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Meat consumption and risk of 25 common conditions: outcome-wide analyses in 475,000
men and women in the UK Biobank study
Keren Papier*, Georgina K Fensom, Anika Knuppel, Paul N Appleby, Tammy YN Tong,
Julie A Schmidt, Ruth C Travis, Timothy J Key, Aurora Perez-Cornago
Affiliation of all authors: Cancer Epidemiology Unit, Nuffield Department of Population
Health, University of Oxford, Oxford, OX3 7LF, UK.
Correspondence to: Dr Keren Papier (Keren.Papier@ndph.ox.ac.uk)
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NOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.
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Abstract
Background There is limited prospective evidence on the association between meat
consumption and many common, non-cancerous health outcomes. We examined associations
of meat intake with risk of 25 common conditions (other than cancer).
Methods We used data from 474 998 middle-aged men and women recruited into the UK
Biobank study between 2006 and 2010 and followed-up until 2017 (mean follow-up of 8.0
years) with available information on meat intake at baseline (collected via touchscreen
questionnaire), and linked hospital admissions and mortality data. For a large sub-sample,
dietary intakes were re-measured using an online, 24-hour questionnaire.
Results In multi-variable adjusted (including body mass index (BMI)) Cox regression models
corrected for multiple testing, a higher consumption of red and processed meat combined was
associated with higher risks of ischaemic heart disease (HR per 70 g/day higher intake 1.14,
95% CI 1.06-1.22), pneumonia (1.28,1.15-1.41), diverticular disease (1.18,1.10-1.26), colon
polyps (1.09,1.04-1.13), and diabetes (1.29,1.19-1.40), and a lower risk of iron deficiency
anaemia (IDA), driven by a higher consumption of red meat (HR per 50g/day higher intake
0.77,0.69-0.86). Higher poultry meat intake was associated with higher risks of gastro-
oesophageal reflux disease (HR per 30g/day higher intake 1.14, 1.06-1.23), gastritis and
duodenitis (1.10,1.04-1.16), diverticular disease (1.09,1.04-1.16), and diabetes (1.13,1.06-
1.20), and a lower risk of IDA (0.80,0.73-0.87).
Conclusions Higher red, processed, and poultry meat consumption was associated with
higher risks of several common conditions; higher BMI accounted for a substantial proportion
of these increased risks. Higher red and poultry meat consumption was associated with lower
IDA risk.
. CC-BY 4.0 International licenseIt is made available under a
is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted May 13, 2020. ; https://doi.org/10.1101/2020.05.04.20085225doi: medRxiv preprint
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Introduction
The World Health Organization
1
and many national dietary advice bodies (e.g. the UK
dietary guidelines
2
) have in recent years recommended the reduction of red and processed
meat consumption, based on consistent evidence linking high processed meat, and probably
red meat consumption with colorectal cancer risk
1
. While the association between meat
intake and cancer risk has been comprehensively studied
3,4
there is little information on the
association between meat consumption, especially poultry meat, and incidence of major non-
cancerous health outcomes
5
. This lack of evidence might relate to outcome selection bias (i.e.
only reporting the outcomes that are found to be associated with meat
6
), differences in the
definition of outcomes, sample size, control of confounders and/or length of follow-up used
among different studies. Examining the association between meat consumption and multiple
non-cancerous health outcomes in the same cohort may help to clarify these associations
7
.
This study uses an outcome-wide approach to prospectively examine associations of meat
consumption with risk of 25 common conditions identified as the 25 leading causes of
hospital admission (other than cancer) in a large UK cohort.
Methods
Study population
We used data from the UK Biobank study, a cohort of 503 317 men and women from across
the UK
8
. Potential participants were recruited through the National Health Service (NHS)
Patient Registers and invited to attend one of the 22 assessment centres between 2006 and
2010. Participants joining the study completed a baseline touchscreen questionnaire, provided
anthropometric and biological data, and gave informed consent for their health to be
followed-up through linkage to electronic medical records. The UK Biobank study was
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is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
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approved by the North West Multi-Centre Research Ethics Committee (reference number
06/MRE08/65).
Assessment of dietary intake
Dietary intake was assessed using a touchscreen dietary questionnaire administered to all
participants at baseline that included 29 questions on diet, assessing the consumption
frequency of each listed food. Responses to the five questions on meat (unprocessed beef,
unprocessed lamb/mutton, unprocessed pork, unprocessed poultry, and processed meat) were
assigned values for frequency per week (never=0, less than once per week = 0.5, once per
week=1, 2-4 times per week=3, 5-6 times per week=5.5, and once or more a day=7). We then
categorized these meat intake frequencies into three or four categories to create
approximately equal-sized groups (see Supplementary Methods S1 for additional detail).
Participants recruited after 2009, as well as participants who provided UK Biobank with an
email address and agreed to be re-contacted, additionally filled out the Oxford WebQ
9
, an
online 24-hour recall questionnaire. Participants were asked to select how many portions of
each food item they consumed over the previous 24-hours, enabling calculation of mean
grams per/day by multiplying frequencies of consumption by standard portion sizes. Similar
foods were then grouped together into meat types to match the touchscreen dietary
questionnaire. We then assigned the mean WebQ intakes in participants who had completed
at least three WebQs to each touchscreen category (see Supplementary Methods S1 for
additional detail).
Assessment of health outcomes
The main outcomes of interest in this study were incident cases of 25 common conditions.
The conditions selected were those identified as the 25 leading, well-defined causes of non-
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cancerous hospital admission in this cohort based on the primary International Classification
of Diseases (ICD) 10 diagnosis codes recorded during admission. Some of commonest causes
of hospital admission in this cohort (e.g. nausea or heartburn) were not considered to be
separate conditions, because they were not well-defined and/or were likely to be associated
with a diverse range of underlying conditions. Moreover, although diabetes was not among
the 25 most common primary diagnoses associated with admission, it is a common secondary
reason for admission and therefore any diagnosis of diabetes was included among the 25
common conditions examined. (See supplementary Table S1 for selected conditions and
relevant diagnosis and procedure codes.)
Participant information on cause-specific in-patient hospital admissions and deaths (primary
cause for all outcomes except diabetes which also included underlying cause) was obtained
through linkage to the NHS Central Registers. For participants in England, Hospital Episode
Statistics (HES) and information on date and cause of death were available until the 31st of
March 2017; for participants in Scotland, the Scottish Morbidity Records and information on
date and cause of death were available until the 31st of October 2016; and for participants in
Wales, the Patient Episode Database and information on date and cause of death were
available until the 29th of February 2016. We also obtained information on cancer
registrations (including date and cancer site) from the NHS Central Registers. (See
Supplementary Methods S2 and Supplementary Table S1 for information on exclusion,
diagnosis and procedure codes).
Exclusions
Of the 503 317 recruited participants, 28 319 were excluded due to study withdrawals,
prevalent cancer (except non-melanoma skin cancer, ICD-10 C44) prior to recruitment, or
because their genetic sex differed from their reported gender, resulting in a maximal study
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is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)
The copyright holder for this preprint this version posted May 13, 2020. ; https://doi.org/10.1101/2020.05.04.20085225doi: medRxiv preprint
