Biomarker-Calibrated Red and Combined Red and Processed Meat Intakes with Chronic Disease Risk in a Cohort of Postmenopausal Women.


Journal

The Journal of nutrition
ISSN: 1541-6100
Titre abrégé: J Nutr
Pays: United States
ID NLM: 0404243

Informations de publication

Date de publication:
06 07 2022
Historique:
received: 04 01 2022
revised: 01 03 2022
accepted: 11 03 2022
pubmed: 16 3 2022
medline: 9 7 2022
entrez: 15 3 2022
Statut: ppublish

Résumé

The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet. We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women. Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50-79 y when enrolled during 1993-1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010-2014). Resulting biomarkers were used in a 450-participant biomarker study (2007-2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993-2020). Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption. A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

Sections du résumé

BACKGROUND
The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet.
OBJECTIVES
We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women.
METHODS
Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50-79 y when enrolled during 1993-1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010-2014). Resulting biomarkers were used in a 450-participant biomarker study (2007-2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993-2020).
RESULTS
Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption.
CONCLUSIONS
A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

Identifiants

pubmed: 35289908
pii: S0022-3166(22)00660-5
doi: 10.1093/jn/nxac067
pmc: PMC9258528
doi:

Substances chimiques

Biomarkers 0

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1711-1720

Subventions

Organisme : NIDA NIH HHS
ID : HHSN271201600004I
Pays : United States
Organisme : NCI NIH HHS
ID : U01 CA197902
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK035816
Pays : United States
Organisme : NIH HHS
ID : S10 OD021562
Pays : United States
Organisme : NCI NIH HHS
ID : P30 CA015704
Pays : United States
Organisme : NIDA NIH HHS
ID : HHSN271201600004C
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA119171
Pays : United States

Informations de copyright

© The Author(s) 2022. Published by Oxford University Press on behalf of the American Society for Nutrition.

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Auteurs

Cheng Zheng (C)

Department of Biostatistics, University of Nebraska Medical Center, Omaha, NE, USA.

Mary Pettinger (M)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

G A Nagana Gowda (GAN)

Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.

Johanna W Lampe (JW)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
School of Public Health, University of Washington, Seattle, WA, USA.

Daniel Raftery (D)

Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.

Lesley F Tinker (LF)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

Ying Huang (Y)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
School of Public Health, University of Washington, Seattle, WA, USA.

Sandi L Navarro (SL)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.

Diane M O'Brien (DM)

Institute for Arctic Biology, University of Alaska, Fairbanks, AK, USA.

Linda Snetselaar (L)

College of Public Health, University of Iowa, Iowa City, IA, USA.

Simin Liu (S)

Department of Epidemiology, School of Public Health, Brown University, Providence, RI, USA.

Robert B Wallace (RB)

College of Public Health, University of Iowa, Iowa City, IA, USA.

Marian L Neuhouser (ML)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
School of Public Health, University of Washington, Seattle, WA, USA.

Ross L Prentice (RL)

Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
School of Public Health, University of Washington, Seattle, WA, USA.

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