Mozaffarian, D., T. Hao, E.B. Rimm, W.C. Willett, F.B. Hu, 2011. Changes in diet and lifestyle and long-term weight gain in women and men. N Engl J Med 2011; 364:2392-2404.
Background: Specific dietary and other lifestyle behaviors may affect the success of the straightforward-sounding strategy “eat less and exercise more” for preventing long-term weight gain. Methods: We performed prospective investigations involving three separate cohorts that included 120,877 U.S. women and men who were free of chronic diseases and not obese at baseline, with follow-up periods from 1986 to 2006, 1991 to 2003, and 1986 to 2006. The relationships between changes in lifestyle factors and weight change were evaluated at 4-year intervals, with multivariable adjustments made for age, baseline body-mass index for each period, and all lifestyle factors simultaneously. Cohort-specific and sex-specific results were similar and were pooled with the use of an inverse-variance–weighted meta-analysis. Results: Within each 4-year period, participants gained an average of 3.35 lb (5th to 95th percentile, −4.1 to 12.4). On the basis of increased daily servings of individual dietary components, 4-year weight change was most strongly associated with the intake of potato chips (1.69 lb), potatoes (1.28 lb), sugar-sweetened beverages (1.00 lb), unprocessed red meats (0.95 lb), and processed meats (0.93 lb) and was inversely associated with the intake of vegetables (−0.22 lb), whole grains (−0.37 lb), fruits (−0.49 lb), nuts (−0.57 lb), and yogurt (−0.82 lb) (P≤0.005 for each comparison). Aggregate dietary changes were associated with substantial differences in weight change (3.93 lb across quintiles of dietary change). Other lifestyle factors were also independently associated with weight change (P<0.001), including physical activity (−1.76 lb across quintiles); alcohol use (0.41 lb per drink per day), smoking (new quitters, 5.17 lb; former smokers, 0.14 lb), sleep (more weight gain with <6 or >8 hours of sleep), and television watching (0.31 lb per hour per day). Conclusions: Specific dietary and lifestyle factors are independently associated with long-term weight gain, with a substantial aggregate effect and implications for strategies to prevent obesity.
Kendall C.W., A. Esfahani, A.R. Josse, L.S. Augustin, E. Vidgen, D.J. Jenkins, 2011. The glycemic effect of nut-enriched meals in healthy and diabetic subjects. Nutr. Metab. Cardiovasc. Dis. 21(Suppl 1):S34-9.
BACKGROUND AND AIMS: The intake of nuts has been linked to a reduced risk of cardiovascular disease (CVD) and diabetes in large cohort studies. One potential contributing mechanism may be the ability of nuts to improve post-meal glycemic response. We, therefore, examined the effect of nuts alone and in combination with white bread on postprandial glycemia. METHODS AND RESULTS: 30, 60 and 90 g (approximately 1, 2 and 3 ounces) of mixed nuts were consumed with and without 50 g available carbohydrate from white bread by 10-14 normoglycemic and 5-10 type 2 diabetic subjects. Glycemic response (GR) was assessed by calculating the incremental area under the 2 h blood glucose curve. All three doses of mixed nuts, when fed alone, significantly reduced the glycemic response in both normoglycemic and diabetic patients. Furthermore, in the normoglycemic subjects, adding nuts to white bread progressively reduced the GR of the meal by 11.2 ± 11.6%, 29.7 ± 12.2% and 53.5 ± 8.5% for the 30, 60, and 90 g doses (P = 0.354, P = 0.031 and P < 0.001, respectively), while in subjects with type 2 diabetes, the effect was half of that seen in the non-diabetic subjects (P = 0.474, P = 0.113 and P = 0.015, respectively). CONCLUSION: Nuts alone have little effect on post-meal blood glucose response. Furthermore, when taken with bread, nuts progressively reduce the glycemic response in a dose-dependent manner. While these findings support a short-term benefit for nuts in postprandial glucose response, more studies are required to determine whether these acute benefits result in long-term improvements in glycemic control.
Martínez-González, M.A., M. Bes-Rastrollo, 2011. Nut consumption, weight gain and obesity: Epidemiological evidence. Nutr Metab Cardiovasc Dis. 21(Suppl 1):S40-5.
BACKGROUND AND AIMS: Short-term trials support that adding tree nuts or peanuts to usual diets does not induce weight gain. We reviewed the available epidemiological evidence on long-term nut consumption and body weight changes. We also report new results from the SUN (“Seguimiento Universidad de Navarra”) cohort. METHODS AND RESULTS: Published epidemiologic studies with ≥1-yr follow-up were located. Two published reports from large cohorts (SUN and Nurses Health Study-2) showed inverse associations between frequency of nut consumption and long-term weight changes. A beneficial effect of a Mediterranean diet supplemented with tree nuts on waist circumference was reported after 1-yr follow-up in the first 1224 high-risk participants in the PREDIMED (“PREvencion DIeta MEDiterranea”) trial. After assessing 11,895 participants of the SUN cohort, a borderline significant (p value for trend = 0.09) inverse association between baseline nut consumption and average yearly weight gain (multivariate-adjusted means = 0.32 kg/yr (95% confidence interval: 0.22-0.42) and 0.24 (0.11-0.37) kg/yr for participants with no consumption and >4 servings/week, respectively) was found after a 6-yr follow-up. CONCLUSIONS: Consumption of nuts was not associated with a higher risk of weight gain in long-term epidemiologic studies and clinical trials.
Salas-Salvadó J, Casas-Agustench P, Salas-Huetos A., 2011. Cultural and historical aspects of Mediterranean nuts with emphasis on their attributed healthy and nutritional properties. Nutr Metab Cardiovasc Dis. 21(Suppl 1):S1-6.
BACKGROUND AND AIMS: Nuts have been part of the human diet since prehistoric times. The aim of the present article is to describe the most important historical and cultural aspects of nut consumption throughout history. DATA SYNTHESIS: We discuss the following historical aspects of nuts originating in the Mediterranean: prehistory, the Egyptian civilization, their spread through the Mediterranean region by the Greek, Phoenician and Roman civilizations, and their reintroduction into Europe by means of the Al-Andalus culture. Particular emphasis is placed on the healthy and nutritional attributes that nuts have had throughout history. We also consider the role of the first globalization of food–the exchange of nuts between continents–and discuss the symbolism that nuts have had for humans throughout history in the context of cultural aspects of the Mediterranean region. CONCLUSIONS: Nuts and fruits are probably the earliest foods consumed by humans and are considered to be important because of their nutritional properties. Nuts have also been used in the past by different civilizations as drugs to prevent or treat several diseases.
Kochar, J., J.M. Gaziano, L. Djousse, 2010. Nut consumption and risk of type II diabetes in the Physicians’ Health Study. European Journal of Clinical Nutrition. 64:75–79.
Background/Objectives: While type II diabetes (DM) is a major cause of morbidity in the United States, limited data are available on the association between nut intake and incident DM. We sought to examine the association between nut consumption and the risk of DM. Subjects/Methods: Prospective cohort of 20 224 male participants of the Physicians’ Health Study I. Nut consumption was estimated using a 19-item brief food frequency questionnaire, and incident DM was ascertained through yearly follow-up questionnaires. Cox regression was used to estimate relative risks of DM. Results: The average age of the study participants was 54.4±9.4 years (range: 40.7–87.1). During a mean follow-up of 19.2 years, 1828 cases of DM occurred. The crude incidence rates of DM were 4.82, 4.85, 4.92, 4.16, 4.29 and 3.32 cases per 1000 person-years for individuals reporting nut consumption of rarely/never, <1, 1, 2–4, 5–6 and 7+ servings per week, respectively. While nut consumption was associated with a lower risk of DM in a model adjusted for age (P for tend 0.017), such relation was attenuated on additional control for other confounders (multivariable adjusted hazard ratios (95% confidence interval) for DM were 1.0 (reference), 1.06 (0.93–1.20), 1.10 (0.95–1.26), 0.97 (0.82–1.14), 0.99 (0.76–1.30) and 0.87 (0.61–1.24) from the lowest to the highest category of nut consumption, respectively (P for trend 0.99). No statistically significant association between nut consumption and DM was found in either lean or overweight/obese participants. Conclusions: Our data do not show an association between nut consumption and incident DM in US male physicians.
Sabate´, J., K. Oda, E. Ros, 2010. Nut Consumption and Blood Lipid Levels A Pooled Analysis of 25 Intervention Trials. Arch Intern Med. 170(9):821-827.
Background: Epidemiological studies have consistently associated nut consumption with reduced risk for coronary heart disease. Subsequently, many dietary intervention trials investigated the effects of nut consumption on blood lipid levels. The objectives of this study were to estimate the effects of nut consumption on blood lipid levels and to examine whether different factors modify the effects. Methods: We pooled individual primary data from 25 nut consumption trials conducted in 7 countries among 583 men and women with normolipidemia and hypercholesterolemia who were not taking lipid-lowering medications. In a pooled analysis, we used mixed linear models to assess the effects of nut consumption and the potential interactions. Results: With a mean daily consumption of 67 g of nuts, the following estimated mean reductions were achieved: total cholesterol concentration (10.9 mg/dL [5.1% change]), low-density lipoprotein cholesterol concentration (LDL-C) (10.2 mg/dL [7.4% change]), ratio of LDL-C to high-density lipoprotein cholesterol concentration (HDL-C) (0.22 [8.3% change]), and ratio of total cholesterol concentration to HDL-C (0.24 [5.6% change]) (P<.001 for all) (to convert all cholesterol concentrations to millimoles per liter, multiply by 0.0259). Triglyceride levels were reduced by 20.6 mg/dL (10.2%) in subjects with blood triglyceride levels of at least 150 mg/dL (P<.05) but not in those with lower levels (to convert triglyceride level to millimoles per liter, multiply by 0.0113). The effects of nut consumption were dose related, and different types of nuts had similar effects on blood lipid levels. The effects of nut consumption were significantly modified by LDL-C, body mass index, and diet type: the lipid-lowering effects of nut consumption were greatest among subjects with high baseline LDL-C and with low body mass index and among those consuming Western diets. Conclusion: Nut consumption improves blood lipid levels in a dose-related manner, particularly among subjects with higher LDL-C or with lower BMI.
Kendall, C.W.C., A.R. Josse, A. Esfahani, D. J. A. Jenkins, 2010. Nuts, metabolic syndrome and diabetes. British Journal of Nutrition. 104(4): 465-473.
The ability of nuts to improve the blood lipid profile and reduce the risk of CHD is now well established. The interest that health effects of nuts have gained recently has brought the possible benefits of consuming nuts, such as improvement in the conditions of the metabolic syndrome, and their potential to prevent and control diabetes into focus. Results from cohort studies have associated nut consumption with a reduced risk of developing diabetes and CVD. However, few randomised controlled trials have assessed the effect of nuts on diabetes control, and those that have been undertaken have shown improvements in blood lipids but not in the glycaemic control. Diabetes agencies are increasingly recognising the importance of controlling postprandial glycaemia fluctuations. Acute feeding studies indicate that nuts have minimal effects on rising postprandial blood glucose levels when eaten alone, and diminish the postprandial glycaemic response when consumed with high-glycaemic index carbohydrate foods in both normoglycaemic and type 2 diabetic individuals. Nuts have a healthy nutritional profile, high in MUFA and PUFA, are a good source of vegetable protein and are rich in fibre, vitamins and minerals. Incorporation of nuts in the diet may therefore improve the overall nutritional quality of the diet. While more research is required to establish the ability of nuts to improve glycaemic control in the long run, early data indicate that the inclusion of nuts in the diets of individuals with diabetes and the metabolic syndrome is warranted, in view of their potential to reduce CHD risk.
Casas-Agustench P., M. Bulló, E. Ros, J. Basora, J. Salas-Salvadó; on behalf of the Nureta-PREDIMED investigators, 2011. Cross-sectional association of nut intake with adiposity in a Mediterranean population. Nutr Metab Cardiovasc Dis. 21(7):518-525.
BACKGROUND AND AIMS: Nut intake has been inversely related to body mass index (BMI) in prospective studies. We examined dietary determinants of adiposity in an elderly Mediterranean population with customarily high nut consumption. METHODS AND RESULTS: A cross-sectional study was conducted in 847 subjects (56% women, mean age 67 years, BMI 29.7kg/m(2)) at high cardiovascular risk recruited into the PREDIMED study. Food consumption was evaluated by a validated semi-quantitative questionnaire, energy expenditure in physical activity by the Minnesota Leisure Time Activity questionnaire, and anthropometric variables by standard measurements. Nut intake decreased across quintiles of both BMI and waist circumference (P-trend <0.005; both). Alcohol ingestion was inversely related to BMI (P-trend=0.020) and directly to waist (P-trend=0.011), while meat intake was directly associated with waist circumference (P-trend=0.018). In fully adjusted multivariable models, independent dietary associations of BMI were the intake of nuts inversely (P=0.002) and that of meat and meat products directly (P=0.042). For waist circumference, independent dietary associations were intake of nuts (P=0.002) and vegetables (P=0.040), both inversely, and intake of meat and meat products directly (P=0.009). From the regression coefficients, it was predicted that BMI and waist circumference decreased by 0.78kg/m(2) and 2.1cm, respectively, for each serving of 30g of nuts. Results were similar in men and women. CONCLUSION: Nut consumption was inversely associated with adiposity independently of other lifestyle variables. It remains to be explored whether residual confounding related to a healthier lifestyle of nut eaters might in part explain these results.
Pérez-Jiménez, J., V. Neveu, F. Vos, A. Scalbert, 2010. Identification of the 100 richest dietary sources of polyphenols: an application of the Phenol-Explorer database. European Journal of Clinical Nutrition. 64: S112–S120.
Background/Objectives: The diversity of the chemical structures of dietary polyphenols makes it difficult to estimate their total content in foods, and also to understand the role of polyphenols in health and the prevention of diseases. Global redox colorimetric assays have commonly been used to estimate the total polyphenol content in foods. However, these assays lack specificity. Contents of individual polyphenols have been determined by chromatography. These data, scattered in several hundred publications, have been compiled in the Phenol-Explorer database. The aim of this paper is to identify the 100 richest dietary sources of polyphenols using this database. Subjects/Methods: Advanced queries in the Phenol-Explorer database (www.phenol-explorer.eu) allowed retrieval of information on the content of 502 polyphenol glycosides, esters and aglycones in 452 foods. Total polyphenol content was calculated as the sum of the contents of all individual polyphenols. These content values were compared with the content of antioxidants estimated using the Folin assay method in the same foods. These values were also extracted from the same database. Amounts per serving were calculated using common serving sizes. Results: A list of the 100 richest dietary sources of polyphenols was produced, with contents varying from 15 000mg per 100g in cloves to 10mg per 100 ml in rose´ wine. The richest sources were various spices and dried herbs, cocoa products, some darkly coloured berries, some seeds (flaxseed) and nuts (chestnut, hazelnut) and some vegetables, including olive and globe artichoke heads. A list of the 89 foods and beverages providing more than 1mg of total polyphenols per serving was established. A comparison of total polyphenol contents with antioxidant contents, as determined by the Folin assay, also showed that Folin values systematically exceed the total polyphenol content values. Conclusions: The comprehensive Phenol-Explorer data were used for the first time to identify the richest dietary sources of polyphenols and the foods contributing most significantly to polyphenol intake as inferred from their content per serving.
Schneider Chafen, J.J., S.J. Newberry, M.A. Riedl, D.M. Bravata, M. Maglione, M.J. Suttorp, V. Sundaram, N.M. Paige, A. Towfigh, B.J. Hulley, P.G. Shekelle, 2010. Diagnosing and managing common food allergies: A systematic review. JAMA. 303(18):1848-1856.
Context: There is heightened interest in food allergies but no clear consensus exists regarding the prevalence or most effective diagnostic and management approaches to food allergies. Objective: To perform a systematic review of the available evidence on the prevalence, diagnosis, management, and prevention of food allergies. Data Sources Electronic searches of PubMed, Cochrane Database of Systematic Reviews, Cochrane Database of Abstracts of Reviews of Effects, and Cochrane Central Register of Controlled Trials. Searches were limited to English-language articles indexed between January 1988 and September 2009. Study Selection: Diagnostic tests were included if they had a prospective, defined study population, used food challenge as a criterion standard, and reported sufficient data to calculate sensitivity and specificity. Systematic reviews and randomized controlled trials (RCTs) for management and prevention outcomes were also used. For foods where anaphylaxis is common, cohort studies with a sample size of more than 100 participants were included. Data Extraction: Two investigators independently reviewed all titles and abstracts to identify potentially relevant articles and resolved discrepancies by repeated review and discussion. Quality of systematic reviews and meta-analyses was assessed using the AMSTAR criteria, the quality of diagnostic studies using the QUADAS criteria most relevant to food allergy, and the quality of RCTs using the Jadad criteria. Data Synthesis: A total of 12 378 citations were identified and 72 citations were included. Food allergy affects more than 1% to 2% but less than 10% of the population. It is unclear if the prevalence of food allergies is increasing. Summary receiver operating characteristic curves comparing skin prick tests (area under the curve [AUC], 0.87; 95% confidence interval [CI], 0.81-0.93) and serum food-specific IgE (AUC, 0.84; 95% CI, 0.78-0.91) to food challenge showed no statistical superiority for either test. Elimination diets are the mainstay of therapy but have been rarely studied. Immunotherapy is promising but data are insufficient to recommend use. In high-risk infants, hydrolyzed formulas may prevent cow’s milk allergy but standardized definitions of high risk and hydrolyzed formula do not exist. Conclusion: The evidence for the prevalence and management of food allergy is greatly limited by a lack of uniformity for criteria for making a diagnosis.
