Meat Intake and Mortality

INTRODUCTION

Meat intake varies substantially around the
world, but the impact of consuming higher levels
of meat in relation to chronic disease mortality
is ambiguous.1- 6 To increase sample size, pooled
analyses of meat intake have been carried out in
Seventh-Day Adventists in the United States1-2
and other vegetarian populations in Europe.3-6
Vegetarian diets differ from nonvegetarian diets
in several respects. The main sources of protein
in a vegetarian diet are legumes, grains, and
nuts. Vegetarian diets also include higher
intakes of vegetables, unsaturated fats, dietary
fiber, and antioxidants (carotenoids and vitamins
C and E), although they contain lower amounts of
iron, zinc, and vitamin B12. Furthermore, other
lifestyle factors, such as smoking, physical
activity, and alcohol consumption among
vegetarians and members of select religious
groups can differ substantially from the general
population.

We prospectively investigated red, white, and
processed meat intakes as risk factors for total
mortality, as well as cause-specific mortality,
including cancer and cardiovascular disease (CVD)
mortality in a cohort of approximately half a
million men and women enrolled in the National
Institutes of Health (NIH)-AARP (formerly known
as the American Association of Retired Persons)
Diet and Health Study.7 This large prospective
study facilitated the investigation of a wide
range of meat intakes with chronic disease
mortality.

STUDY POPULATION

Individuals aged 50 to 71 years were recruited
from 6 US states (California, Florida, Louisiana,
New Jersey, North Carolina, and Pennsylvania) and
2 metropolitan areas (Atlanta, Georgia, and
Detroit, Michigan) to form a large prospective
cohort, the NIH-AARP Diet and Health Study.
Questionnaires on demographic and lifestyle
characteristics, including dietary habits, were
mailed to 3.5 million members of AARP in 1995, as
described in detail elsewhere.7 The NIH-AARP Diet
and Health Study was approved by the Special
Studies Institutional Review Board of the US
National Cancer Institute. Completion of the
baseline questionnaire was considered to imply
informed consent.

DIETARY ASSESSMENT

A 124-item food frequency questionnaire
(http://riskfactor. cancer.gov/ DHQ/forms/ files/shared/ dhq1.2002. sample.pdf)
was completed at baseline. The food frequency
questionnaire collected information on the usual
consumption of foods and drinks and portion sizes
over the last 12 months. The validity of the food
frequency questionnaire was estimated using two
24-hour recalls,8 and the estimated
energy-adjusted correlations ranged from 0.36 to
0.76 for various nutrients and attenuation
factors ranged from 0.24 to 0.68. Red meat intake
was calculated using the frequency of consumption
and portion size information of all types of beef
and pork and included bacon, beef, cold cuts,
ham, hamburger, hotdogs, liver, pork, sausage,
steak, and meats in foods such as pizza, chili,
lasagna, and stew. White meat included chicken,
turkey, and fish and included poultry cold cuts,
chicken mixtures, canned tuna, and low-fat
sausages and low-fat hotdogs made from poultry.
Processed meat included bacon, red meat sausage,
poultry sausage, luncheon meats (red and white
meat), cold cuts (red and white meat), ham,
regular hotdogs and low-fat hotdogs made from
poultry. The components constituting red or white
and processed meats can overlap because both can
include meats such as bacon, sausage, and ham,
while processed meat can also included smoked
turkey and chicken. However, these meat groups
are not used in the same models; thus, they are
not duplicated in any one analysis.

To investigate whether the overall composition
of meat intake was associated with mortality, we
created 3 diet types: high-, medium-, and
low-risk meat diet. To form these diet variables,
red and white meat consumption was energy
adjusted and split into 2 groups using the median
values as cut points. Individuals with red meat
consumption in the upper half and white meat
consumption in the lower half got a score of 1
(high-risk meat diet), those with both red and
white meat consumption in the same half got a
score of 2 (medium-risk meat diet), and those
with red meat consumption in the lower half and
white meat consumption in the upper half got a
score of 3 (low-risk meat diet).

COHORT FOLLOW-UP AND CASE ASCERTAINMENT

Cohort members were followed-up from the date
the baseline questionnaire was returned
(beginning 1995) through December 31, 2005, by
annual linkage of the cohort to the National
Change of Address database maintained by the US
Postal Service and through processing of
undeliverable mail, other address change update
services, and directly from cohort members'
notifications. For matching purposes, we have
virtually complete data on first and last name,
address history, sex, and date of birth.
Follow-up for vital status is performed by annual
linkage of the cohort to the Social Security
Administration Death Master File in the US
verification of vital status, and cause of death
information is provided by follow-up searches of
the National Death Index (NDI) Plus with the
current follow-up for mortality covered until
2005.

CAUSE-SPECIFIC CASE ASCERTAINMENT

Cancer (International Classification of
Diseases, Ninth Revision [ICD-9] codes 140-239
and International Statistical Classification of
Diseases, 10th Revision [ICD-10] codes C00-C44,
C45.0, C45.1, C45.7, C45.9, C48-C97, and D12-D48)
mortality included deaths due to cancers of the
oral cavity and pharynx, digestive tract,
respiratory tract, soft tissue (including heart),
skin (excluding basal and squamous cell
carcinoma), female genital system and breast,
male genital system, urinary tract, endocrine
system, lymphoma, leukemia, and other
miscellaneous cancers.

Cardiovascular disease (ICD-9 codes 390-398,
401-404, 410-438, and 440-448 and ICD-10 codes
I00-I09, I10-I13, I20-I51, and I60-I78) mortality
was from a combination of diseases of the heart;
hypertension without heart disease;
cerebrovascular diseases; atherosclerosis; aortic
aneurysm and dissection; and other diseases of
the arteries, arterioles, and capillaries.

Mortality from injuries and sudden deaths (ICD-9
codes 800-978 and ICD-10 codes U01-U03, V01-Y09,
Y35, Y85-Y86, Y87.0, Y87.1, and Y89.0) included
deaths due to unintentional injury, adverse
effects, suicide, self-inflicted injury,
homicide, and legal intervention.

All others deaths included mortality from
tuberculosis, human immunodeficiency virus, other
infectious and parasitic diseases, septicemia,
diabetes mellitus, Alzheimer disease, stomach and
duodenal ulcers, pneumonia and influenza, chronic
obstructive pulmonary disease and allied
conditions, chronic liver disease and cirrhosis,
nephritis, nephrotic syndrome and nephrosis,
congenital anomalies, certain conditions
originating in the perinatal period, ill-defined
conditions, and unknown causes of death.

Total mortality is a combination of all of the
aforementioned causes of deaths.

STATISTICAL ANALYSIS

A total of 617 119 persons returned the baseline
questionnaire; of these, we excluded individuals
who moved out of the 8 study areas before
returning the baseline questionnaire (n = 321),
requested to be withdrawn from the study
(n = 829), died before study entry (n = 261), had
duplicate records (n = 179), indicated that they
were not the intended respondent and did not
complete the questionnaire (n = 13 442), provided
no information on gender (n = 6), and did not
answer substantial portions of the questionnaire
or had more than 10 recording errors
(n = 35 679). After these exclusions, we further
removed individuals whose questionnaire was
filled in by someone else on their behalf
(n = 15 760). We excluded 4849 subjects reporting
extreme daily total energy intake defined as more
than 2 interquartile ranges above the 75th
percentile or below the 25th percentile and 140
people who had zero person-years of follow-up.
After all exclusions, our analytic cohort
comprised 322 263 men and 223 390 women.

We estimated hazard ratios (HRs) and 95%
confidence intervals (CIs) with time since entry
into the study as the underlying time metric
using Cox proportional hazards regression models.
Quintile cut points were based on the entire
cohort, and multivariate- adjusted HRs are
reported using the lowest quintile as the
referent category. The violation of the
proportional hazard assumption was investigated
by testing an interaction between a
time-dependent binary covariate, which indicated
if follow-up was in the first 5 years or in the
second 5 years, and the quintile terms for meat
consumption. Dietary variables were energy
adjusted using the nutrient density method, and
meat variables in each model added up to total
meat (addition model). For example, one model
contained both red and white meat, while the
processed meat model also contained a
nonprocessed meat variable.

To address confounding, we used forward stepwise
variable selection to include covariates to
develop the fully adjusted model. Smoking was the
largest confounder of the association between
meat intake and mortality. Physical activity and
education were also important covariates, but not
to the same degree as smoking. The final model
included age (continuous) ; education (<8 years or
unknown, 8-11 years, 12 years [high school], some
college, or college graduate); marital status
(married: yes/no); family history of cancer
(yes/no) (cancer mortality only); race
(non-Hispanic white, non-Hispanic black,
Hispanic/Asian/ Pacific Islander/American
Indian/Alaskan native, or unknown); body mass
index (18.5 to <25, 25 to <30, 30 to <35, 35
[calculated as weight in kilograms divided by
height in meters squared]); 31-level smoking
history using smoking status (never, former, or
current), time since quitting for former smokers
and smoking dose; frequency of vigorous physical
activity (never/rarely, 1-3 times/mo, 1-2
times/wk, 3-4 times/wk, 5 times/wk); total energy
intake (continuous) ; alcohol intake (none, 0 to
<5, 5 to <15, 15 to <30, 30 g/d); vitamin
supplement user (1 supplement/mo) ; fruit
consumption (0 to <0.7, 0.7 to <1.2, 1.2 to <1.7,
1.7 to <2.5, 2.5 servings/1000 kcal); vegetable
consumption (0 to <1.3, 1.3 to <1.8, 1.8 to <2.2,
2.2 to <3.0, 3.0 servings/1000 kcal); and
menopausal hormone therapy among women in the
multivariate models.

In subanalyses, we investigated the relation
between meat intake and mortality by smoking
status. We used median values of each quintile to
test for linear trend with 2-sided P values. We
also calculated population-attribut able risks as
an estimate of the percentage of mortality that
could be prevented if individuals adopted intake
levels of participants within the first quintile.
This was computed as 1 minus the ratio consisting
of the sum of the estimated HR (derived from the
Cox proportional hazard regression models) of
each member of the cohort divided by the sum of
the estimated HR for which meat exposure was
assigned to the lowest or highest quintile,
depending on which quintile was the ideal level
of meat consumption. The population-attribut able
risk was multiplied by 100 to convert them to a
percentage. All statistical analyses were carried
out using Statistical Analytic Systems (SAS)
software (SAS Institute Inc, Cary, North
Carolina).

During 10 years of follow-up, there were 47 976
male deaths and 23 276 female deaths. In general,
those in the highest quintile of red meat intake
tended to consume a slightly lower amount of
white meat but a higher amount of processed meat
compared with those in the lowest quintile.
Subjects who consumed more red meat tended to be
married, more likely of non-Hispanic white
ethnicity, more likely a current smoker, have a
higher body mass index, and have a higher daily
intake of energy, total fat, and saturated fat,
and they tended to have lower education and
physical activity levels and lower fruit,
vegetable, fiber, and vitamin supplement intakes
(Table 1).

Table 1. Selected Age-Adjusted Characteristics
of the National Institutes of Health-AARP Cohort
by Red Meat Quintile Categorya

RED MEAT

There was an overall increased risk of total,
cancer, and CVD mortality, as well as all other
deaths in both men (Table 2) and women (Table 3)
in the highest compared with the lowest quintile
of red meat intake in the fully adjusted model.
There was an increased risk associated with death
from injuries and sudden death with higher
consumption of red meat in men but not in women.

Table 2. Multivariate Analysis for Red, White,
and Processed Meat Intake and Total and
Cause-Specific Mortality in Men in the National
Institutes of Health-AARP Diet and Health Studya

Table 3. Multivariate Analysis Red, White, and
Processed Meat Intake and Total and
Cause-Specific Mortality in Women in the National
Institutes of Health-AARP Diet and Health Studya

WHITE MEAT

When comparing the highest with the lowest
quintile of white meat intake, there was an
inverse association for total mortality and
cancer mortality, as well as all other deaths for
both men (Table 2) and women (Table 3). In
contrast, there was a small increase in risk for
CVD mortality in men with higher intake of white
meat. There was no association between white meat
consumption and death from injuries and sudden
death in men or women.

PROCESSED MEAT

There was an overall increased risk of total,
cancer, and CVD mortality, as well as all other
deaths in both men (Table 2) and women (Table 3)
in the highest compared with the lowest quintile
of processed meat intake. In contrast, there was
no association for processed meat intake and
death from injuries and sudden death in either
sex.

A lag analysis, excluding deaths occurring in
the first 2 years of follow-up, produced results
consistent with the main findings in Table 2 and
Table 3. For example, the HRs for total mortality
in men for red meat was as follows: second
quintile HR, 1.05 (95% CI, 1.01-1.09); third
quintile HR, 1.13 (95% CI, 1.09-1.17); fourth
quintile HR, 1.20 (95% CI, 1.16-1.24); and fifth
quintile HR, 1.30 (95% CI, 1.26-1.35). For women,
the HRs were as follows: second quintile HR, 1.07
(95% CI, 1.02-1.12); third quintile HR, 1.15 (95%
CI, 1.11-1.21); fourth quintile HR, 1.27 (95% CI,
1.21-1.33); and fifth quintile HR, 1.35 (95% CI,
1.28-1.42). Furthermore, we investigated our
models for a violation of the proportional hazard
assumption. Proportional hazard assumption was
not rejected for all analyses except one, the
model with red and white meat among the women for
total mortality (P = .008). On further
examination in that model of the relative HR
between the first 5 years of follow-up and the
second 5 years of follow-up, the red meat results
were consistent between the 2 follow-up periods.
However, for white meat, the second 5-year period
showed less of an inverse trend compared with the
first 5-year period (data not shown).

We investigated whether people who consumed a
high-risk meat diet had mortality risk profiles
that were different from people who consumed a
low-risk meat diet. Both men and women who
consumed a low-risk meat diet had statistically
significant lower HRs compared with people who
consumed a high-risk meat diet for all-cause,
cancer, and CVD mortality, as well as all other
deaths; for example, for all-cause mortality, the
HR for a low-risk meat diet was 0.92 (95% CI,
0.80-0.94) for men and 0.80 (95% CI, 0.78-0.84)
for women.

To further explore possible confounding by
smoking, we analyzed meat intake and mortality in
2 subgroups-never smokers (15 413 deaths among
190 135 never smokers) and former/current smokers
(n = 52 754 deaths among 335 036 former/current
smokers). For men, the risks in the fifth
quintile of red meat intake for never and
former/current smokers were as follows: for total
mortality, HR, 1.28 (95% CI, 1.19-1.38), and HR,
1.25 (95% CI, 1.20-1.30), respectively; for
cancer mortality, HR, 1.16 (95% CI, 1.02-1.33),
and HR, 1.17 (95% CI, 1.09-1.24), respectively;
and for CVD mortality, HR, 1.43 (95% CI,
1.25-1.63), and HR, 1.17 (95% CI, 1.10-1.26),
respectively. In women, the risks in the fifth
quintile of red meat intake for never and
former/current smokers were as follows: for total
mortality, HR, 1.36 (95% CI, 1.25-1.48), and HR,
1.28 (95% CI, 1.21-1.35), respectively; for
cancer mortality, HR, 1.10 (95% CI, 0.95-1.27),
and HR, 1.16 (95% CI, 1.06-1.27), respectively;
and for CVD mortality, HR, 1.63 (95% CI,
1.38-1.93), and HR, 1.34 (95% CI, 1.18-1.51),
respectively. Risks were similar for the 2
smoking categories in most instances for
processed meat except for cancer mortality, for
which we found a null relation for both sexes in
never smokers (men: HR, 1.01 [95% CI, 0.88-1.15];
women: HR, 1.02 [95% CI, 0.89-1.17]), but in
former/current smokers we found higher risks
(men: HR, 1.12 [95% CI, 1.05-1.19]; women: HR,
1.11 [95% CI, 1.02-1.21]). Intriguingly, there
was increased risk with higher intake of white
meat for CVD mortality in never smokers (men: HR,
1.24 [95% CI, 1.10-1.40]; women: HR, 1.20 [95%
CI, 1.03-1.41]).

We calculated the population attributable risks,
representing the percentage of deaths that could
be prevented if individuals adopted red or
processed meat intake levels of participants
within the first quintile. For overall mortality,
11% of deaths in men and 16% of deaths in women
could be prevented if people decreased their red
meat consumption to the level of intake in the
first quintile. The impact on CVD mortality was
an 11% decrease in men and a 21% decrease in
women if the red meat consumption was decreased
to the amount consumed by individuals in the
first quintile. The median red meat consumption
based on men and women in the first quintile was
9.8 g/1000 kcal/d compared with 62.5 g/1000
kcal/d in the fifth quintile. For women eating
processed meat at the first quintile level, the
decrease in CVD mortality was approximately 20%.
The median processed meat consumption based on
men and women in the first quintile was 1.6
g/1000 kcal/d compared with 22.6 g/1000 kcal/d in
the fifth quintile.

References

We examined total and cause-specific mortality
in relation to meat consumption in a large
prospective study. We found modest increases in
risk for total mortality, as well as cancer and
CVD mortality, with higher intakes of red and
processed meat in both men and women. In
contrast, higher white meat consumption was
associated with a small decrease in total and
cancer mortality in men and women.

The principal strength of this study is the
large size of the cohort, which provided us the
ability to investigate the relationship of many
deaths (47 976 male deaths and 23 276 female
deaths) within the context of a single study with
a standardized protocol and a wide range of meat
consumption. In contrast, other reports
investigating meat intake in relation to
mortality have pooled data from different studies
conducted in California, the United Kingdom, and
Germany because the numbers of events were
limited in each study.1-6,9- 14 The protocols and
questionnaires in these studies were different,
as were the populations: Seventh-Day Adventists
in California and vegetarians and nonvegetarians
in Europe. Pooled analyses of specialized
populations with distinct healthy lifestyles are
subject to unmeasured confounding. Furthermore,
recall bias and reverse causality were minimized
in our study because diet was assessed prior to
the diagnosis of the conditions that led to death.

There is a possibility that some residual
confounding by smoking may remain; however, we
used a detailed 31-level smoking history variable
and repeated the analyses within smoking status
strata. Within smoking subgroups, we found
consistent results for red, white, and processed
meat intakes; however, there were some intriguing
differences that could be further investigated.
We found a positive association for processed
meat intake and cancer mortality among
former/current smokers but not among never
smokers. This may be because we were still not
able to fully statistically adjust for residual
confounding of smoking because people who eat
processed meat may also smoke. An additional
reason could be that in addition to being exposed
to N-nitroso compounds from processed meats,
smokers inhale carcinogenic chemicals. The
possible reason why there was an increased risk
with white meat consumption among never smokers
is not readily apparent.

Because our cohort was predominantly
non-Hispanic white, more educated, consumed less
fat and red meat and more fiber and fruits and
vegetables, and had fewer current smokers than
similarly aged adults in the US population,
caution should be applied when attempting to
generalize our findings to other populations, 7
although this caution is somewhat tempered
because it is unlikely that the mechanisms
relating meat to mortality differ quantitatively
between our study population and other white
populations older than 50 years. Furthermore, the
population-attribut able risks in our cohort may
be conservative estimates because red and
processed meat consumption may be higher in the
general population than in our cohort.

The inherent limitations of measurement error in
this study are similar to those of any
nutritional epidemiologic study that is based on
recall of usual intake over a given period. We
attempted to reduce measurement error by
adjusting our models for reported energy
intake.15 The correlations for red meat
consumption assessed from the food frequency
questionnaire compared with two 24-hour recall
diaries were 0.62 for men and 0.70 for women, as
reported previously by Schatzkin et al.7 The
problem of residual confounding may still exist
and could explain the relatively small
associations found throughout this study despite
the care taken to adjust for known confounders.

Overall, we did not find statistically
significant association between meat consumption
and deaths from injury and sudden deaths in most
instances. The relative HRs of meat consumption
with the other causes of death (total, cancer,
and CVD mortality) were similar in magnitude in
some cases to those of deaths from injury and
sudden deaths; however, the number of deaths from
injury and sudden deaths was less than the other
causes of deaths, and thus the HRs were generally
not statistically significant. We observed a
higher risk with the category that included "all
other deaths"; this is a broad category with many
heterogeneous conditions (eg, diabetes mellitus,
Alzheimer disease, stomach and duodenal ulcers,
chronic liver disease, cirrhosis, nephritis,
nephrotic syndrome, and nephrosis), some of which
may be positively related to meat intake.

There are various mechanisms by which meat may
be related to mortality. In relation to cancer,
meat is a source of several multisite
carcinogens, including heterocyclic amines and
polycyclic aromatic hydrocarbons, 16-21 which are
both formed during high-temperature cooking of
meat, as well as N-nitroso compounds.22- 23 Iron
in red meat may increase oxidative damage and
increase the formation of N-nitroso
compounds.24- 27 Furthermore, meat is a major
source of saturated fat, which has been
positively associated with breast28-30 and
colorectal cancer.31

In relation to CVD, elevated blood pressure has
been shown to be positively associated with
higher intakes of red and processed meat, even
though the mechanism is unclear, except that
possibly meat may substitute for other beneficial
foods such as grains, fruits, or vegetables.32
Mean plasma total cholesterol, low-density
lipoprotein cholesterol, very-low-density
lipoprotein cholesterol, and triglyceride levels
were found to be decreased in subjects who
substituted red meat with fish.33-34 Vegetarians
have lower arachidonic, eicosapentaenoic, and
docosahexaenoic acid levels and higher linoleate
and antioxidant levels in platelet phospholipids;
such a biochemical profile may be related to
decreased atherogenesis and thrombogenesis. 34-36

Red and processed meat intakes, as well as a
high-risk meat diet, were associated with a
modest increase in risk of total mortality,
cancer, and CVD mortality in both men and women.
In contrast, high white meat intake and a
low-risk meat diet was associated with a small
decrease in total and cancer mortality. These
results complement the recommendations by the
American Institute for Cancer Research and the
World Cancer Research Fund to reduce red and
processed meat intake to decrease cancer
incidence.31 Future research should investigate
the relation between subtypes of meat and
specific causes of mortality.