You are here

Article Text

Article menu
XML
Original research
Changes in nut consumption influence long-term weight change in US men and women
  1. Xiaoran Liu1,
  2. Yanping Li1,
  3. Marta Guasch-Ferré1,2,
  4. Walter C Willett1,2,3,
  5. Jean-Philippe Drouin-Chartier1,
  6. Shilpa N Bhupathiraju1,2 and
  7. Deirdre K Tobias1,4
  1. 1 Department of Nutrition, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
  2. 2 Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA
  3. 3 Department of Epidemiology, Harvard University T H Chan School of Public Health, Boston, Massachusetts, USA
  4. 4 Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA
  1. Correspondence to Dr Deirdre K Tobias, Nutrition, Harvard University T H Chan School of Public Health, Boston, MA 02215, USA; dtobias{at}bwh.harvard.edu

Abstract

Background Nut consumption has increased in the US but little evidence exists on the association between changes in nut consumption and weight change. We aimed to evaluate the association between changes in total consumption of nuts and intakes of different nuts (including peanuts) and long-term weight change, in three independent cohort studies.

Methods and findings Data collected in three prospective, longitudinal cohorts among health professionals in the US were analysed. We included 27 521 men (Health Professionals Follow-up Study, 1986 to 2010), 61 680 women (Nurses’ Health Study, 1986 to 2010), and 55 684 younger women (Nurses’ Health Study II, 1991 to 2011) who were free of chronic disease at baseline in the analyses. We investigated the association between changes in nut consumption over 4-year intervals and concurrent weight change over 20–24 years of follow-up using multivariate linear models with an unstructured correlation matrix to account for within-individual repeated measures. 21 322 individuals attained a body mass index classification of obesity (BMI ≥30 kg/m2) at the end of follow-up.

Average weight gain across the three cohorts was 0.32 kg each year. Increases in nut consumption, per 0.5 servings/day (14 g), was significantly associated with less weight gain per 4-year interval (p<0.01 for all): −0.19 kg (95% CI -0.21 to -0.17) for total consumption of nuts, -0.37 kg (95% CI -0.45 to -0.30) for walnuts, -0.36 kg (95% CI -0.40 to -0.31) for other tree nuts, and -0.15 kg (95% CI -0.19 to -0.11) for peanuts.

Increasing intakes of nuts, walnuts, and other tree nuts by 0.5 servings/day was associated with a lower risk of obesity. The multivariable adjusted RR for total nuts, walnuts, and other tree nuts was 0.97 (95% CI 0.96 to 0.99, p=0.0036), 0.85 (95% CI 0.81 to 0.89, p=0.0002), and 0.89 (95% CI 0.87 to 0.91, p<0.0001), respectively. Increasing nut consumption was also associated with a lower risk of gaining ≥2 kg or ≥5 kg (RR 0.89–0.98, p<0.01 for all).

In substitution analyses, substituting 0.5 servings/day of nuts for red meat, processed meat, French fries, desserts, or potato, chips (crisps) was associated with less weight gain (p<0.05 for all).

Our cohorts were largely composed of Caucasian health professionals with relatively higher socioeconomic status; thus the results may not be generalisable to other populations.

Conclusion Increasing daily consumption of nuts is associated with less long-term weight gain and a lower risk of obesity in adults. Replacing 0.5 servings/day of less healthful foods with nuts may be a simple strategy to help prevent gradual long-term weight gain and obesity.

  • weight management
  • nutrition assessment
  • dietary patterns

This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.

https://doi.org/10.1136/bmjnph-2019-000034

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    View Full Text

    Supplementary materials

    Footnotes

    • Contributors XL, YL, DKT: Conception or design of the work. XL, YL, MGF, DKT: Data analysis and interpretation. XL: Drafting the article. WCW, JP-DC, SNB: Critical revision of the article. DKT: Final approval of the version to be published.

    • Funding This study was supported by research grant UM1 CA186107, UM1 CA176726, and UM1 CA167552 from the National Institutes of Health.

    • Competing interests XL was partly funded by The Peanut Institution and YL was partly funded by the California Walnut Commission. The funders have no roles in study design, data collection and interpretation and decision on manuscript publication. J-PD-C is being supported by a Banting Postdoctoral Fellowship from the Canadian Institutes of Health Research (BPF-156628). J-PD-C received speaker and consulting honoraria from the Dairy Farmers of Canada in 2016 and 2018, outside the submitted work.

    • Patient consent for publication Not required.

    • Provenance and peer review Not commissioned; externally peer reviewed.

    • Data availability statement The Health Professionals Follow-up Study, the Nurses’ Health Study, and the Nurses’ Health Study II data may be used in collaboration with a principal investigator. Please see the study websites for more information: https://www.hsph.harvard.edu/hpfs/hpfs_collaborators.htm, and http://www.nurseshealthstudy.org/researchers.