The National Cholesterol Education Program's Adult Treatment Panel III (ATP III) defines the metabolic syndrome by easily measured clinical parameters that include: increased abdominal circumference, elevated TAG, low HDL-cholesterol (HDL-C), elevated fasting blood glucose and/or elevated blood pressure (BP). Three of these five are required for diagnosis (National Cholesterol Education Program, 2001).
From the third National Health and Nutrition Examination Survey (NHANES III) (Ford, Reference Ford2004) and the THUSA study (THUSA is the acrynom for Transition and Health during Urbanisation in South Africa, and is also the Tswana word for “help”) (Oosthuizen et al. Reference Oosthuizen, Vorster, Kruger, Venter, Kruger and de Ridder2002) it is evident that the increasing prevalence of the metabolic syndrome is a health problem not only for developed countries but also for developing countries.
This syndrome has been identified as a target for dietary therapies (Wirfalt et al. Reference Wirfalt, Hedblad and Gullberg2001) to reduce the risk of CVD (Shirai, Reference Shirai2004) and type 2 diabetes (Jimenez-Cruz et al. Reference Jimenez-Cruz, Seimandi-Mora and Bacardi-Gascon2003). In lieu of the therapeutics of the metabolic syndrome various researchers have investigated different dietary approaches. Some of the recent dietary interventions range from caloric restriction (Wien et al. Reference Wien, Sabate, Ikle', Cole and Kandeel2003; Muzio et al. Reference Muzio, Mondazzi, Sommariva and Brachi2005), type of diet, e.g. Mediterranean (Esposito et al. Reference Esposito, Marfella and Ciotola2004; Michalsen et al. Reference Michalsen, Lehmann, Pithan, Knoblauch, Moebus, Kannenberg, Binder, Budde and Dobos2006), type and/or amount of dietary fat (Riccardi et al. Reference Riccardi, Giacco and Rivellese2004; Freire et al. Reference Freire, Cardoso, Gimeno and Ferreira2005), amount of carbohydrates (Dansinger & Schaefer, Reference Dansinger and Schaefer2006), increasing the intake of certain minerals (He et al. Reference He, Liu, Daviglus, Morris, Loria, Van Horn, Jacobs and Savage2006) and increasing dietary intake of certain functional foods (e.g. nuts, grapefruit) (Pieters et al. Reference Pieters, Oosthuizen, Jerling, Loots, Mukuddem-Petersen and Hanekom2005; Fujioka et al. Reference Fujioka, Greenway, Sheard and Ying2006).
Riccardi et al. (Reference Riccardi, Giacco and Rivellese2004) concluded that the diet for the treatment of the metabolic syndrome should be limited in the intake of saturated fat, while high-fibre/low-glycaemic index foods should be used without specific limitations (Giacco et al. Reference Giacco, Parillo and Rivellese2000). Recently, in the Framingham Offspring cohort, the researchers found glycaemic index and glycaemic load (a measure of both carbohydrate quality and quantity) were positively associated with the prevalence of the metabolic syndrome (McKeown et al. Reference McKeown, Meigs, Liu, Saltzman, Wilson and Jacques2004).
Epidemiological findings indicate that frequent nut consumption offers protection from fatal and non-fatal CHD events (Sabate, Reference Sabate1993). Nuts have a low glycaemic index (Foster-Powell et al. Reference Foster-Powell, Holt and Brand-Miller2002) and are a rich source of protein, unsaturated fatty acids (MUFA and PUFA), vitamin E, B6, folic acid and niacin, fibre, magnesium, potassium, arginine, phytosterols and other phytochemical compounds (such as polyphenols and ellagic acid) (Dreher et al. Reference Dreher, Maher and Kearney1996). The protective effects of nuts are mediated through several mechanisms. Specifically, the health benefits of walnuts include lowering cholesterol, increasing the ratio of HDL-C to total cholesterol (TC), decreasing TAG and increasing HDL-C, reducing inflammation and improving arterial function in patients with type 2 diabetes and hyperlipidaemia (Ros et al. Reference Ros, Nunez and Perez-Heras2004; Tapsell et al. Reference Tapsell, Gillen, Patch, Batterham, Owen, Bare and Kennedy2004; Zhao et al. Reference Zhao, Etherton, Martin, West, Gillies and Kris-Etherton2004; Zibaeenezhad et al. Reference Zibaeenezhad, Shamsnia and Khorasani2005). Besides our recent contribution (Pieters et al. Reference Pieters, Oosthuizen, Jerling, Loots, Mukuddem-Petersen and Hanekom2005), there is a scarcity of literature on the effects of cashew nut interventions.
In fact, to date there are no other studies that investigated the effects of nuts on either markers of the metabolic syndrome or using subjects with metabolic syndrome. Therefore, the primary objective of the present study was to determine the effects of a high walnut diet and a high unsalted cashew nut diet on markers of this syndrome compared to a control diet. In this contribution we report the effects on the following markers: serum lipids (TC, LDL-cholesterol (LDL-C), HDL-C and TAG), serum fructosamine, plasma glucose, BP, serum uric acid and serum high-sensitivity C-reactive protein (S-hs CRP).
Subjects and methods
All participants gave written informed consent and the study was approved by the Ethics Committee of the Potchefstroom Campus of the North-West University. Sixty-eight White/Caucasian volunteers with the metabolic syndrome were recruited mainly from the Potchefstroom Campus of the North-West University and surrounding areas in Potchefstroom, South Africa. According to the power calculations providing 80 % power at 5 % significance based on LDL-C data from several studies (Chisholm et al. Reference Chisholm, Mann, Skeaff, Frampton, Sutherland, Duncan and Tiszavari1998; Jenkins et al. Reference Jenkins, Kendall and Marchie2002; Lovejoy et al. Reference Lovejoy, Most, Lefevre, Greenway and Rood2002; Sabate et al. Reference Sabate, Haddad, Tanzman, Jambazian and Rajaram2003; Ros et al. Reference Ros, Nunez and Perez-Heras2004), twenty subjects per treatment group were needed to detect a decrease of 15 % (0·6 mmol/l) which might reduce the risk of CVD by more than 20 % (Moruisi et al. Reference Moruisi, Oosthuizen and Opperman2006). The ATP III criteria for the diagnosis of the metabolic syndrome was used. In this regard, the metabolic syndrome was defined as the presence of three or more of the following criteria (Ford et al. Reference Ford, Giles and Dietz2002): abdominal obesity (waist circumference >88 cm for women or >102 cm for men); fasting TAG ≥ 1·7 mmol/l; HDL-C ≤ 1·0 mmol/l for men, HDL-C ≤ 1·3 mmol/l for women; BP ≥ 130/85 mmHg (the use of anti-hypertensive medication was also an indication of high BP) and fasting glucose ≥ 6·1 mmol/l (fasting finger prick blood glucose concentrations were measured with a SureStep™ blood glucose meter (Lifescan Inc., Milpitas, CA, USA), using Fine Point lancets, and SureStep™ test strips (code 11).
Additional inclusion criteria included subjects being able to comply with controlled feeding conditions; being willing and able to eat walnuts and cashew nuts, and participants had to be older than 21 and younger than 65 years. Pregnancy or lactation, thiazide (>25 mg/d) and β-blocker (non-specific, β1 and β2) use, subjects having nut allergies and diagnosed diabetes formed part of the exclusion criteria.
A randomized, controlled, parallel, study design was used. The study protocol consisted of a 3-week run-in period during which the subjects consumed a control diet (percentage of total energy (%E) intake from protein–carbohydrate–fat = 20:47:33; Table 1). After the run-in period participants were grouped according to gender and age and then into three groups by randomly drawing numbers from a hat. Group one received walnuts (n 21), group two received unsalted cashew nuts (n 21), while group three continued with the control diet without any nuts or nut-based ingredients (n 22). Furthermore, these three intervention diets were followed for 8 weeks. Due to practical reasons the study was divided into three cohorts distributed over a 1-year period. All the food was provided to the participants for the duration of the trial. Fasting blood samples, oral glucose tolerance tests, anthropometric measurements and BP measurements were taken before (after the 3-week run-in period) and after the intervention period (8-week controlled feeding). BMI (kg/m2) was calculated. In addition, the weighing of subjects was done twice weekly throughout the run-in period and the experimental phase. The subjects were informed of all aspects of the study before commencement.
† Determined by using the FoodFinder 2 Program (Medical Research Council of South Africa, Tygerberg; mean of 14 d menu).
‡ Laboratory analysis.
§ Calculated with the aid of the glycaemic index and glycaemic load tables of Foster-Powell et al. (Reference Foster-Powell, Holt and Brand-Miller2002).
The proportion of total energy (ranging from 63 to 108 g/d) from nuts was 20 %. Except for the nuts, the diets were identical. This was achieved by making proportional reductions to all food portions in the walnut and the unsalted cashew nut diet menus to accommodate the energy supplied by the respective nuts (Tables 1 and 2). The study featured a highly controlled feeding protocol. In this regard, all subjects were required to have their lunch at the metabolic ward of the Department of Nutrition at the Potchefstroom Campus of the North-West University. Breakfast and dinner were provided in take-away format. Using pre-packed food parcels and a variety of set menu options ensured compliance. On a daily basis 10 % of the total energy intake was calculated in the form of ‘additional points’. In this regard, a list of foods with their associated number of points was provided to the participants. In order to ensure total energy intake and some freedom of choice, participants were advised to choose any foods from the list, provided they added up to the allotted number of points for their respective energy intakes for that day. A validated FFQ and physical activity questionnaire, measuring activity index, were analysed in order to determine the correct energy intake requirements for the maintenance of body weight for each participant. The validated physical activity questionnaire is based on the Baecke physical activity questionnaire (Kruger et al. Reference Kruger, Venter and Steyn2004). Evidence of underreporting was found when the ratio of energy intake to BMR was less than 1·2 (Bingham, Reference Bingham1991; Briefel et al. Reference Briefel, Sempos, McDowell, Chien and Alaimo1997). In the light of this fact, the subjects that underreported were interviewed again by the registered dietitian to obtain a more accurate report on their habitual energy intake.
† Langenhoven et al. (Reference Langenhoven, Kruger, Gouws and Faber1991); Kruger et al. (Reference Kruger, Langenhoven and Faber1992).
‡ Percentage of total fatty acids.
A 14 d menu cycle was designed for five amounts of energy intake, ranging from 8000 to 14 000 kJ/d (1905–3333 kcal/d). It was planned by using the FoodFinder 2 program (Medical Research Council of South Africa, Tygerberg), which is based on the South African food composition tables (Langenhoven et al. Reference Langenhoven, Kruger, Gouws and Faber1991). The macronutrient profiles and fatty acid distribution of the three diets were analysed chemically to validate the diet composition. Duplicate portions of breakfast, lunch and dinner for the 14 d menu cycle were collected daily, homogenized and pooled in a container and frozen at − 84°C until the analysis was done.
Compliance to dietary intervention
Quality control and compliance with the protocol were ensured among study participants by the following means: (1) foods were weighed to the nearest gram before being served to the participants; (2) the principal investigator, a registered dietitian, supervised mealtimes and ensured the complete intake of all study foods; (3) participants kept food diaries of the additional points used and possible left-overs were collected and weighed (by researchers). In addition, any deviation from the study protocol were recorded in these diaries (these diaries were reviewed by the investigators during the study); (4) participants were weighed twice weekly and the energy intake was adjusted (especially during the first 3-week run-in period) in order to maintain body weight; and (5) participants were urged to maintain the same activity level throughout the study. Lastly, those individuals who used chronic medication (e.g. lipid-lowering medication) at baseline were instructed to continue use and to maintain the same dosage for the duration of the trial.
Blood sampling and oral glucose tolerance test
The subjects were required to fast overnight (12 h). A qualified nursing sister collected venous blood samples. For the preparation of serum, 20 ml blood were drawn and left to clot. For determination of plasma glucose concentrations 5 ml blood were collected in tubes containing potassium oxalate (10 mg) and sodium fluoride (12·5 mg).
After the fasting blood samples were collected, the oral glucose tolerance test was continued: 75 g glucose were dissolved in 300 ml water; blood samples for the measurement of glucose were drawn again after 2 h; blood was centrifuged for 15 min at 2000 g to yield serum; aliquots of serum were stored at − 82°C until the analysis was performed.
The fatty acid composition of the nuts and diets was measured by GC as described by van Jaarsveld et al. (Reference van Jaarsveld, Smuts, Tichelaar, Kruger and Benade2000). The percentage protein was analysed by a general combustion method (AOAC Method 992·23; AOAC International, 2002) by using a LECO FP 528 (LECO Corporation, St Joseph, MI, USA), the percentage fat by a GAVIEZEL® method using the Büchi B 820 fat determination system with the Büchi B 815 extraction unit (Büchi Labortechnik AG, Flawil, Switzerland), the percentage fibre by the filter bag technique using the ANKOM 220 fibre analyser with F57 filter bags (ANKOM Technologies, Fairport, NY, USA), the percentage moisture with the air-oven (aluminium plate) method (AACC Method 44-16 l; American Association of Clinical Chemistry, 2003) and percentage ash with the AOAC Method 942·05 (AOAC International, 2002). The carbohydrate content was then calculated as the sum of the protein, fat, fibre, moisture and ash subtracted from 100.
CV for all the laboratory analyses of blood samples were less than 5 %. Serum TC, HDL-C, TAG, uric acid and plasma glucose were measured on a Vitros DT60 II Chemistry System (Ortho-Clinical Diagnostics, Rochester, NY, USA) with Vitros reagents (catalogue numbers 153 2175, 133 5504, 153 2159, 153 2134 and 1532316, respectively) and controls (catalogue numbers 842-0317 and 144-8042). Serum LDL-C was calculated using the Friedewald formula: (LDL-C (mmol/l) = TC − TAG/2·2 − HDL). S-hs CRP was measured using the Synchron LX20® clinical system (Beckman Coulter, Inc., Fullerton, CA, USA). Serum fructosamine was measured with a calorimetric method (catalogue number 1930010; Roche, Basel, Switzerland). BP measurements were obtained by taking a 7 min continuous measurement of cardiovascular parameters using the Finometer™ device (FMS; Finapres Measurement Systems, Arnhem, Netherlands).
The computer software package Statistica® (Statsoft Inc., Tulsa, OK, USA) was used for the analyses of the data. The statistical analysis was done in five steps. Initially, the variables were tested for normality using the Shapiro–Wilk's W test. Non-normally distributed data were transformed into an approximately normal distribution by logarithmic and square-root transformations and again tested for normality. Thereafter, descriptive statistics were done. Data that were normally distributed are expressed as mean and 95 % CI. Data that are not normally distributed or logarithmic and square-root transformed are expressed as median (25, 75 percentiles). Furthermore, changes within groups, from baseline to end, were tested for significance by using the t test for dependent samples in the case of parametric data and the Wilcoxon matched-pairs test in the case of non-parametric data. Also, differences in baseline and Δ (change from baseline to end) between the three groups were determined by using the ANOVA for parametric data and the Kruskal–Wallis ANOVA for non-parametric data. When significance between the changes in the three groups was indicated with the ANOVA, the Tukey honest significant difference test for unequal N for parametric data was used to determine between which groups the differences occurred. Lastly, weight-adjusted differences in baseline and Δ between the three groups were determined by using the analysis of covariance. Significance was set at P ≤ 0·05.
Four subjects discontinued the study for the following reasons: two had work obligations outside Potchefstroom, one had an unrelated medical condition and one went on a holiday during the study period. The remaining sixty-four subjects (twenty-nine men and thirty-five women, aged 45 (sd 10) years) all completed one of the three intervention diets. Compliance with the experimental diets was calculated as 90 %, taking into account the left-overs, food diaries and any deviation from the prescribed dietary protocols. Also, activity level was maintained throughout the study. In this regard, most of the participants had a sedentary lifestyle. The baseline characteristics of the subjects did not differ between groups (ANOVA; Table 3). Most of the subjects were obese (91 %) with high waist circumference values exceeding those indicated by the ATP III criteria. Of the subjects, 53 % had high TAG concentrations, 42 % had high systolic BP, 13 % had high diastolic BP, 91 % had low HDL-C and only 5 % had high fasting glucose concentrations as indicated by the ATP III criteria. At baseline 13 % of subjects had high hs-CRP concentrations, greater than 7·5 mg/l (as indicated by the producers of the diagnostic kit). Evidently, the subject characteristics at baseline were indicative of the metabolic syndrome. Also, of the entire study population only four were smokers (Table 3). Weight, BMI and waist circumference remained unchanged during the intervention period.
WC, waist circumference.
The participants' habitual energy intakes ranged from 5500 to 13 000 kJ/d (1310–3095 kcal/d), however, 52 % of the subjects underreported their energy intake. The chemical analysis of the composition of the diets was comparable to the calculated diets, except for the total fat and carbohydrate content of the walnut diet (Table 1). The analysed fat content was higher because the actual fat content of the walnuts was higher than indicated in the food composition tables (Table 2). All three experimental diets had a low to moderate glycaemic index and glycaemic load (Wolever & Jenkins, Reference Wolever and Jenkins1985; Foster-Powell et al. Reference Foster-Powell, Holt and Brand-Miller2002; Table 1). The composition of walnuts (high in α-linolenic acid and linoleic acid) and cashew nuts (high in oleic acid; Table 2) was reflected in the diets and resulted in the anticipated increase in PUFA and MUFA concentrations, in the diets respectively. In particular, the fatty acid composition of the walnut, cashew nut and control diets (expressed as % of total fatty acids) was 6·42 % α-linolenic acid, 46·31 % linoleic acid, 25·65 % oleic acid; 1·05 % α-linolenic acid, 27·82 % linoleic acid, 43·65 % oleic acid and 0·86 % α-linolenic acid, 27·13 % linoleic acid, 32·88 % oleic acid, respectively.
In Table 4, the serum lipid concentrations displayed no significant changes between walnut, cashew nut and control groups at baseline and in response to the intervention. The subjects in the control diet group showed a small significant increase in HDL-C compared to baseline (Table 4). Results from both nut diets displayed no significant change in HDL-C, TAG, TC or LDL-C concentrations when compared to the baseline.
B, baseline (after 3-week run-in period); B v. E, P values for change from baseline to end of intervention period; E, end; HDL-C, HDL cholesterol; LDL-C, LDL cholesterol; TC, total cholesterol; Δ, change from baseline to end.
* Significance was set at P ≤ 0·05.
Serum fructosamine and plasma glucose
In Table 5, serum fructosamine and plasma glucose (t = 0 min and t = 120 min) showed no significant difference at baseline between groups. Also, there was no significant difference in serum fructosamine between groups after the intervention diets. Plasma glucose concentrations (t = 0) increased significantly by 0·70 mmol/l (P = 0·04) in the cashew nut group compared to the control group. Fructosamine significantly increased in the control diet group at the end of the study period, when compared to the baseline concentrations. The 2 h oral glucose tolerance test showed that there was no significant difference between the groups and when comparing baseline to end values.
B, baseline (after 3-week run-in period); B v. E, P values for change from baseline to end of intervention period; E, end; Δ, change from baseline to end.
Median value was significantly different from that of the control group: *P ≤ 0·05.
Blood pressure, uric acid and serum high-sensitivity C-reactive protein
Of all three intervention diets, systolic and diastolic BP as well as uric acid concentrations displayed no significant change between groups at baseline and from baseline to end. The changes in S-hs CRP did not differ significantly between groups (Table 6). There was a significant increase in S-hs CRP concentrations in the walnut intervention group from baseline to end and no significant change in the cashew nut and control groups when comparing baseline to end values. Although not statistically significant, S-hs CRP was also increased, approximately to the same extent, in the control and cashew nut groups. The increase in the walnut group is, therefore, probably not an independent effect of walnuts.
B, baseline; B v. E, P values for change from baseline to end of intervention period; BP, blood pressure; E, end; S-hs CRP, serum high-sensitivity C-reactive protein; Δ, change from baseline to end.
* Significance was set at P ≤ 0·05.
As far as we know this well-designed parallel, randomized, controlled feeding trial investigating the effects of nuts on participants having the metabolic syndrome is the first study of its kind. Regarding our main objective, we found that both the walnut and the unsalted cashew nut intervention diets had no significant effect on the HDL-C, TAG, TC, LDL-C, serum fructosamine, S-hs CRP, BP and serum uric acid concentrations when compared to the control diet. Plasma glucose concentrations increased significantly in the cashew nut group compared to the control group.
In a recent systematic review (Mukuddem-Petersen et al. Reference Mukuddem-Petersen, Oosthuizen and Jerling2005), it was concluded from randomized controlled intervention trials that the consumption of 50–100 g (approximately 1·5–3·5 servings) of nuts five or more times/week as part of a heart healthy diet with a total fat content (high in MUFA and/or PUFA) of approximately 35 %E may significantly decrease TC and LDL-C. In lieu of the dynamic make-up of nuts, it deserves a mention that this decrease is not solely due to the changes in the fatty acid composition that results when nuts are included in the diet, but also as a result of the other components found in nuts.
Contrary to the outcomes of the present controlled feeding trial, four out of seven well-designed walnut studies (40–84 g/d) displayed a significant decrease in TC and LDL-C when compared to Step I (healthy; Sabate et al. Reference Sabate, Fraser, Burke, Knutsen, Bennett and Lindsted1993), Mediterranean (hypercholesterolaemic; Zambon et al. Reference Zambon, Sabate and Munoz2000; Ros et al. Reference Ros, Nunez and Perez-Heras2004) and Japanese (healthy; Iwamoto et al. Reference Iwamoto, Imaizumi and Sato2002) diets. The average %E from fat in the aforementioned nut diets and the control diets were 31 and 29 %, respectively. Two of the studies that showed no significant change in the lipid profile of hyperlipidaemic subjects who followed a walnut intervention diet (64–78 g/d) when compared to a low-fat (30 %E from fat) and Step I diet (33 %E from fat) provided ≥ 38 %E from fat (Chisholm et al. Reference Chisholm, Mann, Skeaff, Frampton, Sutherland, Duncan and Tiszavari1998; Morgan et al. Reference Morgan, Horton, Reese, Carey, Walker and Capuzzi2002), suggesting that the beneficial effects of nuts disappear with high fat intakes. Similarly, in the current study, the walnut diet (60–100 g/d) was high in fat (41 %E from fat) compared to the control diet (33 %E from fat). However, high-PUFA diets, similar to the walnut diet in the current study, are predicted to reduce TC and LDL-C concentrations (Mensink & Katan, Reference Mensink and Katan1992). Based on the predictive equations of Mensink & Katan (Reference Mensink and Katan1992), which predict changes in TC and LDL-C concentrations according to changes in the fatty acid content of the diet, the walnut diet should have reduced the TC and LDL-C concentrations with 0·34 and 0·30 mmol/l, respectively, compared to the control diet. The lack of effect can possibly be ascribed to the low TC and LDL-C concentrations of the subjects at baseline, as these low concentrations make it difficult to show a further benefit.
Most of the walnut studies to date did not show an effect on HDL-C and TAG concentrations (Mukuddem-Petersen et al. Reference Mukuddem-Petersen, Oosthuizen and Jerling2005). Sabate et al. (Reference Sabate, Fraser, Burke, Knutsen, Bennett and Lindsted1993) showed a decrease in HDL-C that could possibly have been due to the high PUFA content on the walnut diet (17 %E) compared to the control diet (10 %E). High intakes of PUFA (>10 %E) may decrease HDL-C (Riccardi et al. Reference Riccardi, Rivellese, Williams, Gibney, Macdonald and Roche2003). Although the PUFA content of the walnut diet in the current study was also much higher compared to the control diet (21·4 v. 9·5 %E), the HDL-C did not differ between the diets.
As no clinical trials have been done on cashew nuts before, we considered almond studies as they are similar in composition to cashew nuts. We expected the cashew nut study to have a beneficial effect on TC and LDL-C concentrations as seen in previous almond nut studies. In this context three out of four well-designed almond studies (54–100 g/d) ranging from 32 to 39 %E from fat, significantly decreased TC and LDL-C in hypercholesterolaemic (Spiller et al. Reference Spiller, Jenkins, Bosello, Gates, Cragen and Bruce1998; Jenkins et al. Reference Jenkins, Kendall and Marchie2002) and normocholesterolaemic (Sabate et al. Reference Sabate, Haddad, Tanzman, Jambazian and Rajaram2003) subjects compared to subjects on a control diet (35 %E from fat), low-fat (26·3 %E from fat) and Step I diet (30 %E from fat) (Sabate et al. Reference Sabate, Haddad, Tanzman, Jambazian and Rajaram2003). In the present study, the cashew nut (66–115 g/d) diet (37 %E from fat) had no significant beneficial effect on the lipid profile (Table 4) when compared to the control diet that is lower in fat (33 %E from fat). This outcome was very similar to results found by Lovejoy et al. (Reference Lovejoy, Most, Lefevre, Greenway and Rood2002) who showed that 57–113 g almonds/d (39 %E from fat) had no significant beneficial effect on the lipid profile of diabetic subjects when compared to a high-fat (37 %E from fat) control group. The same outcome was achieved when the same amount of almonds (27 %E) as part of a low-fat diet was compared to a low-fat (26 %E from fat) control diet (Lovejoy et al. Reference Lovejoy, Most, Lefevre, Greenway and Rood2002). Based on differences in fatty acid content of the cashew nut and control diets in the current study the predicted reductions in TC and LDL-C concentrations with the cashew nut diet were very small ( − 0·14 mmol/l for both TC and LDL-C). However, it has been shown that nuts may reduce TC and LDL-C concentrations beyond the effects predicted based solely on fatty acid profiles (Mukuddem-Petersen et al. Reference Mukuddem-Petersen, Oosthuizen and Jerling2005). As mentioned earlier, the low TC and LDL-C concentrations at baseline might explain the lack of effects. Other possible reasons for the non-significance in lipid concentrations need to be explored.
No direct studies have been done to investigate the effects of nuts on BP. Despite this, we anticipated an improvement in the BP readings with the walnut and cashew nut diets based on their fatty acid composition. In particular, emerging research has suggested possible health benefits associated with modest increases in dietary α-linolenic acid (walnuts), including reduced BP (Ferrara et al. Reference Ferrara, Raimondi, D'Episcopo, Guida, Dello and Marotta2000; Hermansen, Reference Hermansen2000; Hunter, Reference Hunter1990). Also, numerous studies conducted in healthy and hypertensive individuals have shown a beneficial effect of MUFA (cashew nuts) on a number of outcomes related to cardiovascular risk, including BP (Roche et al. Reference Roche, Zampelas and Knapper1998). However, no improvement in BP readings was seen after the nut intervention diets in the current controlled feeding trial.
Zhao et al. (Reference Zhao, Etherton, Martin, West, Gillies and Kris-Etherton2004) concluded that a diet high in α-linolenic acid, obtained from walnuts, walnut oil and flaxseed oil, elicited cardioprotective effects and vascular anti-inflammatory effects. Regarding the latter, it has been reported that walnuts are amongst the dietary plants that contain the most antioxidants (Halvorsen et al. Reference Halvorsen, Holte and Myhrstad2002) and several health effects have been ascribed to flavonoids (antioxidants) including reduced inflammation (Nijveldt et al. Reference Nijveldt, van Nood, van Hoorn, Boelens, van Norren and van Leeuwen2001). In the present study, the walnut diet (high in α-linolenic acid) resulted in an increase in S-hs CRP concentrations, although this was probably not an independent effect of walnuts. Recently, some evidence has been presented for a beneficial effect of MUFA on a number of outcomes related to cardiovascular risk, including reduced inflammation (Ferrara et al. Reference Ferrara, Raimondi, D'Episcopo, Guida, Dello and Marotta2000). Consequently, a cashew nut diet (high in MUFA) could be expected to improve the inflammatory parameter CRP. However, this was not evident in the present study.
Numerous studies compared a low-fat diet (21 %; 23 %; 29 %E from fat; Luscombe et al. Reference Luscombe, Noakes and Clifton1999; Thomsen et al. Reference Thomsen, Rasmussen, Christiansen, Pedersen, Vesterlund, Storm, Ingerslev and Hermansen1999; Rodriguez-Villar et al. Reference Rodriguez-Villar, Manzanares, Casals, Perez-Heras, Zambon, Gomis and Ros2000; Perez-Jimenez et al. Reference Perez-Jimenez, Lopez-Miranda, Pinillos, Gomez, Paz-Rojas, Montilla, Marin, Velasco, Blanco-Molina, Jimenez Pereperez and Ordovas2001) to a high-MUFA diet (35 %; 40 %E from fat; Luscombe et al. Reference Luscombe, Noakes and Clifton1999). The results of these studies provided similar glycaemic control. Those authors concluded that provided the intake of SFA is low, a MUFA diet with a total fat content of up to 40 %E has effects on glycaemic control that are similar to those of the traditional high-carbohydrate diet with fat limited to 25–30 %E. An almond nut study conducted by Lovejoy et al. (Reference Lovejoy, Most, Lefevre, Greenway and Rood2002) showed no effect on plasma glucose concentrations compared to a low-fat (26 %E from fat) control group (olive and rapeseed oil) in diabetics. In contrast to these previous findings, the significant increase of the plasma blood glucose (t = 0) seen in the cashew nut diet (high MUFA; 36·5 %E from fat) group was unexpected. Even though serum fructosamine is a short-term marker of glycaemic control, its concentrations remained unchanged in the cashew nut group compared to the control group that increased. It could be speculated that the aforementioned increase in serum fructosamine concentrations in the control group may be due to this group having lower baseline values compared to the other two groups.
ATP III recommends that obesity should be the primary target of intervention for the metabolic syndrome. In turn, the first line of therapy should be weight reduction reinforced with increased physical activity. A notion related to this is evident in the study by Esposito et al. (Reference Esposito, Marfella and Ciotola2004) where they displayed how a Mediterranean diet (high in MUFA and PUFA) that included nuts, weight loss and increased physical activity resulted in a significant reduction in S-hs CRP amongst other beneficial anti-inflammatory responses.
In conclusion, individuals having the metabolic syndrome showed no improvement in the markers of this syndrome after following a walnut diet or a cashew nut diet (8 weeks) compared to a control diet while maintaining body weight. Most of the study population was obese (average BMI 35) and sedentary therefore it could be speculated that with such a high degree of obesity that even a ‘good diet including nuts’ would not suffice in inducing beneficial effects without weight loss. Firstly, it may be suggested that maintenance of body weight may have masked the positive metabolic effects of the nut diets. Especially, if these diets mediate its beneficial effects mainly through central appetite suppression and consequent body weight reduction. Wien et al. (Reference Wien, Sabate, Ikle', Cole and Kandeel2003) showed how a low-energy nut diet resulted in sustained weight reduction and improved the preponderance of abnormalities associated with the metabolic syndrome. Future nut research on these aspects are worthy of exploration.
A sincere word of thanks to M. C. Lessing, E. Pienaar, Z. White, A. Greyling, C. de Witt, J. Wheeler, J. Bekker, C. Jansen van Rensburg, M. Bailey, L. Loots, V. van Scheltinga, L. Wiggett, L. Davies, L. van Wyk, E. Snyman, F. Mpho and T. Holele, A. Schutte, H. Huisman, J. van Rooyen, S. Jordaan, F. van der Westhuizen, C. S. Venter, H. H. Wright, H. S. Kruger, H. van't Riet, R. Breet, A. Van Graan, M. van Lieshout, D. Loots, M. Pieters-Loots, K. Moruisi, M. Opperman and M. Phometsi for contributing in various ways to the successful execution and completion of the controlled feeding trial – The Nut Study. Financial support was received from The National Research Foundation (NRF) and the South African governments' Technology and Human Resources for Industry Program (THRIP). Various food donations for the controlled feeding trial were received from the following food companies: Tiger Brands, Pick 'n Pay, Clover and Unilever. We declare that we have no conflict of interest.