Meat Intake and Mortality (Annals of Internal Medicine)

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http://archinte.ama-assn.org/cgi/content/full/169/6/562

 

Vol. 169 No. 6, March 23, 2009

 

 

Meat Intake and Mortality

 

A Prospective Study of Over Half a Million People

 

Rashmi Sinha, PhD; Amanda J. Cross, PhD; Barry

I. Graubard, PhD; Michael F. Leitzmann, MD,

DrPH; Arthur Schatzkin, MD, DrPH

 

 

Arch Intern Med. 2009;169(6):562-571.

 

ABSTRACT

 

Background High intakes of red or processed

meat may increase the risk of mortality. Our

objective was to determine the relations of red,

white, and processed meat intakes to risk for

total and cause-specific mortality.

 

Methods The study population included the

National Institutes of Health-AARP (formerly

known as the American Association of Retired

Persons) Diet and Health Study cohort of half a

million people aged 50 to 71 years at baseline.

Meat intake was estimated from a food frequency

questionnaire administered at baseline. Cox

proportional hazards regression models estimated

hazard ratios (HRs) and 95% confidence intervals

(CIs) within quintiles of meat intake. The

covariates included in the models were age,

education, marital status, family history of

cancer (yes/no) (cancer mortality only), race,

body mass index, 31-level smoking history,

physical activity, energy intake, alcohol intake,

vitamin supplement use, fruit consumption,

vegetable consumption, and menopausal hormone

therapy among women. Main outcome measures

included total mortality and deaths due to

cancer, cardiovascular disease, injuries and

sudden deaths, and all other causes.

 

Results There were 47 976 male deaths and 23 276

female deaths during 10 years of follow-up. Men

and women in the highest vs lowest quintile of

red (HR, 1.31 [95% CI, 1.27-1.35], and HR, 1.36

[95% CI, 1.30-1.43], respectively) and processed

meat (HR, 1.16 [95% CI, 1.12-1.20], and HR, 1.25

[95% CI, 1.20-1.31], respectively) intakes had

elevated risks for overall mortality. Regarding

cause-specific mortality, men and women had

elevated risks for cancer mortality for red (HR,

1.22 [95% CI, 1.16-1.29], and HR, 1.20 [95% CI,

1.12-1.30], respectively) and processed meat (HR,

1.12 [95% CI, 1.06-1.19], and HR, 1.11 [95% CI

1.04-1.19], respectively) intakes. Furthermore,

cardiovascular disease risk was elevated for men

and women in the highest quintile of red (HR,

1.27 [95% CI, 1.20-1.35], and HR, 1.50 [95% CI,

1.37-1.65], respectively) and processed meat (HR,

1.09 [95% CI, 1.03-1.15], and HR, 1.38 [95% CI,

1.26-1.51], respectively) intakes. 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 and women.

 

Conclusion Red and processed meat intakes were

associated with modest increases in total

mortality, cancer mortality, and cardiovascular

disease 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.

 

 

METHODS

 

 

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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/formsshared/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-attributable 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-attributable

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.

 

 

COMMENT

 

 

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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-attributable 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.

 

 

AUTHOR INFORMATION

 

 

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Correspondence: Rashmi Sinha, PhD, Division of

Cancer Epidemiology and Genetics, National Cancer

Institute-Nutritional Epidemiology Branch, 6120

Executive Blvd, Rockville, MD 20852

(sinhar).

 

Accepted for Publication: October 24, 2008.

 

Author Contributions: Drs Sinha and Cross had

full access to the data in the study and take

responsibility for the integrity of the data and

the accuracy of the data analysis. All authors

have given full approval to the final manuscript.

Study concept and design: Sinha, Cross, and

Graubard. Acquisition of data: Sinha and

Schatzkin. Analysis and interpretation of data:

Sinha, Cross, Graubard, Leitzmann, and Schatzkin.

Drafting of the manuscript: Sinha, Cross, and

Graubard. Critical revision of the manuscript for

important intellectual content: Sinha, Cross,

Graubard, Leitzmann, and Schatzkin. Statistical

analysis: Sinha, Graubard, and Leitzmann.

Obtained funding: Schatzkin. Administrative,

technical, and material support: Cross and

Schatzkin.

 

Financial Disclosure: None reported.

 

Funding/Support: This research was supported in

part by the Intramural Research Program of the

NIH, National Cancer Institute (NCI).

 

Additional Contributions: Adam Risch, Leslie

Carroll, MA, and Dave Campbell from Information

Management Services Inc, and Traci Mouw, MS, from

NCI, assisted in data management. We are indebted

to the participants in the NIH-AARP Diet and

Health Study for their outstanding cooperation.

Cancer incidence data from the Atlanta

metropolitan area were collected by the Georgia

Center for Cancer Statistics, Department of

Epidemiology, Rollins School of Public Health,

Emory University. Cancer incidence data from

California were collected by the California

Department of Health Services, Cancer

Surveillance Section. Cancer incidence data from

the Detroit metropolitan area were collected by

the Michigan Cancer Surveillance Program,

Community Health Administration. The Florida

cancer incidence data used in this report were

collected by the Florida Cancer Data System under

contract to the Department of Health (DOH) (the

views expressed herein are solely those of the

authors and do not necessarily reflect those of

the contractor or the DOH). Cancer incidence data

from Louisiana were collected by the Louisiana

Tumor Registry, Louisiana State University

Medical Center in New Orleans. Cancer incidence

data from New Jersey were collected by the New

Jersey State Cancer Registry, Cancer Epidemiology

Services, New Jersey State Department of Health

and Senior Services. Cancer incidence data from

North Carolina were collected by the North

Carolina Central Cancer Registry. Cancer

incidence data from Pennsylvania were supplied by

the Division of Health Statistics and Research,

Pennsylvania Department of Health, Harrisburg

(the Pennsylvania Department of Health

specifically disclaims responsibility for any

analyses, interpretations, or conclusions).

 

Author Affiliations: Nutritional Epidemiology

Branch (Drs Sinha, Cross, Leitzmann, and

Schatzkin) and Biostatistics Branch (Dr

Graubard), Division of Cancer Epidemiology and

Genetics, National Cancer Institute, National

Institutes of Health, Department of Health and

Human Services, Rockville, Maryland.

 

REFERENCES

 

 

1. Fraser GE. Associations between diet and

cancer, ischemic heart disease, and all-cause

mortality in non-Hispanic white California

Seventh-day Adventists. Am J Clin Nutr.

1999;70(3)(suppl):532S-538S. FREE FULL TEXT

 

2. Kahn HA, Phillips RL, Snowdon DA, Choi W.

Association between reported diet and all-cause

mortality: twenty-one-year follow-up on 27,530

adult Seventh-Day Adventists. Am J Epidemiol.

1984;119(5):775-787. FREE FULL TEXT

 

3. Appleby PN, Key TJ, Thorogood M, Burr ML, Mann

J. Mortality in British vegetarians. Public

Health Nutr. 2002;5(1):29-36. FULL TEXT | ISI

| PUBMED

 

4. Key TJ, Fraser GE, Thorogood M; et al.

Mortality in vegetarians and non-vegetarians: a

collaborative analysis of 8300 deaths among

76,000 men and women in five prospective studies.

Public Health Nutr. 1998;1(1):33-41. FULL TEXT

| PUBMED

 

5. Key TJ, Fraser GE, Thorogood M; et al.

Mortality in vegetarians and nonvegetarians:

detailed findings from a collaborative analysis

of 5 prospective studies. Am J Clin Nutr.

1999;70(3)(suppl):516S-524S. FREE FULL TEXT

 

6. Thorogood M, Mann J, Appleby P, McPherson K.

Risk of death from cancer and ischaemic heart

disease in meat and non-meat eaters. BMJ.

1994;308(6945):1667-1670. FREE FULL TEXT

 

7. Schatzkin A, Subar AF, Thompson FE; et al.

Design and serendipity in establishing a large

cohort with wide dietary intake distributions:

the National Institutes of Health-American

Association of Retired Persons Diet and Health

Study. Am J Epidemiol. 2001;154(12):1119-1125.

FREE FULL TEXT

 

8. Thompson FE, Kipnis V, Midthune D; et al.

Performance of a food-frequency questionnaire in

the US NIH-AARP (National Institutes of

Health-American Association of Retired Persons)

Diet and Health Study. Public Health Nutr.

2008;11(2):183-195. ISI | PUBMED

 

9. Beeson WL, Mills PK, Phillips RL, Andress M,

Fraser GE. Chronic disease among Seventh-day

Adventists, a low-risk group: rationale,

methodology, and description of the population.

Cancer. 1989;64(3):570-581. FULL TEXT | ISI |

PUBMED

 

10. Sanjoaquin MA, Appleby PN, Thorogood M, Mann

JI, Key TJ. Nutrition, lifestyle and colorectal

cancer incidence: a prospective investigation of

10998 vegetarians and non-vegetarians in the

United Kingdom. Br J Cancer. 2004;90(1):118-121.

FULL TEXT | ISI | PUBMED

 

11. Appleby PN, Thorogood M, Mann JI, Key TJ. The

Oxford Vegetarian Study: an overview. Am J Clin

Nutr. 1999;70(3)(suppl):525S-531S. FREE FULL TEXT

 

12. Appleby PN, Thorogood M, Mann JI, Key TJ. Low

body mass index in non-meat eaters: the possible

roles of animal fat, dietary fibre and alcohol.

Int J Obes Relat Metab Disord.

1998;22(5):454-460. FULL TEXT | ISI | PUBMED

 

13. Mann JI, Appleby PN, Key TJ, Thorogood M.

Dietary determinants of ischaemic heart disease

in health conscious individuals. Heart.

1997;78(5):450-455. FREE FULL TEXT

 

14. Snowdon DA, Phillips RL, Fraser GE. Meat

consumption and fatal ischemic heart disease.

Prev Med. 1984;13(5):490-500. FULL TEXT | ISI

| PUBMED

 

15. Kipnis V, Subar AF, Midthune D; et al.

Structure of dietary measurement error: results

of the OPEN biomarker study. Am J Epidemiol.

2003;158(1):14-21. FREE FULL TEXT

 

16. Knize MG, Dolbeare FA, Carroll KL, Moore DH

II, Felton JS. Effect of cooking time and

temperature on the heterocyclic amine content of

fried beef patties. Food Chem Toxicol.

1994;32(7):595-603. FULL TEXT | ISI | PUBMED

 

17. Sinha R, Knize MG, Salmon CP; et al.

Heterocyclic amine content of pork products

cooked by different methods and to varying

degrees of doneness. Food Chem Toxicol.

1998;36(4):289-297. FULL TEXT | ISI | PUBMED

 

18. Sinha R, Rothman N, Salmon CP; et al.

Heterocyclic amine content in beef cooked by

different methods to varying degrees of doneness

and gravy made from meat drippings. Food Chem

Toxicol. 1998;36(4):279-287. FULL TEXT | ISI

| PUBMED

 

19. Skog K, Steineck G, Augustsson K, Jagerstad

M. Effect of cooking temperature on the formation

of heterocyclic amines in fried meat products and

pan residues. Carcinogenesis.

1995;16(4):861-867. FREE FULL TEXT

 

20. Sugimura T, Wakabayashi K, Ohgaki H, Takayama

S, Nagao M, Esumi H. Heterocyclic amines produced

in cooked food: unavoidable xenobiotics. Princess

Takamatsu Symp. 1990;21:279-288. PUBMED

 

21. Kazerouni N, Sinha R, Hsu CH, Greenberg A,

Rothman N. Analysis of 200 food items for

benzo[a]pyrene and estimation of its intake in an

epidemiologic study. Food Chem Toxicol.

2001;39(5):423-436. FULL TEXT | ISI | PUBMED

 

22. Hughes R, Cross AJ, Pollock JR, Bingham S.

Dose-dependent effect of dietary meat on

endogenous colonic N-nitrosation. Carcinogenesis.

2001;22(1):199-202. FREE FULL TEXT

 

23. Cross AJ, Sinha R. Meat-related

mutagens/carcinogens in the etiology of

colorectal cancer. Environ Mol Mutagen.

2004;44(1):44-55. FULL TEXT | ISI | PUBMED

 

24. Kato I, Dnistrian AM, Schwartz M; et al. Iron

intake, body iron stores and colorectal cancer

risk in women: a nested case-control study. Int J

Cancer. 1999;80(5):693-698. FULL TEXT | ISI |

PUBMED

 

25. Kabat GC, Miller AB, Jain M, Rohan TE. A

cohort study of dietary iron and heme iron intake

and risk of colorectal cancer in women. Br J

Cancer. 2007;97(1):118-122. FULL TEXT | ISI |

PUBMED

 

26. Lee DH, Jacobs DR Jr, Folsom AR. A

hypothesis: interaction between supplemental iron

intake and fermentation affecting the risk of

colon cancer: the Iowa Women's Health Study. Nutr

Cancer. 2004;48(1):1-5. FULL TEXT | ISI |

PUBMED

 

27. Wurzelmann JI, Silver A, Schreinemachers DM,

Sandler RS, Everson RB. Iron intake and the risk

of colorectal cancer. Cancer Epidemiol Biomarkers

Prev. 1996;5(7):503-507. ABSTRACT

 

28. Bingham SA, Luben R, Welch A, Wareham N, Khaw

KT, Day N. Are imprecise methods obscuring a

relation between fat and breast cancer? Lancet.

2003;362(9379):212-214. FULL TEXT | ISI |

PUBMED

 

29. Thiébaut AC, Kipnis V, Chang SC; et al.

Dietary fat and postmenopausal invasive breast

cancer in the National Institutes of Health-AARP

Diet and Health Study cohort. J Natl Cancer Inst.

2007;99(6):451-462. FREE FULL TEXT

 

30. Midthune D, Kipnis V, Freedman LS, Carroll

RJ. Binary regression in truncated samples, with

application to comparing dietary instruments in a

large prospective study. Biometrics.

2008;64(1):289-298. FULL TEXT | ISI | PUBMED

 

31. The World Cancer Research Fund/American

Institute for Cancer Research. Food, Nutrition,

Physical Activity, and the Prevention of Cancer:

A Global Perspective. Washington, DC: AICR; 2007.

 

32. Steffen LM, Kroenke CH, Yu X; et al.

Associations of plant food, dairy product, and

meat intakes with 15-y incidence of elevated

blood pressure in young black and white adults:

the Coronary Artery Risk Development in Young

Adults (CARDIA) Study. Am J Clin Nutr.

2005;82(6):1169-1177. FREE FULL TEXT

 

33. Gascon A, Jacques H, Moorjani S, Deshaies Y,

Brun LD, Julien P. Plasma lipoprotein profile and

lipolytic activities in response to the

substitution of lean white fish for other animal

protein sources in premenopausal women. Am J Clin

Nutr. 1996;63(3):315-321. FREE FULL TEXT

 

34. Wolmarans P, Benade AJ, Kotze TJ, Daubitzer

AK, Marais MP, Laubscher R. Plasma lipoprotein

response to substituting fish for red meat in the

diet. Am J Clin Nutr. 1991;53(5):1171-1176. FREE

FULL TEXT

 

35. Jacques H, Gascon A, Bergeron N; et al. Role

of dietary fish protein in the regulation of

plasma lipids. Can J Cardiol. 1995;11(suppl

G):63G-71G. PUBMED

 

36. Sanders TA, Oakley FR, Miller GJ, Mitropoulos

KA, Crook D, Oliver MF. Influence of n-6 versus

n-3 polyunsaturated fatty acids in diets low in

saturated fatty acids on plasma lipoproteins and

hemostatic factors. Arterioscler Thromb Vasc

Biol. 1997;17(12):3449-3460. FREE FULL TEXT

 

THIS ARTICLE HAS BEEN CITED BY OTHER ARTICLES

 

Reducing Meat Consumption Has Multiple Benefits for the World's Health

Popkin

Arch Intern Med 2009;169:543-545.

FULL TEXT

 

 

 

 

 

 

 

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