Dietary intake of animal-based products and likelihood of follicular lymphoma and survival: A population-based family case-control study.

animal product fish follicular lymphoma risk survival

Journal

Frontiers in nutrition
ISSN: 2296-861X
Titre abrégé: Front Nutr
Pays: Switzerland
ID NLM: 101642264

Informations de publication

Date de publication:
2022
Historique:
received: 19 09 2022
accepted: 12 12 2022
entrez: 23 1 2023
pubmed: 24 1 2023
medline: 24 1 2023
Statut: epublish

Résumé

The association between dietary intake of foods of animal origin and follicular lymphoma (FL) risk and survival is uncertain. In this study, we examined the relationship between dietary intake of dairy foods and fats, meat, fish and seafoods, and the likelihood of FL and survival. We conducted a population-based family case-control study in Australia between 2011 and 2016 and included 710 cases, 303 siblings and 186 spouse/partner controls. We assessed dietary intake of animal products prior to diagnosis (the year before last) using a structured food frequency questionnaire and followed-up cases over a median of 6.9 years using record linkage to national death data. We examined associations with the likelihood of FL using logistic regression and used Cox regression to assess association with all-cause and FL-specific mortality among cases. We observed an increased likelihood of FL with increasing daily quantity of oily fish consumption in the year before last (highest category OR = 1.96, CI = 1.02-3.77; Our study showed suggestive evidence of a positive association between oily fish intake and the likelihood of FL, but findings varied by control type. Further investigation of the potential role of environmental contaminants in oily fish on FL etiology is warranted.

Sections du résumé

Background UNASSIGNED
The association between dietary intake of foods of animal origin and follicular lymphoma (FL) risk and survival is uncertain. In this study, we examined the relationship between dietary intake of dairy foods and fats, meat, fish and seafoods, and the likelihood of FL and survival.
Methods UNASSIGNED
We conducted a population-based family case-control study in Australia between 2011 and 2016 and included 710 cases, 303 siblings and 186 spouse/partner controls. We assessed dietary intake of animal products prior to diagnosis (the year before last) using a structured food frequency questionnaire and followed-up cases over a median of 6.9 years using record linkage to national death data. We examined associations with the likelihood of FL using logistic regression and used Cox regression to assess association with all-cause and FL-specific mortality among cases.
Results UNASSIGNED
We observed an increased likelihood of FL with increasing daily quantity of oily fish consumption in the year before last (highest category OR = 1.96, CI = 1.02-3.77;
Conclusion UNASSIGNED
Our study showed suggestive evidence of a positive association between oily fish intake and the likelihood of FL, but findings varied by control type. Further investigation of the potential role of environmental contaminants in oily fish on FL etiology is warranted.

Identifiants

pubmed: 36687712
doi: 10.3389/fnut.2022.1048301
pmc: PMC9846614
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1048301

Informations de copyright

Copyright © 2023 Odutola, van Leeuwen, Bassett, Bruinsma, Turner, Seymour, Prince, Milliken, Hertzberg, Roncolato, Opat, Lindeman, Tiley, Trotman, Verner, Harvey, Underhill, Benke, Giles and Vajdic.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Michael K Odutola (MK)

Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, Australia.

Marina T van Leeuwen (MT)

Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, Australia.

Julie K Bassett (JK)

Cancer Epidemiology Division, Cancer Council Victoria, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.

Fiona Bruinsma (F)

Cancer Epidemiology Division, Cancer Council Victoria, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.

Jennifer Turner (J)

Douglass Hanly Moir Pathology, Macquarie Park, NSW, Australia.
Department of Clinical Medicine, Faculty of Medicine, Health and Human Science, Macquarie University, Sydney, NSW, Australia.

John F Seymour (JF)

Royal Melbourne Hospital, Peter MacCallum Cancer Centre, University of Melbourne, Melbourne, VIC, Australia.

Henry Miles Prince (HM)

Epworth Healthcare and Sir Peter MacCallum Department of Oncology, University of Melbourne, Parkville, VIC, Australia.

Samuel T Milliken (ST)

St. Vincent's Hospital, University of New South Wales, Sydney, NSW, Australia.

Mark Hertzberg (M)

Department of Haematology, Prince of Wales Hospital, University of New South Wales, Sydney, NSW, Australia.

Fernando Roncolato (F)

St. George Hospital, Kogarah, NSW, Australia.
St. George Clinical School, University of New South Wales, Kogarah, NSW, Australia.

Stephen S Opat (SS)

Clinical Haematology, Monash Health and Monash University, Clayton, VIC, Australia.

Robert Lindeman (R)

New South Wales Health Pathology, University of New South Wales, Sydney, NSW, Australia.

Campbell Tiley (C)

Gosford Hospital, The University of Newcastle, Callaghan, NSW, Australia.

Judith Trotman (J)

Concord Repatriation General Hospital, University of Sydney, Concord, NSW, Australia.

Emma Verner (E)

Concord Repatriation General Hospital, University of Sydney, Concord, NSW, Australia.

Michael Harvey (M)

Liverpool Hospital, Western Sydney University, Liverpool, NSW, Australia.

Craig R Underhill (CR)

Border Medical Oncology Research Unit, Rural Medical School, Albury, NSW, Australia.

Geza Benke (G)

School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.

Graham G Giles (GG)

Cancer Epidemiology Division, Cancer Council Victoria, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, VIC, Australia.
Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, VIC, Australia.

Claire M Vajdic (CM)

Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW, Australia.
The Kirby Institute, University of New South Wales, Sydney, NSW, Australia.

Classifications MeSH