the diet-to-MetS prevalence and incidence relationships, the impact of diet on MetS reversion has only been studied in two clinical trials assessing adherence to the Mediterranean diet in two Mediterranean countries. One trial of 180 Italian subjects found the Mediterranean diet intervention to lead to reversion of MetS (3), the other larger trial (n = 1,224, Spanish) suggested that the observed effect was due to the effect of nut supplements rather than the Mediterranean diet as a whole (4). Even though the clinical utility of MetS as an independent predictor of CVD has been challenged (11), our findings, from a non-Mediterranean country, are novel and strengthen evidence of the potential impact of diet in countering increasing levels of risk factors associated with CVD and type 2 diabetes.

We observed a stronger impact of AHEI on MetS reversion in participants with central obesity and high triglycerides. Among all baseline MetS case subjects, AHEI was associated with reversion of the high triglyceride component but not the central obesity component. Thus, reduction of visceral fat (12) leading to a decrease in the flux of free fatty acids and increased insulin resistance—a key feature in MetS pathophysiology (13)—seems an unlikely explanation for our findings. However, further research is needed to examine these and other plausible mechanisms. These may include counteracting oxidative stress (and related insulin resistance) (14) via antioxidants from fruits, vegetables, and long-term multivitamin use and the lowering of high triglyceride levels—linked to reduction of inflammation processes involved in MetS (15)—as a result of increased consumption of polyunsaturated fat, nuts, and soy and a reduced consumption of trans fat.

Limitations of this study include the small sample size that does not fully represent the British population (6) and that does not allow ethnic group substratification other than White or non-White, thereby limiting the generalizability of our findings; the lack of objective measure of physical activity; and the use of the FFQ, recognized to be less precise than diary questionnaires, to assess diet.

Despite these limitations, our findings emphasize the potential benefits of adherence to the dietary recommendations of the AHEI in middle-aged individuals with MetS, especially those with central obesity or high triglyceride levels.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

The Whitehall II study is supported by grants from the British Medical Research Council (MRC); the British Heart Foundation; the British Health and Safety Executive; the British Department of Health; the National Heart, Lung, and Blood Institute (R01HL036310); the National Institute on Aging (R01AG013196 and R01AG034454); the Agency for Health Care Policy and Research (Grant HS06516); and the John D. and Catherine T. MacArthur Foundation Research Networks on Successful Midlife Development and Socioeconomic Status and Health. T.N.A. was supported by the BUPA Foundation (U.K.). A.S.-M. is supported by a European Young Investigator Award from the European Science Foundation. J.E.F. is supported by the MRC (Grant G8802774) and M.G.M. by an MRC research professorship. M.J.S. is supported by the British Heart Foundation. M.K. is supported by the Academy of Finland and the BUPA Foundation, U.K. Continuing data collection on this study is funded by the MRC, National Institute on Aging (R01AG013196, R01AG034454); the National Heart, Lung, and Blood Institute (R01HL036310); and the British Heart Foundation. This study was additionally supported by the BUPA Foundation, U.K., and the Academy of Finland.

The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

No potential conflicts of interest relevant to this article were reported.

T.N.A. designed the study, conducted the analyses, cowrote the initial and final drafts and is guarantor. A.S.-M. designed the study and reviewed/edited the manuscript. A.G.T., M.J., and M.V. reviewed/edited the manuscript. J.E.F. designed the study and reviewed/edited the manuscript. M.G.M. designed the study. M.J.S. advised on the analysis and reviewed/edited the manuscript. M.K. designed the study, helped in planning the analyses, and cowrote the initial and final drafts.

T.N.A. had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

The authors thank all participating men and women in the Whitehall II Study; all participating Civil Service departments and their welfare, personnel, and establishment officers; the Occupational Health and Safety Agency; and the Council of Civil Service Unions. The Whitehall II study team comprises research scientists, statisticians, study coordinators, nurses, data managers, administrative assistants, and data entry staff who make the study possible.

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Supplementary data