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Meat intake and cause-specific mortality: a pooled analysis of Asian
prospective cohort studies
1–3
Jung Eun Lee, Dale F McLerran, Betsy Rolland, Yu Chen, Eric J Grant, Rajesh Vedanthan, Manami Inoue,
Shoichiro Tsugane, Yu-Tang Gao, Ichiro Tsuji, Masako Kakizaki, Habibul Ahsan, Yoon-Ok Ahn, Wen-Harn Pan,
Kotaro Ozasa, Keun-Young Yoo, Shizuka Sasazuki, Gong Yang, Takashi Watanabe, Yumi Sugawara, Faruque Parvez,
Dong-Hyun Kim, Shao-Yuan Chuang, Waka Ohishi, Sue K Park, Ziding Feng, Mark Thornquist, Paolo Boffetta, Wei Zheng,
Daehee Kang, John Potter, and Rashmi Sinha
ABSTRACT
Background: Total or red meat intake has been shown to be asso-
ciated with a higher risk of mortality in Western populations, but
little is known of the risks in Asian populations.
Objective: We examined temporal trends in meat consumption and
associations between meat intake and all-cause and cause-specific
mortality in Asia.
Design: We used ecological data from the United Nations to com-
pare country-specific meat consumption. Separately, 8 Asian pro-
spective cohort studies in Bangladesh, China, Japan, Korea, and
Taiwan consisting of 112,310 men and 184,411 women were fol-
lowed for 6.6 to 15.6 y with 24,283 all-cause, 9558 cancer, and 6373
cardiovascular disease (CVD) deaths. We estimated the study-
specific HRs and 95% CIs by using a Cox regression model and
pooled them by using a random-effects model.
Results: Red meat consumption was substantially lower in the Asian
countries than in the United States. Fish and seafood consumption
was higher in Japan and Korea than in the United States. Our pooled
analysis found no association between intake of total meat (red meat,
poultry, and fish/seafood) and risks of all-cause, CVD, or cancer
mortality among men and women; HRs (95% CIs) for all-cause mor-
tality from a comparison of the highest with the lo west quartile were
1.02 (0.91, 1.15) in men and 0.93 (0.86, 1.01) in women.
Conclusions: Ecological data indicate an increase in meat intake in
Asian countries; however, our pooled analysis did not provide ev-
idence of a higher risk of mortality for total meat intake and pro-
vided evidence of an inverse association with red meat, poultry, and
fish/seafood. Red meat intake was inversely associated with CVD
mortality in men and with cancer mortality in women in Asian
countries. Am J Clin Nutr 2013;98:1032–41.
INTRODUCTION
Asia is experiencing marked changes in lifestyle and disease
patterns, similar to those seen in Western countries (1, 2), with
projected increases in the proportions of deaths from cancer,
ischemic heart disease, and cardiovascular disease (CVD)
4
(3).
Therefore, it is important to identify modifiable risk factors,
such as diet, which may be responsible for the rising rates of
chronic disease in Asian populations.
Meat intake varies across regions and countries in Asia, with
relatively low consumption in certain countries compared with
others in the continent (4). Meat intake, specifically red meat, has
been associated with an increased risk of mortality in Western
populations (5, 6), although further studies are warranted in
populations that consume different quantities and types of meat
and have dissimilar confounding factors. Many mechanisms
1
From the Department of Food and Nutrition, Sookmyung Women’s Uni-
versity, Seoul, South Korea (JEL); the Division of Public Health Sciences,
Fred Hutchinson Cancer Research Center, Seattle, WA (DFM, BR, RV, MT,
and JP); the Department of Environmental Medicine, New York University
School of Medicine, New York, NY (YC); the Department of Epidemiology,
Radiation Effects Research Foundation, Hiroshima, Japan (EJG and KO); the
Epidemiology and Prevention Division, Research Center for Cancer Preven-
tion and Screening, National Cancer Center, Tokyo, Japan (MI, ST, and SS);
the Department of Epidemiology, Shanghai Cancer Institute, Shanghai,
China (Y-TG); the Division of Epidemiology, Department of Public Health
and Forensic Medicine, Tohoku University Graduate School of Medicine,
Miyagi, Japan (IT, MK, TW, and YS); the Departments of Health Studies,
Medicine, and Human Genetics, Comprehensive Cancer Center, The Uni-
versity of Chicago, Chicago, IL (HA); the Department of Preventive Med-
icine, Seoul National University College of Medicine, Seoul, South Korea
(Y-OA, K-YY, SKP, and DK); the Division of Preventive Medicine and
Health Services Research, Institute of Population Health Sciences, National
Health Research Institutes, Miaoli, Taiwan (W-HP and S-YC); Institute of
Biomedical Sciences, Academia Sinica, Taipei, Taiwan (W-HP); Graduate
Institute of Epidemiology and Preventive Medicine, College of Public
Health, National Taiwan University, Taipei, Taiwan (W-HP); the Division
of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center,
Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine,
Nashville, TN (GY and WZ); the Division of Epidemiology, Department of
Public Health and Forensic Medicine, Tohoku University Graduate School of
Medicine, Miyagi, Japan (TW and YS); the Department of Environmental
Health Sciences, Mailman School of Public Health, Columbia University,
New York, NY (FP); the Department of Social and Preventive Medicine,
Hallym University College of Medicine, Chuncheon, South Korea (D-HK);
the Department of Clinical Studies, Radiation Effects Research Foundation,
Hiroshima, Japan (WO); the Section of Early Cancer Detection and Bio-
markers, The University of Texas, MD Anderson Cancer Center, Houston,
TX (ZF); The Tisch Cancer Institute and Institute for Translational Epide-
miology, Mount Sinai School of Medicine, New York, NY (PB); the Centre
for Public Health Research, Massey University, Wellington, New Zealand
(JP); and the Division of Cancer Epidemiology and Genetics, National Can-
cer Institute, Bethesda, MD (RS).
Received March 21, 2013. Accepted for publication June 28, 2013.
First published online July 31, 2013; doi: 10.3945/ajcn.113.062638.
1032 Am J Clin Nutr 2013;98:1032–41. Printed in USA. Ó 2013 American Society for Nutrition
supporting a detrimental effect of meat have been proposed in
relation to specific outcomes: an adverse lipid profile and free
radical generation as a result of high intakes of SFA and iron,
mutagens generated by high-temperature cooking (7, 8), and N-
nitroso compounds formed in processed meat and endogenously
from heme iron (9). The different rates of change and economic
development in Asian countries provide a fertile environment
for conducting etiologic research on chronic disease, because it
provides a large range of exposures and a variety of endpoints.
We initiated the Asia Cohort Consortium (ACC) to understand
chronic disease etiology in Asia, where the association between
dietary factors and chronic diseases has not been extensively
studied. In the current study, we 1) compared ecological trends
in meat intake over the past 37 y between Asia and the United
States and 2) assessed whether meat intake was associated with
all-cause, cancer and CVD mortality by using individual, pro-
spective data from a pooled analysis of Asian cohort studies
involving 296,721 men and women.
SUBJECTS AND METHODS
Meat consumption in Asia
We compared temporal trends in meat consumption in Ban-
gladesh, China, Japan, South Korea, and the United States with
the use of the FAO database (10). We compared meat con-
sumption in Asia with that in the United States because of high
meat consumption in the United States and supportive evidence
for high mortality with high meat intake in a large US cohort
study (5, 6). The FAO Statistical Database, the world’s largest
online agricultural database (available at http://faostat.fao.org/,
accessed 1 3 June 2012), details historical and chronologic
population-based production and disappearance data (referred to
as food availability). For livestock production and product
consumption, FA O has compiled relev ant data—including agricul-
tural production, fish production, trade, food supply, food balance
sheets, supply utilization accounts, and population size—sub-
mitted by member countries in the form of replies to FAO
questionnaires (11). The FAO Statistical Database provides data
on per capita consumption of meat, beef, pork, poultry, and fish
and seafood and defines total meat (excluding fish) as the sum of
beef, poultry, pork, mutton, goat, and game. Per capita con-
sumption (kcal/person per year) is the total amount of food in
each commodity available for each individual in the total pop-
ulation during the period 1970–2007, representing the average
amount available for the population as a whole.
Study population
The ACC was described elsewhere (12). For the meat and
mortality analysis, a total of 8 prospective cohort studies from
Bangladesh, mainland China, Japan, Korea, and Taiwan were
included. We excluded participants who did not provide food-
frequency questionnaires (FFQs) (n = 8177) and those for whom
time under study was missing (n = 467). A total of 296,721
(112,310 men and 184,411 women) were included in this
analysis. Each cohort collected cause-specific deaths through
linkage to death registries or active follow-up. The study was
reviewed and approved by the ethics committee for all partici-
pating cohort studies and by the institutional review board of
Fred Hutchinson Cancer Research Center.
Assessment of dietary and nondietary factors
Each study assessed food intake with a validated FFQ con-
sisting of the frequency of intake, further qualified as specified
portions (weights, numbers, or servings) or serving sizes (eg,
a half bowl, one bowl) (13–18). The number of items for red
meat, poultry, and fish varied from 6 to 17 across studies (see
Supplemental Table 1 under “Supplemental data” in the online
issue). We quantified food-group intake in grams per day or
servings per day using the reported frequency of intake of each
relevant food item and study-specific portion sizes. Data on age,
education, alcohol intake, tobacco smoking, and residence were
collected through self-administered questionnaire or interview.
Height and weight were self-reported or directly measured. BMI
was calculated by dividing weight (in kg) by the square of height
(in m).
Statistical analysis
Using individual-level data, we calculated study-specific HRs
and 95% CIs using a Cox proportional hazards model; age was
used as the time metric. Person-years of follow-up were estimated
from the baseline entry date until the date of death, loss to follow-
up (if applicable), or end of follow-up, whichever came first.
Baseline age (,40, 40–49, 50–59, 60–69, 70–79, and $80 y),
educational level (less than secondary, secondary, and more than
secondary school graduate), alcohol intake (continuous), urban
or rural residence, total energy intake (continuous), fruit and
vegetable intake (continuous), BMI (in kg/m
2
; ,18.5, 18.5–
1 9.9 , 20.0–24.9, 25.0–29.9, and $30.0), and tobacco smoking
(never smoked, former smoker, current with ,20 pack-years of
smoking, and current with $20 pack-years of smoking) were
adjusted for as potential confounding factors in the multivariate
analyses. Outcomes of interest included all-cause mortality and
cancer and CVD mortality. Because the number of food items
2
Supported by the National Cancer Institute, NIH (intramural funding),
and by the Fred Hutchinson Cancer Research Center. The cohorts partici-
pating in the pooled analysis were supported by the following grants: Japan
Public Health Center–Based Study 1 and Japan Public Health Center–Based
Study 2: National Cancer Center Research and Development Fund; Grant-in-
Aid for Cancer Research; Grant for Health Services and Grant for Compre-
hensive Research on Cardiovascular and Life-Style Related Diseases from
the Ministry of Health, Labour and Welfare, Japan; and Grant for the Sci-
entific Research from the Ministry of Education, Culture, Sports, Science
and Technology, Japan. The Radiation Effects Research Foundation, Hirosh-
ima and Nagasaki, Japan, is a private, nonprofit foundation funded by the
Japanese Ministry of Health, Labour and Welfare and the US Department of
Energy. This publication was supported by RERF Research Protocol RP-A3-
11; Shanghai Women’s Health Study: NIH (R37CA70867); CardioVascular
Disease risk FACtor Two-township Study: Department of Health, Taiwan
(DOH80-27, DOH81-021, DOH8202-1027, DOH83-TD-015, and DOH84-
TD-006); The Korea Multi-Center Cancer Cohort: Ministry of Education,
Science and Technology, Korea (2009-0087452); National Research Foun-
dation of Korea (2009-0087452); Health Effects of Arsenic Longitudinal
Study: NIH (P42ES010349, R01CA102484, and R01CA107431); Seoul
Male Cohort: National Research Grant for Basic Medical Sciences, Korea
and National Research Foundation of Korea, 1992-2011.
3
Address correspondence to R Sinha, NIH, National Cancer Institute, Di-
vision of Cancer Epidemiology and Genetics, 9609 Medical Center Drive,
RM 6E336 MSC 9768, Bethesda, MD 20892. E-mail: sinhar@mail.nih.gov.
4
Abbreviations used: ACC, Asia Cohort Consortium; CVD, cardiovascular
disease; FFQ, food-frequency questionnaire.
MEAT INTAKE AND MORTALITY IN ASIA 1033
varied across studies, in the main analysis, we obtained HRs and
95% CIs using study- and sex-specific quartiles of grams per day
of each food group. For males and females separately, cohort-
specific HRs were pooled to compute cross-cohort estimates by
using a random-effects model. The random-effects model also
produced a trend test for pooled HR estimates. Tertiles rather
than quartiles of poultry intake were used to ensure an adequate
number of cases in each category. In supplemental analyses, we
computed pooled cohort HRs from cohort-specific estimates
computed by using uniform cutoffs rather than cohort-specific
cutoffs to construct intake quartiles and tertiles. In other sup-
plemental analyses, we included 2 additional cohort studies that
offered nonquantitative dietary intake data: 1) the Korean Multi-
Center Cancer Cohort Study (19) and 2) the Radiation Effects
Research Foundation in Hiroshima and Nagasaki, the Life Span
Study cohort (20), which had assessed diet by using non-
quantitative FFQs (data on frequency of intake only). We tested
for heterogeneity across studies using a likelihood ratio test that
compared random- and fixed-effect models for pooled cohort
effect estimates. Because socioeconomic status may be related
to meat intake and disease pattern in Asian populations and
because meat intake varies over time, we also examined whether
FIGURE 1. Meat (A–D) and seafood (E) consumption (FAO data) in Bangladesh, China, Japan, South Korea, and the United States. Meat (A) includes
beef, poultry, pork, mutton, goat, and game.
1034 LEE ET AL
the associations varied by educational level. Also, we examined
whether BMI, smoking status, or baseline period modified the
associations. All statistical tests were 2-sided and P values
,0.05 were considered to be statistically significant. We used
SAS version 9.3 (SAS Institute) for the analyses.
RESULTS
Consumption trends using ecologic data
We examined temporal trends in per capita consumption of
meat, beef, pork, poultry, and fish/seafood with the use of the
international FAO database (Figure 1 and Figure 2). We com-
pared meat-consumption patterns between the United States and
Asian populations because there have been numerous meat- and
chronic disease–related studies conducted in the United States
(5, 6, 21–23). Ecological data indicate an increase in meat intake
in Asian countries. Per capita consumption of meat (excluding
fish) in the United States was .2 times that in China, Japan, and
South Korea and .33 times that in Bangladesh in the 1990s and
2000s (Figure 1). In 2007, average meat consumption in the
United States was 122.8 kg/y, whereas consumption in China,
Japan, and South Korea ranged from 46.1 to 55.9 kg/y. Per
capita beef consumption has decreased to some degree in the
past decade in the United States but still remains substantially
higher than that in Asian countries. Beef consumption increased
in China, Japan, and Korea from 1970 to 2007. Although beef
consumption in the United States remains higher, the gap with
Japan or Korea has progressively decreased; in 1970, the dif-
ference was 18-fold; in 1980, it was 10-fold; in 1990, it was 5-
fold; and in 2007, it was 4-fold. Per capita consumption of pork
has continued to rise in China, Japan, and Korea; consumption
in China and Korea has now surpassed consumption in the
United States. Per capita consumption of poultry has been rising
in China, Japan, South Korea, and the United States, but the
difference between the United States and Asian countries re-
mained substantial. Per capita consumption of fish and seafood
in Japan and Korea has remained higher than that in the United
States; consumption in China has risen to a level similar to that
in the United States but that is still substantially lower than that
in Japan and Korea.
When we compared the proportions of per capita consumption
of beef, pork, poultry, and fish/seafood in Bangladesh, China,
Japan, and Korea with those in the United States, using the 2000
FAO database, the proportions of fish/seafood consumption in
Asian countries were higher than those in the United States
(34%–85% compared with 15%), whereas total meat con-
sumption (largely beef and poultry, totaling 64%) in the United
States was higher than that in Asian countries (Figure 2). China
consumed the highest proportion of pork (45%) and Bangladesh
and Japan consumed the highest proportion of fish/seafood (85%
in Bangladesh and 60% in Japan).
Individual consumption and mortality
In our pooled analysis of the ACC data, the mean follow-up
period ranged from 6.6 to 15.6 y. Most studies began enrollment in
the early to mid 1990s (Table 1). Mean intakes of red meat and
poultry in men were 14.2–92.3 and 4.6–22.3 g/d, respectively
(Table 2). In women, mean intakes of red meat ranged from a low
of 9.9 g/d in the Ohsaki National Health Insurance Cohort Study
to 50.9 g/d in the Shanghai Women’s Health Study. Poultry intake
ranged from 2.8 to 15.4 g/d in women. Mean fish and seafood
intake was .45 g/d in men and .36 g/d in women.
Higher total meat intake was not associated with a higher risk
of all-cause, cancer, or CVD mortality in either men or women
(Table 3). In men, HRs (95% CIs) for the comparison of the highest
with the lowest quartile were 1.02 (0.91, 1.15; P-t rend = 0.82) for
FIGURE 2. Percentages of per capita consumption in 2000 in Bangladesh, China, Japan, South Korea, and the United States.
MEAT INTAKE AND MORTALITY IN ASIA 1035
all mortality, 1.11 (0.94, 1.30; P-trend = 0.25) for cancer mortality ,
and 0.91 (0.78, 1.05; P-trend = 0.29) for CVD mortality . In women,
HRs (95% CIs) for the comparison of the highest with the lowest
quartile were 0.93 (0.86, 1.01; P-trend = 0.25) for all mortality, 0.90
(0.78, 1.04; P-trend = 0.27) for cancer mortality , and 1.02 (0.89,
1.18; P-trend = 0.80) for CVD mortality. Red meat intake appeared
TABLE 1
Baseline characteristics of the cohort studies included
1
Enrollment year,
study, and sex
Follow-up
period
2
Baseline
cohort size
Age range
at entry
Total energy
intake
3
No. of
all deaths
No. of
cancer deaths
No. of
CVD deaths
y kcal/d
1990–1992
JPHC1 (males) 14.2 6 3.7 20,595 40–59 2124 (879) 2300 953 600
JPHC1 (females) 14.7 6 3.1 22,443 40–59 1398 (440) 1128 541 284
1992–1995
JPHC2 (males) 11.2 6 3.2 26,721 40–69 1675 (684) 3662 1621 882
JPHC2 (females) 11.7 6 2.6 29,690 40–69 1087 (330) 1805 784 478
1990
Miyagi (males) 12.6 6 2.7 21,536 40–64 1885 (886) 2335 838 424
Miyagi (females) 12.9 6 2.3 23,430 40–64 1307 (438) 1152 421 202
1995
Ohsaki (males) 9.8 6 3.8 23,462 40–80 1757 (829) 4605 1649 1305
Ohsaki (females) 10.0 6 3.8 25,443 40–80 1266 (461) 2606 769 919
2000–2002
HEALS (males) 6.6 6 1.1 4884 20–75 2806 (967) 284 45 130
HEALS (females) 6.6 6 0.8 6512 17–61 2431 (850) 107 14 41
1992–1993
Seoul (males) 14.7 6 1.7 13,600 25–82 2397 (497) 808 424 145
1996–2000
SWHS (females) 8.6 6 1.2 74,933 40–71 1634 (496) 2908 1346 804
1990–1992
CVDFACTS (males) 14.9 6 3.6 1512 18–92 2325 (943) 332 80 93
CVDFACTS (females) 15.6 6 2.7 1960 18–87 1716 (667) 251 73 66
Total 24,283 9558 6373
1
CVD, cardiovascular disease; CVDFACTS, Cardiovascular Diseases Risk Factor Two-Township Study; HEALS, Health Effects of Arsenic Longitudinal
Study; JPHC, Japan Public Health Center-Based Prospective Study; Miyagi, Miyagi Cohort Study; Ohsaki, Ohsaki National Health Insurance Cohort Study;
Seoul, Seoul Male Cohort Study; SWHS, Shanghai Women’s Health Study.
2
All values are means 6 SDs.
3
All values are medians; IQRs in parentheses.
TABLE 2
Meat intake and number of food items in the cohort studies included
1
Study and sex Red meat
2
Number of
food items Poultry
2
No. of
food items
Fish and
seafood
2
No. of
food items
g/d g/d g/d
JPHC1 (males) 33.8 6 19.8 4 12.7 6 9.0 1 52.8 6 34.3 4
JPHC1 (females) 26.9 6 17.0 11.3 6 7.6 45.3 6 29.7
JPHC2 (males) 17.8 6 11.8 4 8.5 6 8.1 1 58.1 6 38.3 6
JPHC2 (females) 15.1 6 10.2 7.1 6 6.6 45.1 6 28.8
Miyagi (males) 14.7 6 12.0 4 7.9 6 8.3 1 58.7 6 35.3 3
Miyagi (females) 11.1 6 9.1 6.5 6 6.2 52.5 6 30.1
Ohsaki (males) 14.2 6 12.0 4 8.7 6 8.4 1 62.8 6 35.7 3
Ohsaki (females) 9.9 6 8.7 6.9 6 6.3 55.7 6 30.6
HEALS (males) 19.1 6 33.0 1 4.6 6 14.0 1 60.3 6 42.0 4
HEALS (females) 12.2 6 19.8 2.8 6 9.7 51.2 6 38.1
Seoul (males) 92.3 6 109.1 7 4.9 6 9.0 1 50.6 6 58.8 9
SWHS (females) 50.9 6 36.7 9 15.3 6 17.8 2 38.0 6 36.8 5
CVDFACTS (males) 67.1 6 67.0 8 22.3 6 34.9 2 45.2 6 53.7 3
CVDFACTS (females) 45.0 6 39.7 15.4 6 21.4 36.6 6 37.2
Total
1
CVDFACTS, Cardiovascular Diseases Risk Factor Two-Township Study; HEALS, Health Effects of Arsenic Longitudinal Study; JPHC, Japan Public
Health Center-Based Prospective Study; Miyagi, Miyagi Cohort Study; Ohsaki, Ohsaki National Health Insurance Cohort Study; Seoul, Seoul Male Cohort
Study; SWHS, Shanghai Women’s Health Study.
2
All values are means 6 SDs.
1036 LEE ET AL
to be related to all-cause mortality in men and women with the
lo west risk in the third quartile. A significant inverse trend with red
meat intake was observed for CVD mortality in men (P-trend =
0.04) and cancer mortality in women (P-trend , 0.01). An inv erse
association with poultry intake was observed for risk of all-cause
mortality in men (P-trend = 0.02) and women (P-tren d = 0.03) and
for risk of cancer mortality in women (P-trend , 0.01). Fish/sea-
food intake was inv ersely associated with risks of all-cause and
CVD mortality in women (P-trend = 0.05 and 0.04, respectively).
In further analyses, we included 2 more cohort studies (Korean
Multi-Center Cancer Cohort Study and Radiation Effects Re-
search Foundation), which assessed diet using nonquantitative
TABLE 3
HRs and 95% CIs for all-cause, cancer, and CVD mortality by meat intake
1
HR (95% CI)
All-cause mortality Cancer mortality CVD mortality
Men
No. of deaths 14,326 5610 3579
Total meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.95 (0.89, 1.01) 0.99 (0.91, 1.08) 0.87 (0.75, 1.00)
Q3 0.93 (0.85, 1.03)* 1.01 (0.91, 1.13) 0.91 (0.79, 1.04)
Q4 1.02 (0.91, 1.15)
y
1.11 (0.94, 1.30)
y
0.91 (0.78, 1.05)
P-trend 0.82 0.25 0.29
Red meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.94 (0.88, 1.00) 0.95 (0.85, 1.05) 0.89 (0.79, 0.99)
Q3 0.86 (0.80, 0.93) 0.87 (0.78, 0.96) 0.87 (0.79, 0.97)
Q4 0.93 (0.84, 1.02)
y
0.90 (0.77, 1.05)* 0.87 (0.78, 0.98)
P-trend 0.06 0.09 0.04
Poultry
T1 1.00 (ref) 1.00 (ref) 1.00 (ref)
T2 0.88 (0.83, 0.93) 0.93 (0.84, 1.02) 0.82 (0.66, 1.02)*
T3 0.89 (0.81, 0.98) 0.91 (0.80, 1.04) 0.82 (0.64, 1.06)*
P-trend 0.02 0.17 0.14
Fish
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.98 (0.89, 1.08)* 1.02 (0.90, 1.15) 0.99 (0.82, 1.20)*
Q3 0.98 (0.89, 1.08)* 1.04 (0.96, 1.13) 0.96 (0.79, 1.15)*
Q4 1.05 (0.95, 1.16)
y
1.14 (1.04, 1.26) 0.95 (0.80, 1.13)
P-trend 0.43 0.02 0.50
Women
No. of deaths 9957 3948 2794
Total meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.88 (0.82, 0.94) 0.92 (0.78, 1.08) 0.88 (0.78, 0.99)
Q3 0.91 (0.82, 1.02) 0.96 (0.79, 1.17)* 0.88 (0.74, 1.04)
Q4 0.93 (0.86, 1.01) 0.90 (0.78, 1.04) 1.02 (0.89, 1.18)
P-trend 0.25 0.27 0.80
Red meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.93 (0.87, 0.98) 0.92 (0.82, 1.04) 0.93 (0.82, 1.06)
Q3 0.88 (0.81, 0.95) 0.83 (0.74, 0.92) 0.86 (0.75, 0.99)
Q4 0.93 (0.86, 1.00) 0.85 (0.76, 0.94) 1.03 (0.85, 1.25)
P-trend 0.05 ,0.01 0.99
Poultry
T1 1.00 (ref) 1.00 (ref) 1.00 (ref)
T2 0.91 (0.85, 0.97) 0.91 (0.83, 1.01) 0.97 (0.85, 1.09)
T3 0.93 (0.86, 0.99) 0.88 (0.79, 0.97) 1.05 (0.92, 1.18)
P-trend 0.03 ,0.01 0.49
Fish
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.86 (0.75, 0.98) 0.97 (0.80, 1.17) 0.84 (0.75, 0.94)
Q3 0.89 (0.83, 0.96) 1.01 (0.81, 1.28)
y
0.79 (0.68, 0.91)
Q4 0.91 (0.85, 0.97) 1.00 (0.83, 1.20) 0.88 (0.77, 1.01)
P-trend 0.05 0.92 0.04
1
Values were adjusted for age, BMI, education, smoking habit, rural/urban residence, alcohol intake, fruit and
vegetable intake, and total energy intake. *P value for homogeneity across studies rejected at a , 0.05.
y
P value for
homogeneity across studies rejected at a , 0.01. CVD, cardiovascular disease; Q, quartile; ref, reference; T, tertile.
MEAT INTAKE AND MORTALITY IN ASIA 1037
FFQs. We examined whether there were similar associations be-
tween frequencies of meat intake and all-cause, cancer, and CVD
mortality. Similar to the results in the analysis of grams per day,
we found no statistically significant associations for total meat
intake with frequency of total meat consumption as the main
exposure (data not shown). Furthermore, when we used common
cutoffs rather than cohort-specific cutoffs to construct intake
quartiles, the results were similar for total meat intake (data not
shown). When we examined the associations for intakes of total
meat, red meat, poultry, and fish in individual cohort studies, we
found generally similar patterns with pooled results (see Sup-
plemental Table 2 under “Supplemental data” in the online is-
sue). Because socioeconomic status may have been linked to
meat availability during the study period, we investigated whether
associations varied by educational level (less than secondary,
secondary, and more than secondary graduate) (Table 4). We
found no statistically significant associations for all-cause mor-
tality with total meat intake in any education stratum. For red
meat intake, a lower risk of all-cause mortality was observed at
the second and third quartiles in women with less than secondary
school education. When we stratified BMI into 3 groups (BMI
,20, 20 to ,25, and $25), we found similar associations be-
tween total meat intake and all-cause mortality in both men and
women. A comparison of the highest with the lowest quartile
resulted in HRs (95% CIs) of 1.10 (0.94, 1.28) for men with
aBMI,20, 1.01 (0.88, 1.16) for men with a BMI of 20 to ,25,
and 1.01 (0.82, 1.24) for men with a BMI $25; the respective
values for women were 0.85 (0.70, 1.04) for women with a BMI
,20, 1.00 (0.84, 1.18) for women with a BMI of 20 to ,25, and
0.91 (0.77, 1.06) for women with a BMI $25. When we limited
our analysis to never-smokers, HRs for total meat intake in re-
lation to all-cause mortality in a comparison of the highest with
the lowest quartile were 1.12 (0.97, 1.29) in men and 0.94 (0.87,
1.02) in women. We also found that baseline period (before or
after 1995) did not modify any of the associations between total
meat, red meat, poultry, or fish/seafood and risk of all-cause
mortality (data not shown). When we excluded participants who
died within the first 3 y of follow-up, we found that the results of
total meat, red meat, poultry, or fish/seafood were similar for all-
cause, cancer, and CVD mortality (data not shown).
DISCUSSION
Even with the marked increase in industrialization and urban-
ization in Asian countries, food-availability data from FAO in-
dicated that meat consumption was still substantially higher in
the United States than in any Asian country. The main differences
between meat consumption in the United States and Asia were seen
for beef and poultry . Even though meat consumption has continued
to rise in China, Japan, and South Korea and ev en though the gap
between the United States and Asian countries has narrowed, meat
consumption in Asia has remained lower than that in the United
States into the 21st century. In contrast, fi sh and seafood con-
sumption in Japan and Korea is .2-fold that in the United States.
Our pooled analysis of 8 Asian prospective cohort studies did
not provide evidence of a higher risk of mortality for total meat
intake. For red meat and poultry, inverse associations were ob-
served for mortality in both men and women. We found that fish
intake was inversely associated with risk of mortality in women.
No variation in the associations between mortality and total meat
intake were observed by educational levels or study period.
Overall cancer and CVD mortality has increased in Asian
countries (24–26), and mortality rates from some cancers are
approaching those in Western countries (24, 27). Given the trend
of increasing meat consumption over time in Asia, a westernized
diet heavy in animal products has been invoked as a cause of this
increasing incidence and mortality from cancer and CVD (28).
However, Asian prospective cohort studies (29–33), most of
which were included in our pooled analysis, have not supported
the hypothesis that meat intake is involved in all-cause, cancer,
or CVD mortality, unlike the pattern seen in Europe and North
America (5, 6, 34, 35).
The absence of a positive association between meat intake and
mortality in Asia may be related to several factors. First, Asia has
been experiencing a dramatic change in many other chronic
disease risk factors, including physical activity, adiposity, and
access to medical care. At this stage, it is possible that meat
consumption may not be as large a contributor to risk of death as
socioeconomic status, a sedentary lifestyle (36, 37), or adiposity.
Furthermore, other risk factors such as obesity (12), hypertension
(38), and smoking (39) could largely explain the increasing risks
of cancer or CVD in Asia to date. Second, the null, and even
inverse, association between meat consumption and mortality
observed in our data warrants further study because the dietary
transition is still under way in many parts of Asia. Residual or
unmeasured confounding factors, such as socioeconomic status
related to meat availability, could be important because food
accessibility and availability is related to income levels in the
Asia-Pacific region (40); ie, even though we failed to detect
differences by education, a higher intake of meat at this point in
the epidemiologic transition may be a marker for other protective
factors, including a sufficient intake of energy and access to
medical care. Third, nondifferential measurement error in dietary
assessments could have led to bias toward the null, although all
the FFQs used in each study have been validated with modest
to good correlation with a reference method (13–18). Although
the absence of a positive association can be partly explained by
aforementioned reasons, we still cannot rule out the hypothesis
that total meat intake is not related to mortality in Asian pop-
ulations, given the findings we observed in this pooled analysis.
A reduced risk of all-cause and cancer mortality with higher
fish intakes in women could be explained as a result of delayed
progression of disease through inhibition of eicosanoid bio-
synthesis, which leads to a reduction in prostaglandin conversion
from arachidonic acid (41, 42). We found an inverse association
in women only, perhaps because social and cultural differences
between men and women determine health behaviors such as
alcohol intake and tobacco smoking in Asia; therefore, these risk
factors could play a role to a lesser extent in women than in men.
The strengths of our study include the size of the total ACC
cohort and a prospective study design with assessment of long-
term usual dietary intake. In the ACC study, we were able to
include unpublished individual data from some Asian studies,
which provides greater accuracy than meta-analyses. We had
extensive information on potential confounders. Furthermore, we
analyzed the data and adjusted for confounding factors in
a standardized, uniform way by using the original data from each
cohort, which is not allowed in a meta-analysis.
Our study had several limitations. Unmeasured or residual
confounding may still exist, although we adjusted for potential
confounding factors, including alcohol intake, fruit and vegetable
1038 LEE ET AL
intake, education, and smoking status. We did not analyze processed
meat intake because a limited number of processed meats were
included in the FFQs. We could not evaluate whether meat prep-
aration or cooking procedures were associated with risk of mortality
because most of the cohorts did not include such detailed in-
formation in their questionnaires. We were not able to examine
changes in meat intake or timing of meat intake in relation to
mortality because dietary information was not assessed at multiple
TABLE 4
HRs and 95% CIs for all-cause mortality by meat intake, stratified by educational level
1
Education
Low Middle High
Men
No. of deaths 5477 3102 1126
Total meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.98 (0.84, 1.14) 0.97 (0.86, 1.08) 0.97 (0.81, 1.16)
Q3 1.07 (0.93, 1.22) 0.83 (0.68, 1.00) 1.10 (0.88, 1.37)
Q4 1.05 (0.86, 1.30)* 1.07 (0.89, 1.28) 1.10 (0.86, 1.40)
P-trend 0.45 0.91 0.33
Red meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.95 (0.86, 1.04) 0.96 (0.87, 1.07) 1.06 (0.90, 1.26)
Q3 0.91 (0.80, 1.04) 0.83 (0.68, 1.03) 0.87 (0.72, 1.05)
Q4 0.97 (0.85, 1.11) 0.94 (0.78, 1.14)* 0.93 (0.69, 1.26)
P-trend 0.59 0.29 0.38
Poultry
T1 1.00 (ref) 1.00 (ref) 1.00 (ref)
T2 0.88 (0.79, 0.99) 0.89 (0.79, 1.00) 0.77 (0.63, 0.94)
T3 0.94 (0.84, 1.04) 0.97 (0.86, 1.10) 0.89 (0.74, 1.08)
P-trend 0.22 0.64 0.24
Fish
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.99 (0.87, 1.13) 0.98 (0.82, 1.17) 1.14 (0.86, 1.50)
Q3 1.02 (0.89, 1.16) 0.97 (0.82, 1.16) 1.14 (0.82, 1.60)*
Q4 1.11 (0.97, 1.28) 1.01 (0.81, 1.26) 1.21 (0.89, 1.64)
P-trend 0.19 0.95 0.17
Women
No. of deaths 4663 1928 985
Total meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.89 (0.80, 0.98) 0.84 (0.71, 1.00) 1.03 (0.84, 1.26)
Q3 0.97 (0.85, 1.11) 0.86 (0.71, 1.04) 1.11 (0.90, 1.38)
Q4 0.98 (0.88, 1.10) 0.88 (0.73, 1.06) 1.09 (0.88, 1.37)
P-trend 0.85 0.26 0.36
Red meat
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.89 (0.81, 0.97) 0.88 (0.76, 1.02) 1.13 (0.92, 1.37)
Q3 0.84 (0.76, 0.93) 0.87 (0.73, 1.03) 1.07 (0.87, 1.31)
Q4 0.95 (0.84, 1.07) 0.84 (0.69, 1.01) 1.11 (0.90, 1.38)
P-trend 0.29 0.09 0.44
Poultry
T1 1.00 (ref) 1.00 (ref) 1.00 (ref)
T2 0.92 (0.84, 1.01) 0.82 (0.70, 0.96) 0.97 (0.79, 1.21)
T3 0.94 (0.86, 1.04) 0.88 (0.73, 1.08) 1.06 (0.87, 1.30)
P-trend 0.26 0.22 0.55
Fish
Q1 1.00 (ref) 1.00 (ref) 1.00 (ref)
Q2 0.90 (0.82, 0.98) 0.81 (0.65, 1.01) 1.06 (0.87, 1.30)
Q3 0.89 (0.70, 1.12)* 0.84 (0.71, 1.00) 1.07 (0.88, 1.31)
Q4 0.98 (0.88, 1.08) 0.89 (0.70, 1.12) 0.96 (0.77, 1.19)
P-trend 0.68 0.35 0.98
1
Values were adjusted for age, BMI, smoking habit, rural/urban residence, alcohol intake, fruit and vegetable intake,
and total energy intake. Educational levels were categorized into: less than secondary; secondary; and more than secondary
school. Japan Public Health Center-Based Prospective Study 2 and Health Effects of Arsenic Longitudinal Study were
excluded from these analyses because educational level was not available. *P value for homogeneity across studies rejected
at a , 0.05. Q, quartile; ref, reference; T, tertile.
MEAT INTAKE AND MORTALITY IN ASIA 1039
times during the study period of each cohort. Heterogeneity in
intake was observed across studies; however, we found that
study-specific results in general did not show an increased risk of
mortality with higher total meat intake. We could not investigate
the role of meat intake with specific types of CVD and cancer
outcomes because we did not have the relevant information from
the different cohorts. However, our finding warrants subsequent
studies to explore the role of diet in the development of specific
CVD or cancer outcomes in this ACC study.
In conclusion, our pooled analysis of prospective cohort
studies showed that higher total and red meat consumption was
not associated with an increased risk of cancer or CVD mortality.
Fish and seafood intake was inversely associated with mortality
in women. Additional dietary studies among Asian populations
are needed to elucidate outstanding questions: 1) Is meat intake
associated with an increased risk of cancer and CVD mortality
beyond changes in lifestyle and environmental factors?; 2)Do
some, as yet undefined, characteristics of Asian populations
explain the association that we observed with meat intake?; and
3) Is the cumulative exposure to a high intake of meat crucial to
disease etiology?
The authors’ responsibilities were as follows—K-YY, PB, WZ, DK, JP,
and RS: conceived the study; JEL, DFM, and RS: designed the research; JEL
and RS: drafted the manuscript; DFM: analyzed the data; and all authors:
revised the manuscript and approved the final manuscript. None of the au-
thors declared a conflict of interest. The funders had no role in the study
design, data collection and analysis, decision to publish, or preparation of the
manuscript.
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