Highlights
- •Walnut and nut consumers had higher HEI2015 diet quality scores than those who do not consume nuts.
- •Walnut consumers had a better CVD risk profile than other nut and no nut consumers.
- •Our study findings support the health claim to include walnuts as part of a healthy diet.
Abstract
Background and aims
Few studies have examined long-term associations of walnut, other nut, and no nut consumption with cardiovascular disease (CVD) risk factors. Results from prospective studies with long-term follow-up can provide further evidence for dietary guideline messaging to consume nuts. Therefore, we examined the associations of walnut, other nut, and no nut consumption with diet quality and CVD risk factors over 30 years of follow-up.
Methods and results
Data were analyzed from 3092 young adults enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Dietary intake, including walnuts and other nuts, was assessed 3 times over 20 years. CVD risk factors were measured at multiple exams. General linear regression evaluated the associations of walnut, other nut, and no nut consumption with CVD risk factors over 30 years (Y30) of follow-up. The 20-year cumulative mean intake of walnuts (0.74 oz/d), other nuts (1.6 oz/d), or no nut consumption was differentially associated with HEI-2015 and CVD risk factors by Y30. Generally, walnut consumers had significantly higher HEI-2015, lower body mass index, waist circumference, blood pressure, and triglyceride concentration, and gained less weight since baseline than other nut consumers (p ≤ 0.05 for all). Further, walnut consumers had lower fasting blood glucose than no nut consumers (p ≤ 0.05).
Conclusion
Study findings that walnut and other nut consumption was associated with better CVD risk factors and diet quality aligns with the 2020–2025 US. Dietary Guidelines for Americans recommendation to consume nuts, such as walnuts, within the context of a healthy diet.
Keywords
1. Introduction
Cardiovascular disease (CVD) is the leading cause of death globally, and many modifiable risk factors, including dietary intake, have been identified. Higher intake of nuts is one dietary behavior associated with lower risk of CVD [
[1]
]. Evidence from numerous studies about the associations of nut intake, including tree nuts and peanuts, with CVD and its risk factors justified approval of a health claim by the Food and Drug Administration (FDA) in 2003 that intake of most nuts as part of a diet low in saturated fat and cholesterol may reduce the risk of CVD [- Liu X.
- Guasch-Ferré M.
- Drouin-Chartier J.P.
- et al.
Changes in nut consumption and subsequent cardiovascular disease risk among US men and women: 3 large prospective cohort studies.
J Am Heart Assoc. 04 07 2020; 9e013877https://doi.org/10.1161/JAHA.119.013877
[2]
]. A similar health claim for walnuts was approved by the FDA several months later [[3]
]. Notably, since 1990 the U.S. Dietary Guidelines for Americans have included recommendations to eat nuts as a part of a healthy diet [[4]
].Meta-analyses of randomized controlled trials (RCTs) that tested the effects of daily mixed nut consumption (a combination of at least two types of tree nuts) on blood pressure (BP) or body composition demonstrated reduced diastolic BP (DBP) [
[5]
], but no effect on body mass index (BMI), waist circumference, body weight, or percent body fat [[6]
] in adults. Other single RCTs conducted in adults with metabolic syndrome who ate mixed nuts daily demonstrated reduced blood concentrations of insulin [[7]
] and total cholesterol [[8]
], but no change in other CVD risk factors, including BMI, waist circumference, BP, and low-density lipoprotein (LDL) cholesterol, triglycerides (TG) and fasting blood glucose concentrations. In prospective studies conducted among college graduates, middle-aged, and White adult men and/or women, mixed nut intake was associated with less weight gain and lower risk of obesity [9
, 10
, 11
]. Finally, in cross-sectional studies, mixed nut intake was favorably associated with BMI, obesity, waist circumference, abdominal obesity, systolic BP (SBP), DBP, and insulin concentration [12
, - Ibarrola-Jurado N.
- Bulló M.
- Guasch-Ferré M.
- et al.
Cross-sectional assessment of nut consumption and obesity, metabolic syndrome and other cardiometabolic risk factors: the PREDIMED study.
PLoS One. 2013; 8e57367https://doi.org/10.1371/journal.pone.0057367
13
, 14
]. In addition, better diet quality and nutrient adequacy among nut consumers compared with non-consumers was reported in cross-sectional studies [15
, - States U.
Department of agriculture (USDA) CfNPaP, (CNPP). The healthy eating index.
https://www.cnpp.usda.gov/sites/default/files/healthy_eating_index/HEI89-90report.pdf
Date accessed: February 10, 2019
16
, 17
]. In summary, findings are generally inconsistent across studies due to differing study design, study population, dose and combinations of nut types, and study time period or follow-up time; though observational studies report consistent results related to mixed nut consumption and better body composition, while RCTs demonstrated no change in body composition.In contrast to evidence presented about mixed nuts in the previous paragraph, walnut consumption showed reduced total and LDL cholesterol and TG, but no alteration in high-density lipoprotein (HDL) cholesterol, body weight, BMI, or BP as reported from a recent meta-analysis of 26 RCTs [
[18]
]. The health benefits of walnuts may potentially be due to the alpha-linolenic acid (ALA; 18:3, n3) content in walnuts not shared with other nuts [[19]
]. However, the long-term associations of consumption of walnuts, other nuts, and no nuts with CVD risk factors, including dietary intake, are less well studied.The objective of this study is to examine the associations of walnut consumption, other nut consumption, and no nut consumption with CVD risk factors, including dietary intake, smoking, body composition, BP, and plasma lipids, fasting blood glucose, and insulin concentrations among young adults enrolled in the Coronary Artery Risk Development in Young Adults (CARDIA) study over 30 years of follow-up. We hypothesize that walnut consumers have a higher diet quality score, as represented by the Healthy Eating Index-2015 (HEI-2015), and better CVD risk factors than other nut consumers and no nut consumers.
2. Methods
2.1 Study overview
Data for this study were obtained from the CARDIA study, a multi-center, longitudinal study investigating the development and determinants of CVD risk beginning in young adulthood [
[20]
]. The institutional review boards at each participating institution approved this study protocol, and the study participants gave written informed consent at each study examination.2.2 Study population
In 1985–86, 5,115 young men and women who identified as Black or White enrolled in the CARDIA study at one of four field centers located in Birmingham, AL, Chicago, IL, Minneapolis, MN, and Oakland, CA. Study participants were age 18–30 years and generally healthy at baseline (year 0 [Y0]). Exclusion criteria for these analyses were participants without year 20 (Y20) diet data (n = 1971), implausible energy intake at Y0, year 7 (Y7), and Y20 (<600 kcal/d and >6000 kcal/d for women and <800 kcal/d and >6000 kcal/d for men) (n = 30); diabetes at Y0 (n = 23); and had bariatric surgery (n = 69). The total sample for these analyses included 3,023 study participants.
2.3 Measurements
2.3.1 Dietary assessment
Dietary intake was assessed using the CARDIA Diet History, administered by trained and certified interviewers at the Y0, Y7 and Y20 exams [
[21]
]. Dietary intake was elicited in closed- and open-ended responses to general questions, such as “Do you usually eat nuts or seeds (yes/no)? If yes, what kind of nuts do you eat? Are they salted or unsalted? How many nuts do you usually eat? How often do you have them (per day/week/month)?” Diet data collected included type and brand name, if applicable, of food and beverage intake, frequency (per day, week, or month) and estimated portion size using food models, measuring cups and spoons. The Nutrition Data System for Research (NDSR) program, developed at the University of Minnesota Nutrition Coordinating Center, was used to create the nutrient database to estimate the nutrient and food output for the CARDIA Diet History [[22]
]. NDSR food groups (servings/day) were created based on the United States Department of Agriculture (USDA) food grouping system, including 13 major food groups (fruit, vegetables, grains, legumes, meat, fish and seafood, dairy products, eggs, condiments, sugar, fats, nuts, and beverages) and 166 food subgroups. The ‘nuts’ food group includes walnuts, almonds, pecans, pistachios, cashews, peanuts, hazelnuts, and peanut butter. ‘Walnuts’ were extracted from the ‘nuts’ food group by examining the original reported food items using the NDSR food ID to create a ‘walnut’ food group for each of the CARDIA Y0, Y7, and Y20 food databases. The ‘other nuts’ food group was created from the remaining ‘nuts’ food group and those who did not report eating nuts made up the ‘no nut’ group at Y0, Y7, and Y20. Other nuts include peanuts and tree nuts, excluding walnuts. To validate walnut consumption at Y20, we found significantly higher percentage of plasma phospholipid ALA among walnut consumers compared with non-walnut consumers (0.293% vs 0.230% of total phospholipids, respectively; p = 0.01) [University of Minnesota Nutrition Coordinating Center
Nutrient information sources.
Nutrient information sources.
http://www.ncc.umn.edu/products/nutrient-information-sources/
Date accessed: August 17, 2021
[23]
].The HEI-2015 was selected to represent diet quality and was created according to the National Cancer Institute and USDA scoring guidelines [
[24]
]. However, when used as a confounding factor in the statistical models, the food group ‘nuts’ was excluded from the score since ‘walnuts’ and ‘other nuts’ were the exposure variables in this study.National Cancer Institute
Developing the healthy eating index.
Developing the healthy eating index.
https://epi.grants.cancer.gov/hei/developing.html
Date accessed: August 14, 2018
2.4 Physical and clinical measurements
Using standard procedures, height was measured to the nearest 0.5 cm by wall-mounted stadiometer and weight was measured to the nearest 0.2 kg by calibrated balance-beam scale. Waist circumference was measured to the nearest 0.5 cm midway between the bottom of the ribcage and the iliac crest using a Gulick 2 anthropometric tape with tensioning mechanism [
[25]
]. BMI was defined as weight (kg) divided by height squared (m2). Obesity was defined as BMI ≥30 kg/m2. Abdominal obesity was defined as waist circumference >88 cm for women and >102 cm for men.After a 5-min rest, BP was measured 3 times on the right arm of the seated participant using a Hawksley random zero sphygmomanometer (WA Baum Company, Copiague, NY) at baseline. At the Y20 and year 30 (Y30) exams, BP was measured using a standard automated BP measurement monitor (Omron model HEM907XL; Omron Healthcare, Inc.; Bannockburn, IL). The oscillometric BP values were recalibrated to random zero measurements at Y20, so that no machine bias remained.
Fasting blood samples were drawn by venipuncture at each exam by standard protocol and then stored at −80 °C. Plasma total cholesterol, HDL-cholesterol, and TG concentrations were measured at all examinations by enzymatic methods [
[26]
]. HDL-cholesterol was measured after dextran-magnesium precipitation. LDL-cholesterol was calculated using the Friedewald equation at all exam years [[27]
]. Fasting blood glucose at baseline was determined by the hexokinase UV method (American BioScience Laboratories; Van Nuys, CA) and by hexokinase coupled to glucose-6-phosphate dehydrogenase (Merck Millipore, Billerica, MA) at Y30. Insulin was determined by radioimmunoassay (Linco Research, St. Charles, MO) at baseline, by Elecsys sandwich immunoassay (Roche Diagnostics, Rotkreuz, Switzerland) at Y30. Standardized questionnaires were administered to collect demographic and lifestyle characteristics, including age, sex, race, level of education, current smoking and drinking alcohol. The CARDIA Physical Activity Questionnaire quantified usual physical activity [[28]
]. Hypertension was defined as having systolic BP ≥ 140mmHg, diastolic BP ≥ 90mmHg, and/or use of antihypertensive medication. Elevated cholesterol was defined as total cholesterol ≥200 mg/dL and/or use of cholesterol-lowering medication. High cholesterol was defined as total cholesterol ≥240 mg/dL and/or use of cholesterol-lowering medication. Diabetes was defined as having fasting blood glucose >7 mmol/L (126 mg/dL) and/or use of antidiabetic medication.2.5 Statistical methods
For this secondary data analysis, we used SAS, version 9.4 (SAS Institute, Cary, NC). Means (standard error) and frequencies (%) were reported for continuous and categorical variables, respectively, for Y0 characteristics according to consumption of walnuts, other nuts, and no nuts at Y0 and adjusted for demographic characteristics and energy intake. Multiple linear regression analysis evaluated the relations of averaged (Y0, Y7, and Y20) intakes of walnuts, other nuts, and no nut intake with averaged (Y0, Y7, and Y20) daily nutrient and food group intakes and with Y30 CVD risk factors. Models were adjusted for demographic characteristics (age, sex, race, field center, education), lifestyle factors (energy intake, smoking, physical activity, drinking alcohol, and HEI-2015 without nuts), and each baseline risk factor, as appropriate. Statistical significance is represented as p-value ≤0.05.
3. Results
As shown in Table 1, age was similar among the nut groups. At baseline, more White participants and those with more years of education ate walnuts or other nuts. In cross-sectional analysis, SBP was lower in those consuming walnuts than in the other nut or no nut groups. There were no other significant associations between nut groups and CVD risk factors.
Table 1Mean (SE) and frequency (%) of CARDIA participant characteristics at baseline (1985–86) stratified by baseline intake of walnuts, other nuts, and no nuts, n = 3023.
| Baseline characteristics | Walnut consumers (n = 94) | Other nut consumers (n = 2143) | No Nut consumers (n = 786) | p-value | ||
|---|---|---|---|---|---|---|
| Walnuts vs Other Nuts | Walnuts vs No Nuts | Other Nuts vs No Nuts | ||||
| Walnuts, oz/d | 0.73 (0.93) | 0 | 0 | |||
| Other nuts, oz/d | 1.1 (2.1) | 1.6 (2.2) | 0 | |||
| HEI2015 (without nuts) | 63.7 (0.9) | 60.1 (0.2) | 57.9 (0.3) | <0.001 | <0.001 | <0.001 |
| Age, years | 25.5 (0.3) | 25.1 (0.1) | 24.9 (0.1) | 0.31 | 0.11 | 0.11 |
| Sex, % women | 63.9 (4.7) | 56.6 (1.0) | 55.8 (1.6) | 0.12 | 0.11 | 0.68 |
| Race, % White | 63.9 (4.9) | 58.3 (1.0) | 44.9 (1.7) | 0.26 | <0.001 | <0.001 |
| Education, ≥ high school, % | 74.7 (4.6) | 67.6 (0.9) | 56.1 (1.6) | 0.13 | <0.001 | <0.001 |
| Current smoker, % | 17.2 (4.3) | 24.7 (0.9) | 27.2 (1.5) | 0.09 | 0.03 | 0.17 |
| Physical activity score | 455.6 (28.5) | 433.1 (6.0) | 400.7 (9.9) | 0.44 | 0.07 | 0.006 |
| Body mass index, kg/m2 | 23.6 (0.5) | 24.3 (0.10) | 24.5 (0.17) | 0.18 | 0.08 | 0.24 |
| Obesity, % | 6.9 (3.1) | 10.2 (0.6) | 11.4 (1.1) | 0.29 | 0.17 | 0.33 |
| Waist circumference, cm | 76.0 (1.0) | 77.7 (0.2) | 78.3 (0.4) | 0.12 | 0.04 | 0.16 |
| Abdominal obesity, % | 5.9 (2.5) | 6.4 (0.6) | 7.5 (0.9) | 0.84 | 0.55 | 0.30 |
| Systolic BP, mmHg | 108.3 (1.0) | 110.6 (0.2) | 111.0 (0.4) | 0.02 | 0.009 | 0.29 |
| Diastolic BP, mmHg | 67.3 (0.9) | 68.7 (0.2) | 69.2 (0.3) | 0.13 | 0.05 | 0.20 |
| Hypertension, % | 2.7 (1.9) | 3.5 (0.4) | 3.9 (0.7) | 0.70 | 0.53 | 0.50 |
| Total cholesterol, mg/dL | 171.8 (3.4) | 177.9 (0.7) | 177.8 (1.2) | 0.09 | 0.09 | 0.97 |
| LDL cholesterol, mg/dL | 104.3 (3.2) | 110.4 (0.7) | 110.2 (1.1) | 0.06 | 0.08 | 0.91 |
| HDL cholesterol, mg/dL | 52.9 (1.3) | 53.1 (0.3) | 53.1 (0.5) | 0.89 | 0.88 | 0.96 |
| Triglycerides, mg/dL | 70.1 (4.8) | 71.7 (1.0) | 72.9 (1.7) | 0.75 | 0.58 | 0.54 |
| Elevated cholesterol (≥200 mg/dL),% | 21.0 (4.4) | 23.6 (0.9) | 23.6 (1.5) | 0.57 | 0.58 | 0.99 |
| High cholesterol (≥240 mg/dL), % | 4.39 (0.2) | 4.12 (0.4) | 4.35 (0.7) | 0.90 | 0.98 | 0.78 |
| Lipid medication use, % | 0 | 0 | 0 | |||
| Fasting blood glucose, mg/dL | 81.7 (0.9) | 82.3 (0.2) | 81.3 (0.3) | 0.53 | 0.73 | 0.01 |
| Insulin, μU/ml | 9.6 (0.8) | 10.5 (0.2) | 10.8 (0.3) | 0.27 | 0.16 | 0.35 |
BP = blood pressure; HDL = high density lipoprotein; LDL = low density lipoprotein; HEI = healthy eating index.
a Adjusted for age, sex, race, field center, education, and energy intake.
b Linear regression models were used. Statistical significance is represented as p-value ≤0.05.
Between baseline and Y20, the prevalence of walnut consumers increased almost fourfold, from 3.1% to 11.5%, other nut consumers increased 16.8%, while non-consumers of nuts declined by 78.5%. Intakes of nutrients and food groups by walnut consumers, other nut consumers, and no nut consumption over 20 years is shown in Table 2. Mean intake of walnuts was 0.74 oz/d, intake of nuts among walnut and other nut consumers was about 1.1 and 1.6 oz/d, respectively. Walnut consumers had higher HEI-2015 score than other nut and no nut consumers, and other nut consumers had higher HEI-2015 than no nut consumers (p < 0.001). Intakes of energy, % energy from polyunsaturated fatty acid (PUFA), gamma-linolenic acid and ALA, fiber, vitamins B6 and E, magnesium, and potassium were higher and % energy from saturated fatty acids (SFA) was lower among walnut consumers compared with both other nut consumers and no nut consumers (p ≤ 0.04). Similarly, other nut consumers had higher intakes of % energy from PUFA, fiber, vitamins B6 and E, magnesium, and potassium and lower % energy from SFA than no nut consumers (p ≤ 0.01). Both walnut and other nut consumers reported lower intake of added sugar than no nut consumers (p < 0.001).
Table 2Mean (SE) dietary intake over 20 years stratified by intake of walnuts, other nuts, and no nuts, n = 3023.
| Daily Dietary Intake, | Walnut consumers (n = 352) | Other nut consumers (n = 2494) | No Nut consumers (n = 177) | p-value | ||
|---|---|---|---|---|---|---|
| Walnut vs Other Nuts | Walnuts vs No Nuts | Other Nuts vs No Nuts | ||||
| Walnuts, oz | 0.74 (1.2) | 0 | 0 | |||
| Other nuts, oz | 1.1 (2.5) | 1.6 (2.2) | 0 | |||
| HEI2015 score (all components) | 65.6 (0.5) | 63.3 (0.2) | 57.6 (0.7) | <0.001 | <0.001 | <0.001 |
| HEI2015 score (without nuts) | 63.7 (0.5) | 61.9 (0.2) | 57.5 (0.7) | 0.001 | <0.001 | <0.001 |
| Nutrient intake | ||||||
| Energy, kcal | 2,821 (51.1) | 2,705 (18.8) | 2,638 (71.3) | 0.03 | 0.04 | 0.37 |
| Protein, % kcal | 14.9 (0.1) | 15.0 (0.04) | 15.0 (0.2) | 0.41 | 0.64 | 0.97 |
| Total fat, % kcal | 36.5 (0.3) | 36.4 (0.1) | 36.0 (0.4) | 0.68 | 0.23 | 0.26 |
| Saturated fat, % kcal | 12.3 (0.12) | 12.6 (0.04) | 13.0 (0.2) | 0.02 | <0.001 | 0.01 |
| Monounsaturated fat,% kcal | 13.7 (0.1) | 13.6 (0.04) | 13.4 (0.2) | 0.62 | 0.08 | 0.08 |
| Polyunsaturated fat, % kcal | 7.8 (0.1) | 7.4 (0.03) | 6.8 (0.1) | <0.001 | <0.001 | <0.001 |
| 18:3, gm (GLA + ALA) | 2.5 (0.1) | 2.1 (0.02) | 2.0 (0.1) | <0.001 | <0.001 | 0.48 |
| Cholesterol, mg | 177.4 (1.6) | 180.9 (0.6) | 179.0 (2.2) | 0.03 | 0.55 | 0.40 |
| Added sugar, % kcal | 12.3 (0.3) | 13.6 (0.1) | 15.6 (0.4) | <0.001 | <0.001 | <0.001 |
| Carbohydrate, % kcal | 47.8 (0.3) | 47.5 (0.1) | 46.6 (0.5) | 0.29 | 0.02 | 0.05 |
| Fiber, gm | 24.4 (0.4) | 20.6 (0.2) | 16.9 (0.6) | <0.001 | <0.001 | <0.001 |
| Vitamin B6, mg | 2.3 (0.04) | 2.1 (0.02) | 1.9 (0.06) | 0.002 | <0.001 | <0.001 |
| Magnesium, mg | 382.2 (5.6) | 338.5 (2.0) | 293.5 (7.8) | <0.001 | <0.001 | <0.001 |
| Calcium, mg | 1026.6 (21.4) | 1003.1 (7.9) | 963.3 (29.8) | 0.30 | 0.09 | 0.20 |
| Vitamin D, mcg | 5.5 (0.2) | 5.7 (0.1) | 5.5 (0.3) | 0.24 | 0.87 | 0.51 |
| Vitamin E (alpha tocopherol), mg | 15.4 (0.4) | 13.0 (0.1) | 10.2 (0.5) | <0.001 | <0.001 | <0.001 |
| Potassium, mg | 2,216 (35.9) | 2,040 (13.3) | 1,892 (50.1) | <0.001 | <0.001 | 0.004 |
| Sodium, mg | 3396 (54.2) | 3368 (20.0) | 3283 (74.7) | 0.62 | 0.23 | 0.28 |
| Food group intake, sv/day | ||||||
| Whole grain products | 1.78 (0.06) | 1.56 (0.02) | 1.21 (0.08) | <0.001 | <0.001 | <0.001 |
| Refined grain products | 3.24 (0.08) | 3.45 (0.03) | 3.61 (0.12) | 0.02 | 0.01 | 0.17 |
| Fruit | 2.10 (0.07) | 1.59 (0.03) | 1.29 (0.09) | <0.001 | <0.001 | 0.004 |
| Vegetables | 5.22 (0.12) | 4.33 (0.05) | 3.90 (0.17) | <0.001 | <0.001 | 0.02 |
| Dairy products | 2.60 (0.09) | 2.72 (0.03) | 2.89 (0.12) | 0.18 | 0.22 | 0.63 |
| Legumes | 0.31 (0.02) | 0.23 (0.01) | 0.21 (0.02) | <0.001 | <0.001 | 0.50 |
| Red meat | 3.19 (0.09) | 3.46 (0.04) | 4.00 (0.13) | 0.006 | <0.001 | <0.001 |
| Processed meat | 1.15 (0.05) | 1.30 (0.02) | 1.42 (0.06) | 0.002 | <0.001 | 0.06 |
| Poultry | 1.40 (0.05) | 1.38 (0.02) | 1.27 (0.07) | 0.77 | 0.17 | 0.15 |
| Fish | 1.15 (0.05) | 1.04 (0.02) | 0.89 (0.07) | 0.05 | 0.004 | 0.04 |
| Eggs | 0.60 (0.02) | 0.59 (0.01) | 0.62 (0.03) | 0.74 | 0.73 | 0.51 |
| Protein sources | 7.74 (0.16) | 7.33 (0.05) | 6.57 (0.22) | 0.02 | <0.001 | <0.001 |
| Candy | 0.29 (0.02) | 0.32 (0.01) | 0.23 (0.03) | 0.33 | 0.14 | 0.01 |
| Diet beverages | 0.51 (0.06) | 0.64 (0.02) | 0.56 (0.08) | 0.03 | 0.67 | 0.29 |
| Sugar-sweetened beverages | 1.14 (0.07) | 1.23 (0.03) | 1.68 (0.09) | 0.22 | <0.001 | <0.001 |
| Coffee/tea (unsweetened) | 1.80 (0.13) | 1.80 (0.05) | 1.77 (0.18) | 0.99 | 0.89 | 0.88 |
HEI = healthy eating index; SE = standard error.
a Mean dietary intake at baseline (Y0), Y7, and Y20.
b Adjusted for age, sex, race, education, field center, and energy intake.
c Linear regression models were used. Statistical significance is represented as p-value ≤0.05.
d Protein sources include meat, fish, eggs, legumes, nuts, and poultry.
e Candy includes candy, sugar, honey, syrup, jam and jelly.
Compared with other nut and no nut consumers, walnut consumers ate more servings of whole grain products, fruit, vegetables, legumes, and fish, and fewer servings of refined grain products, red meat and processed meat (p ≤ 0.05). Other nut consumers ate more servings of whole grain products, fruit, vegetables, legumes, fish, and candy, and fewer red meat and sugar-sweetened beverages than no nut consumers (p ≤ 0.04). There were no differences in eating patterns among nut groups for dairy products, poultry, eggs, diet beverages, and coffee or tea (p > 0.05).
Adjusted mean (SE) and frequency (%) of participant characteristics and risk factors at Y30 are shown in Table 3. At Y30, compared with other nut and no nut consumers, walnut consumers had higher physical activity score (p ≤ 0.02). In addition, by Y30, walnut consumers had lower BMI, weight gain, waist circumference, change in waist circumference, SBP, DBP and TG concentration and lower prevalence of abdominal obesity than other nut consumers (p ≤ 0.04). Furthermore, walnut consumers had lower fasting blood glucose concentration compared with no nut consumers (p = 0.02). There were fewer smokers among walnut and other nut consumers than no nut consumers (p ≤ 0.05). The no nut consumer group had lower LDL-cholesterol concentrations than the other nut group (p = 0.04), while there was no difference among nut groups for total cholesterol and insulin concentrations or prevalence of having high blood pressure or high cholesterol (p > 0.05).
Table 3Adjusted mean (SE) and frequency (%) of CARDIA participant characteristics and risk factors at Year 30 stratified by intakes of walnuts, other nuts, and no nuts, n = 3023.
| Y30 (2015–2016) Characteristics | Walnut consumers (n = 352) | Other nut consumers (n = 2494) | No nut consumers (n = 177) | p-value | ||
|---|---|---|---|---|---|---|
| Walnut vs Other ∗Nuts | Walnut vs No nuts | Other nut vs No nuts | ||||
| Age, years | 55.2 (0.03) | 55.2 (0.01) | 55.2 (0.05) | 0.39 | 0.36 | 0.60 |
| Current smoker, % | 11.8 (1.5) | 10.9 (0.6) | 17.5 (2.4) | 0.59 | 0.05 | 0.008 |
| Physical activity score | 383.4 (13.7) | 337.2 (5.4) | 321.1 (22.6) | 0.001 | 0.02 | 0.49 |
| Body mass index, kg/m2 | 29.0 (0.3) | 29.7 (0.12) | 29.5 (0.9) | 0.03 | 0.38 | 0.74 |
| Weight gain, lb since baseline | 34.1 (1.9) | 38.7 (0.7) | 37.0 (3.1) | 0.02 | 0.43 | 0.59 |
| Obesity, % | 36.9 (2.6) | 41.5 (1.0) | 45.0 (4.3) | 0.10 | 0.11 | 0.42 |
| Waist circumference, cm | 92.4 (0.7) | 94.3 (0.3) | 94.4 (1.2) | 0.01 | 0.15 | 0.96 |
| Waist change, cm since baseline | 16.8 (0.7) | 18.7 (0.3) | 18.8 (1.2) | 0.01 | 0.15 | 0.96 |
| Abdominal Obesity, % | 29.4 (2.6) | 37.2 (0.9) | 32.0 (3.7) | 0.004 | 0.48 | 0.25 |
| Systolic BP, mmHg | 118.5 (0.9) | 120.4 (0.4) | 120.9 (1.4) | 0.04 | 0.19 | 0.78 |
| Diastolic BP, mmHg | 72.0 (0.6) | 74.1 (0.3) | 74.3 (0.9) | 0.002 | 0.07 | 0.91 |
| Hypertension, % | 9.6 (2.0) | 12.7 (0.8) | 13.4 (0.3) | 0.16 | 0.35 | 0.84 |
| Total cholesterol, mg/dL | 191.4 (2.1) | 193.9 (0.8) | 191.3 (3.5) | 0.27 | 0.97 | 0.46 |
| LDL cholesterol, mg/dL | 111.9 (1.9) | 114.4 (0.8) | 107.8 (3.2) | 0.21 | 0.27 | 0.04 |
| HDL-cholesterol, mg/dL | 59.9 (1.1) | 58.7 (0.4) | 60.2 (1.5) | 0.30 | 0.98 | 0.15 |
| Triglycerides, mg/dL | 92.2 (3.7) | 100.3 (1.5) | 102.4 (6.1) | 0.04 | 0.16 | 0.73 |
| Elevated cholesterol (≥200 mg/dL),% | 47.7 (2.9) | 50.3 (1.1) | 47.4 (4.6) | 0.40 | 0.97 | 0.55 |
| High cholesterol (≥240 mg/dL), % | 12.0 (2.1) | 13.9 (0.8) | 16.1 (3.3) | 0.38 | 0.31 | 0.54 |
| Lipid medication use, % | 29.7 (2.6) | 27.9 (0.9) | 26.8 (4.1) | 0.52 | 0.55 | 0.78 |
| Fasting blood glucose, mg/dL | 94.4 (0.9) | 96.2 (0.4) | 99.0 (1.6) | 0.07 | 0.02 | 0.09 |
| Insulin, μU/ml | 11.2 (0.60) | 12.2 (0.2) | 12.4 (0.9) | 0.08 | 0.26 | 0.84 |
| Diabetes, % | 12.5 (2.0) | 13.7 (0.7) | 13.2 (3.0) | 0.56 | 0.85 | 0.87 |
BP = blood pressure; LDL = low density lipoprotein; SE = standard error.
a Adjusted for age, sex, race, field center, education, energy intake, physical activity, current smoking, drinking alcohol, HEI2015 without nuts, and each baseline risk factor, as appropriate.
b Linear regression models were used. Statistical significance is represented as p-value ≤0.05.
c Participants with diabetes were excluded, sample sizes are as follows for walnut consumers n = 322; other nut consumers n = 2195; no nut consumers n = 153.
In sensitivity analysis we excluded those who developed diabetes by Y30 in case individuals with diabetes changed their diet (i.e., ate walnuts or other nuts). Regardless, study results did not substantively change (data not shown).
4. Discussion
Walnut consumers had a better CVD risk profile than other nut and no nut consumers even after adjusting for their higher HEI-2015 and other confounding factors. Walnut consumers were significantly more physically active with lower measures of body composition, blood pressure, and TG concentration over 30 years of follow-up than other nut consumers, as detailed in Table 3. Furthermore, compared to no nut consumers, walnut consumers had significantly lower fasting blood glucose concentrations while other nut consumers had higher LDL-cholesterol. Compared to no nut consumers, walnut and other nut consumers had better diet quality as represented by higher HEI-2015 diet quality scores, including more daily servings of nutrient rich foods, such as whole grain products, fruit, vegetables, and fish and lower intake of red meat. Nut consumers show an advantage in relation to diet quality but walnut consumers appear to have a better CVD risk factor profile than the other groups, even after accounting for overall diet quality.
4.1 Dietary quality
In National Health and Nutrition Examination Survey (NHANES 2005–2010), compared to non-consumers, tree nut consumers reported better quality diet as represented by a higher HEI-2005 score [
[17]
]. Similar to CARDIA walnut consumers, women in the prospective Nurses’ Health Studies (NHS) I and II who consumed walnuts compared with non-consumers had higher quality diets as characterized by higher nutrient intakes of energy, PUFA:SFA ratio, ALA, fiber, and magnesium, as well as higher food intakes of whole grains, fruit, and vegetables, and lower intakes of red/processed meat and sugar-sweetened beverages [[29]
].4.2 Body composition
Among RCTs, many studies demonstrated no change in BMI, body weight or waist circumference among walnut consumers [
30
, 31
, 32
, - Bamberger C.
- Rossmeier A.
- Lechner K.
- et al.
A walnut-enriched diet reduces lipids in healthy caucasian subjects, independent of recommended macronutrient replacement and time point of consumption: a prospective, randomized, controlled trial.
Nutrients. Oct 06 2017; 9https://doi.org/10.3390/nu9101097
33
, 34
, 35
, 36
, 37
, 38
, 39
, 40
, - Njike V.Y.
- Ayettey R.
- Petraro P.
- Treu J.A.
- Katz D.L.
Walnut ingestion in adults at risk for diabetes: effects on body composition, diet quality, and cardiac risk measures.
BMJ Open Diabetes Res Care. 2015; 3e000115https://doi.org/10.1136/bmjdrc-2015-000115
41
, 42
] and mixed nut consumers [[7]
,[8]
] compared with controls, and some studies demonstrated weight loss [[42]
,[43]
] or weight gain [[44]
] among walnut consumers compared with controls. In three prospective studies, intake of nuts was associated with less weight gain over 28 months [[9]
], 5 years [[11]
], and 8 years [[10]
] of follow-up. In addition, intake of nuts was associated with a lower risk of obesity over 8 years [[10]
]. However, in the CARDIA study over 30 years, walnut consumers had lower BMI and waist circumference and gained less weight than other nut consumers. In addition, there were fewer abdominally obese walnut consumers than other nut consumers by Y30.4.3 Blood pressure
Blood pressure was measured in several of the RCTs testing the effectiveness of walnuts and mixed nuts on health; however, duration of these trials was relatively short for blood pressure to change [
[7]
,[8]
,[30]
,[33]
,[36]
,38
, 39
, 40
,- Njike V.Y.
- Ayettey R.
- Petraro P.
- Treu J.A.
- Katz D.L.
Walnut ingestion in adults at risk for diabetes: effects on body composition, diet quality, and cardiac risk measures.
BMJ Open Diabetes Res Care. 2015; 3e000115https://doi.org/10.1136/bmjdrc-2015-000115
44
, 45
, 46
]. In an 8-week RCT of adults with type 2 diabetes, SBP and DBP increased after walnut consumption compared with controls; however, blood pressure was not significantly different from baseline in both walnut consumers and non-consumers [[34]
]. In a cross-sectional study of the Prospective Urban Rural Epidemiology (PURE) study from 16 countries, higher nut consumption was associated with lower SBP and DBP [[13]
]. In CARDIA, we observed lower SBP and DBP among walnut consumers than in other nut consumers over 30 years of follow-up.4.4 Lipids
While results from individual walnut intervention RCTs were inconsistent for change in LDL- and HDL-cholesterol and triglycerides, results from a meta-analysis of 26 RCTs [
[18]
] showed reduced plasma total and LDL cholesterol and TG in walnut consumers compared with controls, while HDL-cholesterol did not change. For mixed nut interventions, results from RCTs demonstrated no effect on LDL- and HDL-cholesterol [[7]
,[8]
] and TG concentrations [[7]
], but inconsistent results for total cholesterol [[7]
]. ]. In 30 years of follow-up in CARDIA, total cholesterol and HDL-cholesterol were not different between groups. Although, walnut consumers had lower TG concentration than no nut consumers and those who consumed other nuts had higher LDL-cholesterol concentrations than no nut consumers, both of these results may be due to chance given their marginal significance level (both p = 0.04).4.5 Fasting blood glucose and insulin
In contrast to CARDIA results, investigators in the NHS reported lower risk of developing type 2 diabetes with greater walnut intake compared with no walnut intake over 10 years of follow-up [
[29]
]. In CARDIA, walnut consumers had lower fasting blood glucose concentration compared with no nut consumers, while insulin concentration was not different between groups. However, in short-term study periods of RCTs, fasting blood glucose and insulin concentrations were not different between walnut intervention and control groups [[33]
,[34]
,[36]
,[38]
,[40]
,- Njike V.Y.
- Ayettey R.
- Petraro P.
- Treu J.A.
- Katz D.L.
Walnut ingestion in adults at risk for diabetes: effects on body composition, diet quality, and cardiac risk measures.
BMJ Open Diabetes Res Care. 2015; 3e000115https://doi.org/10.1136/bmjdrc-2015-000115
[41]
,[44]
,[52]
]. In a 12-week RCT, mixed nuts had no effect on fasting blood glucose concentration; however, results were inconsistent for insulin concentration between mixed nut and control groups [[7]
,[8]
].The inconsistent results of RCTs may be explained by differential methodology in the design and conduct of the RCTs, including duration of the intervention, amount of nut intake, and study population. RCTs were conducted over 4 weeks to 1 year, and the amount of nuts by treatment group varied greatly, ranging from 15 to 108 g/d [
[18]
]. The study populations enrolled in the studies were diverse, including young, middle-aged or older adults, adults with normal cholesterol or those with dyslipidemia, adults at high risk of diabetes or had diabetes, and adults with metabolic syndrome [[18]
]. Observational studies also differed in study design, including the population studied (i.e., differing age, sex, race, and education groups), diet assessment instrument (FFQ vs diet history), and follow-up period (2 years–30 years). The CARDIA observational study design provides long-term information which is not likely to be available for a RCT.Many studies have shown that nut intake does not promote weight gain [
[30]
,[34]
,[45]
,[49]
,[55]
,[56]
]. While the mechanism of weight maintenance is unclear, it may be due to the satiety effect of walnuts [57
, 58
, 59
] as well as inefficient absorption of energy from walnuts [[60]
]. In addition, the poor digestion of cell walls of nuts may increase fecal fat excretion [[61]
]. Further, walnuts contain melatonin, a bioactive compound shown to improve body composition, blood pressure, and glucose metabolism [[62]
,[63]
]. Melatonin influences body composition through energy metabolism [[62]
] and it regulates blood pressure through improved insulin sensitivity and improved glucose control through reduced glucose production [[63]
]. Other possible mechanisms that may explain the influence of walnuts on blood pressure include their favorable effect on endothelial function [[44]
,[64]
] and attenuation of vascular reactivity in resistance vessels. A rapid beta-oxidation of ALA was observed in human studies compared with other fatty acids [[65]
], and this trait of ALA may play a role in improving insulin sensitivity by decreasing the accumulation of lipid in skeletal muscle and liver [[66]
], which would explain better blood pressure as well as glucose metabolism in addition to the influence of melatonin [[63]
].There are strengths and limitations in our study. Self-reported dietary intake is subject to measurement error, which is a potential limitation. However, Poppitt et al. demonstrated in obese and non-obese adults that typical foods underreported or forgotten were in-between meal snacks and high carbohydrate-containing snack foods, including high-sugar snack foods [
[67]
]. Although snack foods may be underestimated, they would be underestimated in all study participants, thus measurement error is non-differential for these foods. Still, overweight and obese adults are known to underreport energy intake by 12–20% [[68]
,[69]
]. Notably, we found higher proportion of plasma phospholipid ALA in walnut consumers than non-walnut consumers; therefore, we expect that walnut reporting was accurate. Given accurate walnut reporting, the differences for clinical characteristics between walnut consumers and non-consumers are likely unbiased. However, we cannot rule out residual confounding. Finally, we did not isolate other specific nuts in our database; therefore our findings should not be interpreted as indicating no benefit of other nuts.The strengths of this study include the prospective study design and 30 years of follow-up, the cohort of Black and White, young male and female adults at baseline, repeated measures of dietary intake assessed by diet history over 20 years, and measurement of CVD risk factors over 30 years. Follow-up of participants enrolled in RCTs testing the effectiveness of walnut intake is typically short-term; therefore, it may be difficult to assure that the effects of walnut intake remain constant after many years [
[70]
]. However, in CARDIA, participants were examined regularly over time to monitor lifestyle, physical, and clinical characteristics. Thus, in this prospective study, we observed an increase in walnut consumption over 20 years and significant and beneficial associations of walnut intake with CVD risk factors over 30 years of follow-up.Our study findings support the health claim to include walnuts as part of a healthy diet by adding the observation of a more favorable risk profile after 30 years of follow-up, a duration that cannot be addressed in RCT designs [
[3]
]. In addition, our findings are consistent with and add a long-term dimension to the 2020–25 DGA to consume a variety of protein sources, including nuts in a healthy eating pattern, and to replace saturated fat with other fats, including those from nuts and olive oil [[71]
].Funding source
The Coronary Artery Risk Development in Young Adults Study (CARDIA) is supported by contracts HHSN268201800003I, HHSN268201800004I, HHSN268201800005I, HHSN268201800006I, and HHSN268201800007I from the National Heart, Lung, and Blood Institute (NHLBI). Other funding was R01-HL-084099 from NHLBI (Dr. Myriam Fornage) and the California Walnut Commission (Dr. Lyn Steffen). This report was reviewed for scientific content by the CARDIA publications committee, on which there is an NIH representative. The California Walnut Commission had no role in writing or reviewing this paper.
Declaration of competing interest
So Yun Yi: no conflicts of interest; Lyn M. Steffen received a grant from the California Walnut Commission which partially supported manuscript preparation; Xia Zhou: no conflicts of interest; James M. Shikany: no conflicts of interest; David R. Jacobs: no conflicts of interest.
Acknowledgements
SYY, LMS, and DRJ designed research; LMS and XZ conducted research; XZ analyzed the data; SYY and LMS wrote the paper; LMS had primary responsibility for final content; JMS and DRJ critically reviewed and revised the paper for important content; All authors have read and approved the final manuscript.
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Publication history
Published online: July 30, 2022
Accepted:
July 18,
2022
Received in revised form:
July 11,
2022
Received:
March 30,
2022
Handling Editor: P. RussoIdentification
Copyright
© 2022 The Authors. Published by Elsevier B.V. on behalf of The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University.
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