Skip to main content
PMC home page
PLOS ONE logoLink to PLOS ONE
. 2020 Dec 15;15(12):e0244007. doi: 10.1371/journal.pone.0244007

Association between meat intake and mortality due to all-cause and major causes of death in a Japanese population

Eiko Saito 1,2, Xiaohe Tang 3, Sarah Krull Abe 2, Norie Sawada 2, Junko Ishihara 4, Ribeka Takachi 5, Hiroyasu Iso 6, Taichi Shimazu 2, Taiki Yamaji 2, Motoki Iwasaki 2, Manami Inoue 2,*, Shoichiro Tsugane 2; for the JPHC Study Group
Editor: Marly A Cardoso7
PMCID: PMC7737902  PMID: 33320898

Abstract

Purpose

We examined the association between meat intake and mortality due to all-cause and major causes of death using a population-based cohort study in Japan.

Methods

87,507 Japanese aged between 45 and 74 years old at 5-year follow-up study were followed for 14.0 years on average. Associations between meat intake and mortality risk were assessed using a Cox proportional hazards model.

Results

A heavy intake of total meat was associated with a higher risk of all-cause mortality relative to the lowest quartile intake in men (Q4: HR,1.18; 95%CIs, 1.06–1.31). A higher intake of total meat was associated with a lower risk of stroke mortality in women (Q2: HR, 0.70; 95%CIs, 0.51–0.94, Q3: HR, 0.68; 95%CIs, 0.50–0.95, Q4: HR, 0.66; 95%CIs, 0.44–0.99). A heavy intake of red meat was also associated with all-cause mortality (Q4: HR, 1.13; 95%CIs, 1.02–1.26) and heart disease mortality (Q4: HR, 1.51; 95%CIs, 1.11–2.06) in men but not in women. Heavy intake of chicken was inversely associated with cancer mortality in men.

Conclusions

Heavy intakes of total and red meat were associated with an increase in all-cause and heart disease mortality in men, while total meat intake was associated with a lower risk of stroke mortality in women.

Introduction

Meat is a major source of protein and fat in the diet of many countries around the world [1]. Total meat intake is generally reported to be considerably higher in Western countries than in Asia. For instance, a study using the Food and Agriculture Organization (FAO) database showed that per capita consumption of total meat in the United States was approximately three times higher than that in Japan, China and South Korea since the 1990s [2]. Indeed, mean consumption of meat in the United States in 2007 was 122.8 kg per year versus 46.1 to 55.9 kg in these three countries [2].

In Japan, westernization of the diet has seen a near-doubling of meat consumption between 1970 and 2006 [2]. Increased intake of animal fat and/or protein has contributed to reducing stroke among Japanese since the 1960s [3]. However, detrimental effects of meat consumption have also been reported, albeit primarily from Western populations. Epidemiological studies have reported that excessive intake of meat, especially red meat and processed meat, is associated with increased risk of morbidity, including heart disease [4], cardiovascular disease [5], diabetes [6, 7] and certain types of cancer [8, 9]. Elucidating the association of meat intake with overall mortality will aid in assessing the differential impact of meat intake on health among Asians. Current reporting of summary estimates of the link between meat consumption and mortality has primarily been obtained from Western populations [10–13], where meat intake is considerably higher than that in Asian populations. Evidence from Japan is scarce: only a few studies have reported the association of meat intake on mortality [2, 3, 14, 15] and the results are in any case disconcordant. A recent study in 2019 published from the same Japanese cohort reported associations of protein intake with mortality [16]; however, the study primarily assessed the effect of animal and plant-based protein intake on mortality, and did not provide a comprehensive breakdown of item-specific associations.

Here, we aimed to investigate the association between meat intake and all-cause and major causes of death, including cancer, heart disease and cerebrovascular disease in Japan using comprehensive, item-specific information obtained from a large-scale, prospective cohort study.

Methods

Study population

The baseline study for Cohort I started in 1990 and that for Cohort II in 1993, covering a total of 140,420 participants (68,722 men and 71,698 women) in 11 public health center areas. The study enrolled participants aged 40 to 59 years in Cohort I and 40 to 69 years in Cohort II. Details of the Japan Public Health Center-based Prospective Study have been described elsewhere [17, 18]. The study was approved by the Institutional Review Boards of the National Cancer Center (approval number: 2001–021) and The University of Tokyo (approval number: 10508). Participants in the current study were subjects in the JPHC study who were enrolled at age 45–74 years and who responded to a self-administered 5-year follow-up questionnaire, which included comprehensive information on dietary intake and lifestyle-related factors, between 1995 and 1999. This follow-up survey was used as the starting point in the present study. After exclusion of participants who had died, migrated outside of Japan, or were lost to follow-up before the start of the 5-year follow-up survey, the remaining 125,363 subjects were eligible for participation. Of these, 99,629 subjects returned the completed questionnaire (response rate = 79%). Participants were further excluded if they reported a past history of heart disease, cancer or stroke at the time of the baseline or 5-year follow-up survey (n = 6,588), and those with missing data on variables including intakes of meat and total energy or who reported extreme caloric intake (upper and lower 2.5%) (n = 5,534). The final analytic cohort included 87,507 participants (40,072 men and 47,435 women) (S1 Fig).

Follow-up

Participants were followed from the date of the 5-year follow-up survey to the date of death or to the end date of follow-up (December 31, 2011) except for Katsushika area, for which the follow-up was terminated on December 31, 2009. Subjects who died or moved to other areas were followed through the residential registry. Cause of death was ascertained by death certificates with permission of the Ministry of Health, Labour and Welfare [18]. Causes of death were classified using International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) [19], namely cancer (C00-C97), heart disease (I20-I52), cerebrovascular disease (I60-I69), colorectal cancer (C18-C20) and all-cause mortality. We also included mortality from ischemic heart disease (I20-I25) and intracerebral hemorrhage (I61) in our sub-analysis.

Assessment of exposures

Dietary information was collected through a validated self-administered food frequency questionnaire (FFQ) which enquires about the average frequency and portion size of 138 foods and beverages consumed in the past year [20, 21]. Red meat items included three beef dishes (steak, grilled beef and stewed beef), six pork dishes (stir-fried pork, deep-fired pork, stewed pork in western style, stewed pork in Japanese style, pork in soup, and pork liver), four processed meat products (ham, sausage or Wiener sausage, bacon and luncheon meat) and chicken liver. Chicken items included two chicken dishes (grilled chicken and deep-fried chicken). For each food item, nine response categories were provided to report consumption frequency, ranging from rarely (<1 time/month) to more than 7 times a day. The standard portion sizes were enquired about for each food item in three choices: small (less than half of the standard portion), medium (standard portion), and large (more than 1.5 times the standard portion). Participants were categorized by quartiles of total meat, red meat, beef, pork, processed meat and chicken consumption for men and women separately. The validity of the FFQ for the assessment of meat intake has been previously reported as fair to moderate [20, 21]. Spearman’s correlation coefficients comparing energy-adjusted meat intake derived from the FFQ with one derived from 28-day (or 14-day) dietary records were 0.50 and 0.45 for men and women in Cohort I [20], and 0.48 and 0.44 for men and women in Cohort II [21], respectively. As for the reproducibility of the FFQ, correlation coefficients comparing the two FFQ values administered 1 year apart were 0.52 for Cohort I (men and women) [22] and 0.52 for men and 0.41 for women in Cohort II [20]. Spearman’s correlation coefficients comparing the energy-adjusted intake of specific meats for men derived from the FFQ and that derived from 28-day (or 14-day) dietary records for men were as follows: beef, 0.43; pork, 0.42; processed meat, 0.45; and chicken, 0.20 [23].

Statistical analysis

Person-years for each participant were calculated from the date of the 5-year follow-up survey until the date of death or the date of censoring (December 31, 2011), whichever occurred first. Cox proportional hazards regression models were used to estimate the Hazard Ratios (HRs) and 95% confidence intervals (CIs) between quartiles of meat intake and risk of all-cause and cause-specific mortality, with the lowest quartile category being the reference, and by modeling the risk factors separately for men and women. The model was adjusted for age (years, continuous); public health center area; cigarette smoking (never, past, current); alcohol consumption (none; drinker: <150, 150–299, 300+ grams of ethanol per week); body mass index (BMI) (<25, 25–27, 28-<30, 30+,); metabolic equivalent task-hours [24] per day (in quartiles); and history of diabetes or hypertension (yes, no). Missing values for each of these covariates were grouped into one and included in the analysis. We also adjusted the model for consumption of the following food items (in grams/day): fruit, vegetables, fish, dairy products, egg, sodium in addition to total fat and total energy intake. All food intakes were energy-adjusted for men and women separately using the residual method. Tests for linear trend were performed by assigning scores for each intake category for each type of meat intake, starting from one for the lowest consumption status of meat to four for the highest as a continuous variable. We repeated the same analysis after excluding deaths that occurred within 5 years after the 5-year follow-up survey to avoid potential bias from subclinical illnesses. Additionally, sub-group analyses by age groups at 5-year follow-up (45–54 years, 55–64 years, 65 years and older) were performed to assess the generational differences in the associations by using the fully-adjusted model. We computed P-interaction values by using likelihood ratio tests to compare Cox proportional hazards models with and without cross-product terms for meat intake (in scores) and age (45–54 years, 55–64 years, and 65 years and older) in the subgroup analyses. Proportional hazards assumptions were tested using Shoenfeld residuals and found to be nonsignificant. Throughout the paper, all p-values are two-sided, and statistical significance was set at smaller than p<0.05 level. All analyses were conducted using Stata SE 14 (StatCorp, College Station, TX).

Results

During 1,225,257 person-years of follow-up (average 14.0 years), there were 9,886 deaths due to all-cause mortality (6,266 for men, 3,620 for women), 4,174 deaths due to cancer (2,695 for men, 1,479 for women), 940 deaths due to cerebrovascular disease (569 for men, 371 for women), and 1,209 deaths due to heart disease (751 for men, 458 for women). Table 1 shows the characteristics of participants according to quartiles of total meat intake by sex. Those who consumed more meat tended to be younger, and consumed less fruits, vegetables and dairy products.

Table 1. Basic characteristics of participants by quartile of energy-adjusted total meat intake in the study population.

Characteristic Quartiles of total meat intake
Men Women
Q1 Q2 Q3 Q4 P-value1 Q1 Q2 Q3 Q4 P-value1
Total participants (n = 87,507) 10,018 10,018 10,018 10,018 11,859 11,859 11,859 11,858
Age (years), mean ±SE2 58.5±0.1 57.3±0.1 56.8±0.1 57.0±0.1 <0.001 59.0±0.1 57.7±0.1 57.2±0.1 57.3±0.1 <0.001
Total meat intake (g/d),3 mean ±SE 17.5±0.1 38.4±0.1 58.7±0.1 106.4±0.4 <0.001 16.8±0.1 38.1±0.05 58.1±0.1 104.2±0.3 <0.001
Red meat intake (g/d), mean ±SE 14.3±0.1 31.9±0.1 49.8±0.1 92.9±0.4 <0.001 13.6±0.1 31.5±0.1 48.7±0.1 90.3±0.3 <0.001
Beef intake (g/d), mean ±SE 5.5±0.1 12.7±0.1 20.7±0.1 38.2±0.3 <0.001 3.1±0.04 7.9±0.1 12.6±0.1 23.1±0.2 <0.001
Pork intake (g/d), mean ±SE 7.3±0.1 16.2±0.1 25.4±0.1 50.4±0.3 <0.001 8.0±0.1 18.2±0.1 28.4±0.1 56.7±0.3 <0.001
Processed meat intake (g/d), mean ±SE 1.3±0.02 2.9±0.03 4.5±0.05 8.4±0.1 <0.001 2.1±0.03 4.6±0.04 6.9±0.1 11.7±0.1 <0.001
Chicken intake (g/d), mean ±SE 2.8±0.03 5.7±0.04 8.1±0.1 13.4±0.1 <0.001 3.2±0.03 6.6±0.05 9.5±0.1 15.1±0.1 <0.001
Current smoker (%) 43.9 45.9 46.0 42.4 <0.001 5.3 4.9 5.2 6.1 <0.001
Alcohol intake per week (g), mean ±SE 263.4±3.1 224.7±2.6 191.1±2.3 133.3±1.9 <0.001 18.0±0.8 16.3±0.6 13.6±0.5 10.7±0.4 <0.001
Body mass index (kg/m^2), mean ±SE 23.4±0.03 23.5±0.03 23.6±0.03 23.8±0.03 <0.001 23.4±0.03 23.4±0.03 23.4±0.03 23.7±0.03 <0.001
Physical activity (MET-h/d), mean ±SE 33.2±0.1 33.1±0.1 32.8±0.1 32.2±0.1 0.070 32.0±0.05 32.2±0.05 32.1±0.05 31.6±0.05 0.773
History of hypertension (%) 24.4 22.5 21.4 21.0 <0.001 24.5 21.5 20.6 21.8 <0.001
History of diabetes (%) 8.8 8.3 8.3 8.1 <0.001 4.4 3.9 3.8 4.0 <0.001
Total energy (kcal /d), mean ±SE 2268.2±6.6 2248.1±6.1 2169.2±6.1 2002.1±6.1 <0.001 1930.1±5.5 1914.1±4.9 1868.2±4.9 1741.3±5.0 <0.001
Other dietary intake3
Vegetables (g/d), mean ±SE 127.5±1.0 126.7±0.8 124.3±0.8 124.4±0.8 0.010 242.5±1.4 228.8±1.1 216.0±1.0 201.3±1.0 <0.001
Fruits (g/d), mean ±SE 86.5±0.8 86.7±0.7 83.2±0.7 75.4±0.6 <0.001 273.7±1.8 250.5±1.5 226.7±1.4 190.8±1.4 <0.001
Fish (g/d), mean ±SE 66.9±0.5 68.8±0.4 72.2±0.4 72.7±0.4 <0.001 82.7±0.5 83.4±0.4 85.0±0.4 82.7±0.4 <0.001
Egg (g/d), mean ±SE 26.6±0.3 26.5±0.3 27.4±0.3 29.4±0.3 <0.001 25.9±0.3 27.2±0.2 28.2±0.2 29.2±0.2 <0.001
Dairy products (g/d), mean ±SE 76.0±1.0 67.9±0.8 64.3±0.7 60.4±0.7 <0.001 226.7±2.1 209.1±1.7 186.3±1.5 166.2±1.6 <0.001
Sodium (mg/d), mean ±SE 3850.5±14.1 3918.1±12.5 3990.6±12.4 4109.2±12.5 <0.001 4458.3±14.1 4430.5±50.1 4399.8±11.8 4468.8±43.3 <0.001
Total fat (g/d), mean ±SE 33.1±0.1 38.3±0.1 43.3±0.1 54.5±0.1 <0.001 45.5±0.1 50.6±0.1 55.1±0.1 54.5±0.1 <0.001
Open in a new tab

Abbreviations: Q, quartile; MET, metabolic equivalents.

1ANOVA or chi-square test.

2 SE, Standard errors.

3 All mean total intakes of food and nutrients are energy-adjusted.

Tables 2 and 3 show Hazard Ratios (HRs) and 95% confidence intervals (95% CI) for the association between meat consumption and all-cause and cause-specific mortality separately for men and women, and S1 and S2 Tables show the Hazard Ratios and 95% CIs after excluding deaths that occurred within five years after the 5-year follow-up survey. After adjusting for potential confounders, total meat intake was associated with a higher risk of all-cause mortality in men [Q1: reference; Q4: HR, 1.18 (95% CIs, 1.06–1.31)]. Total meat intake was also associated with an elevated risk of heart disease mortality only in men [Q1: reference; Q4: HR, 1.46 (95% CIs, 1.08–1.99)]. In contrast, an intake of total meat was associated with a lower risk of stroke mortality in women [Q2: HR, 0.70 (95% CIs, 0.51–0.94), Q3: HR, 0.68 (95% CIs, 0.50–0.95), Q4: HR, 0.66 (95% CIs, 0.44–0.99)].

Table 2. Adjusted hazard ratios of mortality by meat consumption status (men).

All-cause Cancer Cerebrovascular Disease Heart Disease Colorectal Cancer
Cases HR1,2 95% CI Cases HR1,2 95% CI Cases HR1,2 95% CI Cases HR1,2 95% CI Cases HR1,2 95% CI
All meat
Q1 1,788 1.00 762 1.00 173 1.00 218 1.00 79
Q2 1,501 0.98 (0.91–1.05) 649 0.95 (0.85–1.07) 123 0.89 (0.70–1.15) 184 1.05 (0.85–1.30) 51 0.81 (0.56–1.18)
Q3 1,420 0.99 (0.91–1.07) 640 1.00 (0.88–1.12) 130 1.03 (0.78–1.35) 156 0.99 (0.78–1.26) 38 0.63 (0.40–0.98)
Q4 1,557 1.18 (1.06–1.31) 644 1.06 (0.90–1.25) 143 1.39 (0.97–1.98) 193 1.46 (1.08–1.99) 83 1.51 (0.91–2.49)
p for trend 0.026 0.534 0.127 0.083 0.514
Red meat3
Q1 1,819 1.00 770 1.00 174 1.00 221 1.00 75
Q2 1,470 0.93 (0.87–1.01) 636 0.92 (0.82–1.03) 123 0.85 (0.66–1.10) 180 1.03 (0.83–1.27) 50 0.83 (0.56–1.22)
Q3 1,430 0.98 (0.90–1.06) 647 1.01 (0.89–1.14) 130 1.02 (0.78–1.35) 153 1.00 (0.78–1.28) 46 0.83 (0.54–1.27)
Q4 1,547 1.13 (1.02–1.26) 642 1.07 (0.91–1.25) 142 1.36 (0.95–1.95) 197 1.51 (1.11–2.06) 80 1.52 (0.91–2.54)
p for trend 0.079 0.380 0.137 0.048 0.265
Beef4
Q1 1,883 1.00 747 1.00 165 1.00 264 1.00 74
Q2 1,515 1.03 (0.59–1.79) 666 1.08 (0.96–1.20) 146 1.22 (0.96–1.55) 178 0.85 (0.70–1.04) 59 1.04 (0.72–1.49)
Q3 1,399 0.76 (0.39–1.49) 621 1.07 (0.95–1.20) 135 1.24 (0.96–1.59) 148 0.76 (0.61–0.94) 52 0.91 (0.62–1.36)
Q4 1,469 1.12 (0.50–2.48) 661 1.18 (1.04–1.33) 123 1.12 (0.84–1.50) 161 0.83 (0.66–1.06) 66 1.19 (0.79–1.78)
p for trend 0.562 0.019 0.312 0.051 0.563
Pork5
Q1 1,744 1.00 728 1.00 190 1.00 213 1.00 67
Q2 1,406 0.95 (0.88–1.02) 638 1.01 (0.90–1.13) 112 0.69 (0.54–0.89) 151 0.89 (0.71–1.11) 51 0.99 (0.67–1.47)
Q3 1,475 0.98 (0.91–1.06) 647 1.02 (0.90–1.15) 122 0.74 (0.57–0.97) 185 1.13 (0.90–1.42) 54 1.06 (0.70–1.60)
Q4 1,641 1.11 (1.01–1.22) 682 1.12 (0.97–1.29) 145 0.92 (0.67–1.25) 202 1.26 (0.96–1.65) 79 1.52 (0.95–2.42)
p for trend 0.061 0.192 0.441 0.051 0.103
Processed meat6
Q1 2,016 1.00 850 1.00 206 1.00 247 1.00 85
Q2 1,471 0.91 (0.85–0.98) 628 0.88 (0.79–0.98) 128 0.80 (0.63–1.02) 183 1.02 (0.83–1.25) 55 0.86 (0.60–1.24)
Q3 1,388 0.92 (0.85–0.99) 595 0.89 (0.79–0.99) 128 0.86 (0.67–1.09) 157 0.93 (0.75–1.16) 41 0.63 (0.42–0.95)
Q4 1,391 0.98 (0.91–1.07) 622 1.00 (0.88–1.13) 107 0.85 (0.64–1.13) 164 1.05 (0.83–1.32) 70 1.04 (0.71–1.55)
p for trend 0.488 0.759 0.251 0.935 0.751
Chicken7
Q1 1,793 1.00 769 1.00 160 1.00 230 1.00 79
Q2 1,504 0.97 (0.90–1.04) 678 0.98 (0.88–1.09) 129 0.91 (0.71–1.16) 183 0.96 (0.79–1.18) 60 0.93 (0.65–1.32)
Q3 1,454 0.95 (0.88–1.02) 647 0.96 (0.85–1.07) 141 1.05 (0.82–1.34) 157 0.82 (0.65–1.02) 53 0.82 (0.56–1.19)
Q4 1,515 0.94 (0.87–1.02) 601 0.85 (0.75–0.96) 139 1.01 (0.77–1.31) 181 0.92 (0.73–1.15) 59 0.85 (0.58–1.25)
p for trend 0.128 0.010 0.742 0.245 0.329
Open in a new tab

Abbreviations: HR, hazard ratio; 95% CI, 95% confidence intervals; Q, quartile.

1 Cox proportional hazard models were used.

2 Adjusted for age (years, continuous); public health center area; smoking status (never, former, current), alcohol intake (none, >0-<150 g/w, 150-<300 g/w, 300+g/w), BMI (<25, 25 - <27, 27-<30, 30+), quartile of metabolic equivalent task-hours/d, history of hypertension, history of diabetes, total energy intake, intakes of fruits, vegetables, fish, dairy products, egg, sodium and total fat (continuous).

3 Additionally adjusted for intake of chicken.

4 Additionally adjusted for intakes of pork, processed meat and chicken.

5 Additionally adjusted for intakes of beef, processed meat and chicken.

6 Additionally adjusted for intakes of beef, pork and chicken.

7 Additionally adjusted for intake of red meat.

Table 3. Adjusted hazard ratios of mortality by meat consumption status (women).

All-cause Cancer Cerebrovascular Disease Heart Disease Colorectal Cancer
Cases HR1,2 95% CI Cases HR1,2 95% CI Cases HR1,2 95% CI Cases HR1,2 95% CI Cases HR1,2 95% CI
All meat
Q1 1,013 1.00 404 1.00 123 1.00 128 1.00 47
Q2 850 0.98 (0.89–1.08) 354 1.01 (0.87–1.17) 79 0.70 (0.51–0.94) 106 0.99 (0.75–1.30) 43 1.08 (0.69–1.67)
Q3 834 1.02 (0.91–1.13) 367 1.13 (0.96–1.33) 80 0.68 (0.50–0.95) 97 0.92 (0.69–1.24) 55 1.48 (0.94–2.34)
Q4 923 1.11 (0.97–1.26) 354 1.18 (0.96–1.45) 89 0.66 (0.44–0.99) 127 1.09 (0.77–1.56) 49 1.45 (0.81–2.60)
p for trend 0.164 0.070 0.029 0.829 0.104
Red meat3
Q1 1,018 1.00 405 1.00 120 1.00 130 1.00 47
Q2 834 0.96 (0.87–1.06) 356 1.01 (0.87–1.18) 90 0.84 (0.63–1.13) 100 0.91 (0.69–1.21) 44 1.11 (0.71–1.73)
Q3 852 1.04 (0.94–1.16) 355 1.11 (0.94–1.32) 78 0.68 (0.49–0.96) 105 0.98 (0.73–1.33) 51 1.41 (0.88–2.25)
Q4 916 1.08 (0.95–1.24) 363 1.23 (0.99–1.51) 83 0.62 (0.41–0.95) 123 1.01 (0.70–1.45) 52 1.52 (0.84–2.74)
p for trend 0.174 0.051 0.013 0.921 0.111
Beef4
Q1 1,136 1.00 426 1.00 128 1.00 163 1.00 57
Q2 808 0.93 (0.84–1.02) 348 0.96 (0.82–1.11) 91 0.96 (0.71–1.28) 88 0.76 (0.58–1.01) 46 1.07 (0.71–1.63)
Q3 812 0.96 (0.87–1.06) 356 1.04 (0.89–1.21) 81 0.87 (0.64–1.18) 96 0.89 (0.68–1.18) 52 1.13 (0.75–1.72)
Q4 864 1.00 (0.91–1.11) 349 1.05 (0.89–1.24) 71 0.71 (0.51–1.00) 111 0.95 (0.72–1.25) 39 0.88 (0.55–1.41)
p for trend 0.914 0.415 0.050 0.777 0.748
Pork5
Q1 979 1.00 415 1.00 105 1.00 118 1.00 46
Q2 809 0.93 (0.84–1.03) 339 0.90 (0.77–1.05) 79 0.79 (0.57–1.09) 106 1.03 (0.78–1.37) 46 1.20 (0.77–1.87)
Q3 866 0.99 (0.89–1.10) 348 0.95 (0.81–1.12) 91 0.95 (0.69–1.31) 95 0.85 (0.63–1.15) 46 1.13 (0.71–1.82)
Q4 966 0.97 (0.86–1.10) 377 1.03 (0.85–1.25) 96 0.80 (0.54–1.17) 139 0.96 (0.69–1.34) 56 1.37 (0.80–2.33)
p for trend 0.887 0.766 0.436 0.546 0.326
Processed meat6
Q1 1,145 1.00 451 1.00 115 1.00 149 1.00 62
Q2 825 0.93 (0.84–1.02) 341 0.90 (0.77–1.04) 91 1.13 (0.84–1.52) 96 0.92 (0.70–1.21) 35 0.68 (0.44–1.07)
Q3 814 0.98 (0.89–1.08) 333 0.95 (0.81–1.11) 89 1.18 (0.87–1.61) 106 1.08 (0.82–1.42) 39 0.83 (0.53–1.28)
Q4 836 1.05 (0.95–1.17) 354 1.10 (0.93–1.30) 76 1.01 (0.71–1.42) 107 1.11 (0.83–1.48) 58 1.26 (0.82–1.94)
p for trend 0.327 0.266 0.793 0.355 0.260
Chicken7
Q1 1,008 1.00 409 1.00 97 1.00 132 1.00 50
Q2 863 1.00 (0.91–1.10) 370 0.99 (0.86–1.15) 90 1.05 (0.77–1.42) 107 1.02 (0.78–1.33) 51 1.12 (0.74–1.69)
Q3 834 0.96 (0.87–1.06) 359 0.98 (0.84–1.15) 82 0.95 (0.69–1.31) 91 0.89 (0.67–1.18) 41 0.92 (0.59–1.43)
Q4 915 1.00 (0.90–1.10) 341 0.94 (0.79–1.10) 102 1.04 (0.75–1.44) 128 1.08 (0.81–1.42) 52 1.09 (0.70–1.70)
p for trend 0.789 0.439 0.964 0.819 0.913
Open in a new tab

Abbreviations: HR, hazard ratio; 95% CI, 95% confidence intervals; Q, quartile.

1 Cox proportional hazard models were used.

2 Adjusted for age (years, continuous); public health center area; smoking status (never, former, current), alcohol intake (none, >0-<150 g/w, 150-<300 g/w, 300+g/w), BMI (<25, 25 - <27, 27-<30, 30+), quartile of metabolic equivalent task-hours/d, history of hypertension, total energy intake, history of diabetes, intakes of fruits, vegetables, fish, dairy products, egg, sodium and total fat (continuous).

3 Additionally adjusted for intake of chicken.

4 Additionally adjusted for intakes of pork, processed meat and chicken.

5 Additionally adjusted for intakes of beef, processed meat and chicken.

6 Additionally adjusted for intakes of beef, pork and chicken.

7 Additionally adjusted for intake of red meat.

Our analyses by meat type showed that a higher intake of red meat was also associated with all-cause mortality [Q1: reference; Q4: HR, 1.13 (95% CIs, 1.02–1.26)] and heart disease mortality [Q1: reference; Q4: HR, 1.51 (95% CIs, 1.11–2.06)] in men but not in women. Among different types of red meat, beef consumption was associated with an increased risk of cancer mortality only among men in the highest intake quartile [Q1: reference; Q4: HR, 1.18 (95% CIs, 1.04–1.33)]. Higher pork consumption was also associated with an increased risk of total mortality in men [Q1: reference; Q4: HR, 1.11 (95% CIs, 1.01–1.22)]. In contrast, a moderate intake of processed meat was associated with a lower risk of total mortality [Q1: reference; Q2: HR, 0.91 (95% CIs: 0.85–0.98); Q3: 0.92 (95% CIs, 0.85–0.99)] and of cancer mortality [Q1: reference; Q2: HR, 0.88 (95% CI: 0.79–0.98); Q3: 0.89 (95% CIs, 0.79–0.99)] only among men, albeit that associations seen in Q3 were not significant after exclusion of deaths within 5 years. Higher intake of chicken was associated with a lower risk of cancer mortality in men [Q1: reference; Q4: HR, 0.85 (95% CIs: 0.75–0.96)]. This inverse association between chicken consumption and all-cause mortality was also seen after exclusion of deaths occurring within 5 years [Q1: reference, Q4: HR, 0.83 (95% CIs: 0.72–0.96)]. No significant associations were observed between all types of meat and colorectal cancer mortality. In our sub-analysis, no significant association was seen between meat intake and mortality due to ischemic heart disease or intracerebral hemorrhage (S3 Table). Across other types of cause-specific mortality, the same associations remained after exclusion of deaths that occurred within 5 years after the 5-year follow-up survey in both men and women.

Table 4 shows the results of meat intake and all-cause and cause-specific mortality according to age groups at baseline (45–54 years, 55–64 years, and 65 years and older) in men and women, respectively. In men, a significant increase in all-cause mortality risk was observed in those older than 65 years [Q1: reference; Q4: HR, 1.21 (95% CIs: 1.03–1.41)]. Red meat intake was also associated with a higher risk of all-cause mortality in those aged 55–64 years [Q1: reference; Q4: HR, 1.20 (95% CIs: 1.02–1.42)]. The risk difference was significant by age group (p-interaction with age: total meat, 0.004; red meat, 0.018). In women, a significant increase in all-cause mortality risk was seen in those aged 45–54 years who consumed more total meat [Q1: reference; Q2: HR, 1.32 (95% CIs: 1.01–1.72); Q3: HR, 1.37 (95% CIs: 1.03–1.82)] and more red meat [Q1: reference; Q3: HR, 1.34 (95% CIs: 1.01–1.79)].

Table 4. Adjusted hazard ratios of all-cause mortality according to quartile of meat consumption by age group.

45–54 years 55–64 years 65–79 years
Cases HR1,2 95% CI Cases HR1,2 95% CI Cases HR1,2 95% CI
Men
All meat
Median intake (g/d)3 50.4 45.6 45.4
Q1 270 1.00 766 1.00 752 1.00
Q2 250 0.85 (0.71–1.03) 646 0.99 (0.88–1.10) 605 1.01 (0.90–1.13)
Q3 260 0.96 (0.78–1.17) 555 0.96 (0.84–1.09) 605 1.02 (0.90–1.16)
Q4 249 1.10 (0.84–1.44) 626 1.17 (0.99–1.38) 682 1.21 (1.03–1.41)
p-interaction with age: 0.004
Red meat4
Median intake (g/d)3 42.3 37.9 37.7
Q1 271 1.00 773 1.00 775 1.00
Q2 253 0.87 (0.73–1.05) 626 0.96 (0.86–1.08) 591 0.92 (0.82–1.04)
Q3 259 0.99 (0.80–1.21) 564 0.99 (0.87–1.13) 607 0.95 (0.84–1.08)
Q4 246 1.12 (0.85–1.47) 630 1.20 (1.02–1.42) 671 1.08 (0.92–1.27)
p-interaction with age: 0.018
Chicken5
Median intake (g/d)3 5.8 5.1 5.0
Q1 260 1.00 751 1.00 782 1.00
Q2 294 1.04 (0.88–1.24) 653 0.91 (0.82–1.02) 557 0.99 (0.89–1.11)
Q3 236 0.83 (0.69–1.01) 602 0.88 (0.78–0.99) 616 1.09 (0.97–1.22)
Q4 239 0.90 (0.74–1.11) 587 0.92 (0.82–1.04) 689 0.99 (0.88–1.11)
p-interaction with age: 0.002
Women
All meat
Median intake (g/d)3 50.9 45.2 44.9
Q1 101 1.00 365 1.00 547 1.00
Q2 144 1.32 (1.01–1.72) 311 0.95 (0.81–1.12) 395 0.95 (0.82–1.08)
Q3 154 1.37 (1.03–1.82) 299 1.05 (0.88–1.25) 381 0.92 (0.79–1.06)
Q4 155 1.41 (0.99–2.01) 319 1.19 (0.95–1.49) 449 0.99 (0.83–1.19)
p-interaction with age: 0.093
Red meat4
Median intake (g/d)3 42.0 37.3 37.0
Q1 106 1.00 373 1.00 539 1.00
Q2 139 1.20 (0.91–1.56) 311 0.90 (0.77–1.06) 384 0.96 (0.83–1.10)
Q3 155 1.34 (1.01–1.79) 290 1.00 (0.83–1.20) 407 1.00 (0.86–1.17)
Q4 154 1.37 (0.95–1.96) 320 1.15 (0.92–1.45) 442 0.97 (0.81–1.17)
p-interaction with age: 0.196
Chicken5
Median intake (g/d)3 6.7 5.9 5.6
Q1 116 1.00 338 1.00 554 1.00
Q2 151 1.07 (0.83–1.38) 337 1.05 (0.90–1.23) 375 0.93 (0.81–1.07)
Q3 135 0.88 (0.67–1.15) 322 1.00 (0.85–1.18) 377 0.97 (0.84–1.11)
Q4 152 0.97 (0.73–1.27) 297 0.95 (0.80–1.14) 466 1.03 (0.89–1.18)
p-interaction with age: 0.868
Open in a new tab

Abbreviations: HR, hazard ratio; 95% CI, 95% confidence intervals; Q, quartile.

1 Cox proportional hazard models were used.

2 Adjusted for age (years, continuous); public health center area; smoking status (never, former, current), alcohol intake (none, >0-<150 g/w, 150-<300 g/w, 300+g/w), BMI (<25, 25-<27, 27-<30, 30+), quartile of metabolic equivalent task-hours/d, history of hypertension, history of diabetes, total energy intake, intakes of fruits, vegetables, fish, dairy products, egg, sodium and total fat (continuous).

3 All median intakes of meat are energy-adjusted.

4 Additionally adjusted for intake of chicken.

5 Additionally adjusted for intake of red meat.

Discussion

Our study is one of the few conducted in Asia to assess the association between meat intake and mortality due to all-cause and leading causes using data from a large-scale prospective study. Compared with subjects in the lowest quartile of total meat intake, men in the highest quartile had 18% higher risk of dying from all causes, although the associations were not dose-responsive. Our results agree with a 2014 meta-analysis of nine prospective cohort studies in the US, Europe and China, although total red meat intake in that review increased the risk of all-cause mortality by 29% in the highest intake category [10] compared with 18% in our study. This difference in the magnitude of risk increase is because the analyses in both studies were performed using relative consumption categories rather than absolute consumption amounts. The difference may also be due to the fact that the absolute amount of intake of meat differs between the Japanese and Western populations: mean daily intake of total meat in the US population amounted to 127.9 grams per day between 2003 and 2004 [25] versus 77 grams per day in Japan as of 2003 [26]. Mean intake amount in the US is almost twice that in Japan.

In our study population, the crude mean intake (adjusted for the difference between the FFQ and dietary records [20, 21]) of total meat was 71.9 grams per day.

We also noted generational differences in the association patterns between meat intake and all-cause mortality: notably, women aged 45–54 years had significantly higher risk of total mortality. However, these results could be a chance finding resulting from the multiple statistical tests conducted, given that the highest intake quartile showed no significant associations. In men, in contrast, elevated risk of mortality in the highest intake quartile was seen only in the older groups, and not in the younger age group.

Of note, our study found that intake of total meat was associated with a decreased risk of cerebrovascular disease mortality in women. Meat is a major source of animal protein, and a modest amount of protein intake has been reported to suppress blood pressure and thereby prevent stroke [27]. For instance, previous population-based studies—both derived from Japanese populations—showed that dietary animal protein intake was associated with lower blood pressure levels [28] and also a reduced risk of intraparenchymal hemorrhage [29]. Nevertheless, our results did not show any association between meat intake and intracerebral hemorrhage, a finding which warrants further investigation.

On the contrary, our study reported an elevated risk of heart disease mortality in men but not in women if red meat is taken to the level of the highest intake quartile. One possible mechanism of this association between red meat and heart disease is that meat is a major source of saturated fatty acid, which is reported to increase the risk of myocardial infarction [30]. Several cohort studies have also reported an association between red meat consumption and cardiovascular disease mortality [5, 31], although we did not observe any association between red meat intake and ischemic heart disease mortality in the current study.

Our study also found an elevated risk of cancer mortality in men with the highest intake of beef. Although not specifically referring to beef, the World Cancer Research Fund reported that red meat increases the risk of colorectal cancer [32], and showed suggestive evidence that red meat increases the risk of nasopharynx, lung and pancreatic cancer [32]. The International Agency for Research on Cancer (IARC) also reported that red meat intake is associated with the risk of prostate cancer [33]. Potential pathways can be explained as follows: in the process of cooking red meat, the nitrites convert to N-nitroso compounds, which are known carcinogens that function as a series of initiators and promoters in cancer [34–36]. Heme iron from red meat can catalyze lipid peroxidation, and cause DNA damage in tissues [37, 38]. Other carcinogens, including heterocyclic aromatic amines and polycyclic aromatic hydrocarbons, which are produced by cooking of meat at high temperatures (e.g. pan-frying, grilling or barbecuing), also contribute to carcinogenesis of different sites [33, 39–42]. Despite mounting evidence linking red meat intake and colorectal cancer incidence globally [32] and in Japan [23], no association was seen between meat and colorectal cancer mortality in our study; this may have been due to the fact that the survival rate of colorectal cancer is generally high in Japan, for example with a 5-year relative survival rate of 71.1% for cases diagnosed between 2006–2008 [43, 44].

Contrary to previous studies [5, 45], our analysis showed that processed meat consumption was not associated with elevated risk of mortality due to all-cause, cancer, heart disease and cerebrovascular disease. This null association might be explained by the difference in the intake amount of processed meat in Japan: generally, consumption is lower in Japan than in Western countries. For example, average consumption in the US was estimated to be 23.2 grams per day between 2003 and 2004 [25] versus 12 grams per day in Japan as of 2003 [26]. In our study population, the crude mean intake (adjusted for the difference between the FFQ and dietary records [46]) of processed meat was 7.7 grams per day. Such difference in the absolute amount intake of processed meat may have attenuated the adverse effects.

While a moderate intake of processed meat and pork showed a lower risk of mortality in men, this may have been a chance finding as we did not see any significant trend for different quartile intakes of the corresponding meat type. In contrast, our results showed that higher intake of white meat (i.e. chicken) is associated with a modest decrease in the risk of cancer mortality while red meat intake was held constant. A US study reported that poultry intake was inversely associated with esophagus squamous cell carcinoma, liver cancer and lung cancer, assuming no change in the amount intake of red meat [47]. Given that both studies adjusted for red meat intake, the inverse associations are not due to the effect of substituting red meat with poultry. The mechanism whereby chicken intake alone reduces cancer risk is unclear, and further research is required in this area.

The major strength of this study is the fact that the subjects were recruited from a large sample of the Japanese population. The high response rate and low loss to follow-up may have reduced selection bias. With an average of 14.0 years of follow-up, we consider that sufficient numbers of deaths due to all-cause, overall cancer, heart disease and cerebrovascular disease were captured. Second, we used a 5-year follow-up survey containing the FFQ collecting the necessary information about daily diet with reasonable degree of validity. On the other hand, some limitations warrant mention. Given the information on meat intake was collected only at 5-year follow-up, any change in meat intake during follow-up after the five-year follow-up survey may have produced misclassification.

Conclusion

In this prospective, large-scale cohort study, heavy intake of total and red meat was associated with an increased risk of total mortality in men. In contrast, modest intake of total meat was associated with a lower risk of cerebrocascular disease mortality in women.

Supporting information

S1 Fig. Participant flow chart.

(TIF)

Click here for additional data file. (181.6KB, tif)
S1 Table. Adjusted hazard ratios of mortality by meat consumption status after excluding deaths within 5 years (men).

(DOCX)

Click here for additional data file. (34.2KB, docx)
S2 Table. Adjusted hazard ratios of mortality by meat consumption status after excluding deaths within 5 years (women).

(DOCX)

Click here for additional data file. (34.4KB, docx)
S3 Table. Adjusted hazard ratios of mortality from ischemic heart disease and intracerebral hemorrhage by meat consumption status.

(DOCX)

Click here for additional data file. (32.1KB, docx)

Acknowledgments

ES and XT analyzed the data, drafted the manuscript, reviewed and edited the manuscript, and contributed to discussion; MI and ST conducted, designed, and supervised the study, reviewed and edited the manuscript, and contributed to discussion; SKA, NS, JI, RT, HI, TS, TY and MIw reviewed and edited the manuscript, and contributed to discussion. All authors read and approved the final manuscript. Members of the Japan Public Health Center-based Prospective Study (JPHC Study; principal investigator, S. Tsugane; e-mail, stsugane@ncc.go.jp) Group are: S. Tsugane, N. Sawada, M. Iwasaki, M. Inoue, T. Yamaji, R. Katagiri, T. Imatoh, H. Ihira, S. K. Abe and S. Tanaka, National Cancer Center, Tokyo; T. Sugie, Iwate Prefectural Ninohe Public Health Center, Iwate; T. Minamizono, Akita Prefectural Yokote Public Health Center, Akita; Y. Shirai, Nagano Prefectural Saku Public Health Center, Nagano; H. Sakiyama, Okinawa Prefectural Chubu Public Health Center, Okinawa; T. Yoshimi, Ibaraki Prefectural Chuo Public Health Center, Ibaraki; H. Sonoda, Niigata Prefectural Nagaoka Public Health Center, Niigata; T. Tagami, Kochi Prefectural Chuo-higashi Public Health Center, Kochi; T. Ando, Nagasaki Prefectural Kamigoto Public Health Center, Nagasaki; Y. Miyasato, Okinawa Prefectural Miyako Public Health Center, Okinawa; Y. Kokubo, National Cerebral and Cardiovascular Center, Osaka; K. Yamagishi, University of Tsukuba, Ibaraki; T. Mizoue, National Center for Global Health and Medicine, Tokyo; K. Nakamura, Niigata University, Niigata; and R. Takachi, Nara Women’s University, Nara; J. Ishihara, Azabu University, Kanagawa; H. Iso and T. Kitamura, Osaka University, Osaka; I. Saito, Oita University, Oita; N. Yasuda, Kochi University, Kochi; M. Mimura, Keio University, Tokyo; K. Sakata, Iwate Medical University, Iwate; M. Noda, Saitama Medical University; A. Goto, Yokohama City University, Kanagawa; H. Yatsuya, Fujita Health University, Aichi.

Data Availability

Regarding data accessibility, we cannot publicly share the individual data even after anonymization according to the ethical guidelines in Japan if: a) consent to public sharing of data has not been obtained from each participant, and b) there is a possibility of identifying an individual by combining the information or due to the existence of rare diseases, etc. Therefore, the investigators require the approval of the JPHC Steering Committee (SC) and the Institutional Review Board (IRB). Currently, only citizens of Japan who fulfill the requirements of conducting research projects are eligible to apply for the JPHC data and/or biospecimens. The investigator is required to submit a Project Protocol (Research question, Aim, Background, Design and analytical plan) for review by the JPHC SC. Requests can be made by contacting the JPHC SC directly (jphcadmin@ml.res.ncc.go.jp) or investigators in the JPHC. After approval is obtained from the JPHC SC, the investigator is required to obtain additional approval for the protocol under which the data and/or biospecimens are to be used from the Institutional Review Board of the National Cancer Center. This information on how to submit an application to gain access to JPHC data/or biospecimens is publicly available at http://epi.ncc.go.jp/en/jphc/805/8155.html.

Funding Statement

This study was supported by National Cancer Center Research and Development Fund (23-A-31[toku], 26-A-2 and 29-A-4) (since 2011) and a Grant-in-Aid for Cancer Research from the Ministry of Health, Labour and Welfare of Japan (from 1989 to 2010). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.World Health Organization. Diet, nutrition, and the prevention of chronic diseases: report of a joint WHO/FAO expert consultation: Diamond Pocket Books (P) Ltd; 2003. [Google Scholar]
  • 2.Lee JE, McLerran DF, Rolland B, Chen Y, Grant EJ, Vedanthan R, et al. Meat intake and cause-specific mortality: a pooled analysis of Asian prospective cohort studies. Am J Clin Nutr. 2013;98(4):1032–41. 10.3945/ajcn.113.062638 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Sauvaget C, Nagano J, Allen N, Grant EJ, Beral V. Intake of animal products and stroke mortality in the Hiroshima/Nagasaki Life Span Study. Int J Epidemiol. 2003;32(4):536–43. 10.1093/ije/dyg151 [DOI] [PubMed] [Google Scholar]
  • 4.Micha R, Wallace SK, Mozaffarian D. Red and processed meat consumption and risk of incident coronary heart disease, stroke, and diabetes mellitus: a systematic review and meta-analysis. Circulation. 2010;121(21):2271–83. 10.1161/CIRCULATIONAHA.109.924977 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Sinha R, Cross AJ, Graubard BI, Leitzmann MF, Schatzkin A. Meat intake and mortality: a prospective study of over half a million people. Arch Intern Med. 2009;169(6):562–71. 10.1001/archinternmed.2009.6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Willett WC, et al. Red meat consumption and risk of type 2 diabetes: 3 cohorts of US adults and an updated meta-analysis. Am J Clin Nutr. 2011;94(4):1088–96. 10.3945/ajcn.111.018978 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Aune D, Ursin G, Veierod MB. Meat consumption and the risk of type 2 diabetes: a systematic review and meta-analysis of cohort studies. Diabetologia. 2009;52(11):2277–87. 10.1007/s00125-009-1481-x [DOI] [PubMed] [Google Scholar]
  • 8.Zheng W, Lee SA. Well-done meat intake, heterocyclic amine exposure, and cancer risk. Nutr Cancer. 2009;61(4):437–46. 10.1080/01635580802710741 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Chan DS, Lau R, Aune D, Vieira R, Greenwood DC, Kampman E, et al. Red and processed meat and colorectal cancer incidence: meta-analysis of prospective studies. Plos One. 2011;6(6):e20456 10.1371/journal.pone.0020456 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Larsson SC, Orsini N. Red meat and processed meat consumption and all-cause mortality: a meta-analysis. Am J Epidemiol. 2014;179(3):282–9. 10.1093/aje/kwt261 [DOI] [PubMed] [Google Scholar]
  • 11.Pan A, Sun Q, Bernstein AM, Schulze MB, Manson JE, Stampfer MJ, et al. Red meat consumption and mortality: results from 2 prospective cohort studies. Arch Intern Med. 2012;172(7):555–63. 10.1001/archinternmed.2011.2287 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Abete I, Romaguera D, Vieira AR, Lopez de Munain A, Norat T. Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: a meta-analysis of cohort studies. Br J Nutr. 2014;112(5):762–75. 10.1017/S000711451400124X [DOI] [PubMed] [Google Scholar]
  • 13.Zheng Y, Li Y, Satija A, Pan A, Sotos-Prieto M, Rimm E, et al. Association of changes in red meat consumption with total and cause specific mortality among US women and men: two prospective cohort studies. Bmj. 2019;365:l2110 10.1136/bmj.l2110 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Khan MM, Goto R, Kobayashi K, Suzumura S, Nagata Y, Sonoda T, et al. Dietary habits and cancer mortality among middle aged and older Japanese living in hokkaido, Japan by cancer site and sex. Asian Pac J Cancer Prev. 2004;5(1):58–65. [PubMed] [Google Scholar]
  • 15.Nagao M, Iso H, Yamagishi K, Date C, Tamakoshi A. Meat consumption in relation to mortality from cardiovascular disease among Japanese men and women. Eur J Clin Nutr. 2012;66(6):687–93. 10.1038/ejcn.2012.6 [DOI] [PubMed] [Google Scholar]
  • 16.Budhathoki S, Sawada N, Iwasaki M, Yamaji T, Goto A, Kotemori A, et al. Association of Animal and Plant Protein Intake With All-Cause and Cause-Specific Mortality in a Japanese Cohort. JAMA internal medicine. 2019;179(11):1509–18. 10.1001/jamainternmed.2019.2806 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Tsugane S, Sawada N. The JPHC study: design and some findings on the typical Japanese diet. Jpn J Clin Oncol. 2014;44(9):777–82. 10.1093/jjco/hyu096 [DOI] [PubMed] [Google Scholar]
  • 18.Watanabe S, Tsugane S, Sobue T, Konishi M, Baba S. Study design and organization of the JPHC study. Japan Public Health Center-based Prospective Study on Cancer and Cardiovascular Diseases. J Epidemiol. 2001;11(6 Suppl):S3–7. 10.2188/jea.11.6sup_3 [DOI] [PubMed] [Google Scholar]
  • 19.Organization WH. International statistical classification of diseases and related health problems. 2009.
  • 20.Sasaki S, Kobayashi M, Tsugane S, Jphc. Validity of a self-administered food frequency questionnaire used in the 5-year follow-up survey of the JPHC Study Cohort I: comparison with dietary records for food groups. J Epidemiol. 2003;13(1 Suppl):S57–63. 10.2188/jea.13.1sup_57 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Ishihara J, Sobue T, Yamamoto S, Yoshimi I, Sasaki S, Kobayashi M, et al. Validity and reproducibility of a self-administered food frequency questionnaire in the JPHC Study Cohort II: study design, participant profile and results in comparison with Cohort I. J Epidemiol. 2003;13(1 Suppl):S134–47. 10.2188/jea.13.1sup_134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Sasaki S, Ishihara J, Tsugane S, Jphc. Reproducibility of a self-administered food frequency questionnaire used in the 5-year follow-up survey of the JPHC Study Cohort I to assess food and nutrient intake. J Epidemiol. 2003;13(1 Suppl):S115–24. 10.2188/jea.13.1sup_115 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Takachi R, Tsubono Y, Baba K, Inoue M, Sasazuki S, Iwasaki M, et al. Red meat intake may increase the risk of colon cancer in Japanese, a population with relatively low red meat consumption. Asia Pac J Clin Nutr. 2011;20(4):603–12. [PubMed] [Google Scholar]
  • 24.Inoue M, Iso H, Yamamoto S, Kurahashi N, Iwasaki M, Sasazuki S, et al. Daily total physical activity level and premature death in men and women: results from a large-scale population-based cohort study in Japan (JPHC study). Ann Epidemiol. 2008;18(7):522–30. 10.1016/j.annepidem.2008.03.008 [DOI] [PubMed] [Google Scholar]
  • 25.Daniel CR, Cross AJ, Koebnick C, Sinha R. Trends in meat consumption in the USA. Public Health Nutr. 2011;14(4):575–83. 10.1017/S1368980010002077 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Ministry of Health, Labour and Welfare of Japan. National Health and Nutrition Survey. Ministry of Health, Labour and Welfare of Japan; 2005. [Google Scholar]
  • 27.Iso H. Lifestyle and cardiovascular disease in Japan. Journal of atherosclerosis and thrombosis. 2011;18(2):83–8. 10.5551/jat.6866 [DOI] [PubMed] [Google Scholar]
  • 28.Umesawa M, Sato S, Imano H, Kitamura A, Shimamoto T, Yamagishi K, et al. Relations between protein intake and blood pressure in Japanese men and women: the Circulatory Risk in Communities Study (CIRCS). Am J Clin Nutr. 2009;90(2):377–84. 10.3945/ajcn.2008.27109 [DOI] [PubMed] [Google Scholar]
  • 29.Iso H, Stampfer MJ, Manson JE, Rexrode K, Hu F, Hennekens CH, et al. Prospective study of fat and protein intake and risk of intraparenchymal hemorrhage in women. Circulation. 2001;103(6):856–63. 10.1161/01.cir.103.6.856 [DOI] [PubMed] [Google Scholar]
  • 30.Yamagishi K, Iso H, Kokubo Y, Saito I, Yatsuya H, Ishihara J, et al. Dietary intake of saturated fatty acids and incident stroke and coronary heart disease in Japanese communities: the JPHC Study. European heart journal. 2013;34(16):1225–32. 10.1093/eurheartj/eht043 [DOI] [PubMed] [Google Scholar]
  • 31.Kelemen LE, Kushi LH, Jacobs DR Jr., Cerhan JR. Associations of dietary protein with disease and mortality in a prospective study of postmenopausal women. Am J Epidemiol. 2005;161(3):239–49. 10.1093/aje/kwi038 [DOI] [PubMed] [Google Scholar]
  • 32.World Cancer Research Fund. Food, nutrition, physical activity, and the prevention of cancer: a global perspective: Amer Inst for Cancer Research; 2007. [Google Scholar]
  • 33.IARC Working Group on the Evaluation of Carcinogenic Risk to Humans. IARC Monographs on the Evaluation of Carcinogenic Risks to Humans Red Meat and Processed Meat. Lyon (FR): International Agency for Research on Cancer; 2018. [PubMed] [Google Scholar]
  • 34.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. 10.1093/carcin/22.1.199 [DOI] [PubMed] [Google Scholar]
  • 35.Hebels DG, Jennen DG, Kleinjans JC, de Kok TM. Molecular signatures of N-nitroso compounds in Caco-2 cells: implications for colon carcinogenesis. Toxicol Sci. 2009;108(2):290–300. 10.1093/toxsci/kfp035 [DOI] [PubMed] [Google Scholar]
  • 36.Mirvish SS. N-nitroso compounds: their chemical and in vivo formation and possible importance as environmental carcinogens. Journal of toxicology and environmental health. 1977;2(6):1267–77. 10.1080/15287397709529529 [DOI] [PubMed] [Google Scholar]
  • 37.McCord JM. Iron, free radicals, and oxidative injury. Seminars in hematology. 1998;35(1):5–12. [PubMed] [Google Scholar]
  • 38.Huang X. Iron overload and its association with cancer risk in humans: evidence for iron as a carcinogenic metal. Mutation research. 2003;533(1–2):153–71. 10.1016/j.mrfmmm.2003.08.023 [DOI] [PubMed] [Google Scholar]
  • 39.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):861–7. 10.1093/carcin/16.4.861 [DOI] [PubMed] [Google Scholar]
  • 40.Sinha R, Rothman N, Salmon CP, Knize MG, Brown ED, Swanson CA, et al. Heterocyclic amine content in beef cooked by different methods to varying degrees of doneness and gravy made from meat drippings. Food and chemical toxicology: an international journal published for the British Industrial Biological Research Association. 1998;36(4):279–87. 10.1016/s0278-6915(97)00162-2 [DOI] [PubMed] [Google Scholar]
  • 41.Sinha R, Knize MG, Salmon CP, Brown ED, Rhodes D, Felton JS, et al. Heterocyclic amine content of pork products cooked by different methods and to varying degrees of doneness. Food and chemical toxicology: an international journal published for the British Industrial Biological Research Association. 1998;36(4):289–97. 10.1016/s0278-6915(97)00159-2 [DOI] [PubMed] [Google Scholar]
  • 42.Cross AJ, Sinha R. Meat-related mutagens/carcinogens in the etiology of colorectal cancer. Environmental and molecular mutagenesis. 2004;44(1):44–55. 10.1002/em.20030 [DOI] [PubMed] [Google Scholar]
  • 43.Center for Cancer Control and Information Services. Monitoring of Cancer Incidence in Japan—Survival 2006–2008 Report. National Cancer Center; 2016.
  • 44.Matsuda T, Ajiki W, Marugame T, Ioka A, Tsukuma H, Sobue T. Population-based survival of cancer patients diagnosed between 1993 and 1999 in Japan: a chronological and international comparative study. Jpn J Clin Oncol. 2011;41(1):40–51. 10.1093/jjco/hyq167 [DOI] [PubMed] [Google Scholar]
  • 45.Fung TT, Stampfer MJ, Manson JE, Rexrode KM, Willett WC, Hu FB. Prospective study of major dietary patterns and stroke risk in women. Stroke. 2004;35(9):2014–9. 10.1161/01.STR.0000135762.89154.92 [DOI] [PubMed] [Google Scholar]
  • 46.Nanri A, Shimazu T, Ishihara J, Takachi R, Mizoue T, Inoue M, et al. Reproducibility and validity of dietary patterns assessed by a food frequency questionnaire used in the 5-year follow-up survey of the Japan Public Health Center-Based Prospective Study. J Epidemiol. 2012;22(3):205–15. 10.2188/jea.je20110087 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Daniel CR, Cross AJ, Graubard BI, Hollenbeck AR, Park Y, Sinha R. Prospective investigation of poultry and fish intake in relation to cancer risk. Cancer prevention research. 2011;4(11):1903–11. 10.1158/1940-6207.CAPR-11-0241 [DOI] [PMC free article] [PubMed] [Google Scholar]

Decision Letter 0

Marly A Cardoso

25 Sep 2020

PONE-D-20-16630

Association between meat intake and mortality due to all-cause and major causes of death in a Japanese population

PLOS ONE

Dear Dr. Inoue,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process.

Please submit your revised manuscript by Nov 09 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

  • A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.

  • A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.

  • An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

We look forward to receiving your revised manuscript.

Kind regards,

Marly A. Cardoso, Ph.D.

Academic Editor

PLOS ONE

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2.We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

3.One of the noted authors is a group or consortium [JPHC Study Group]. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address.

Additional Editor Comments (if provided):

The study is well-organized with interesting results. However, the manuscript needs revision following all reviewer´s suggestions. Particular attention should be given to the comparison on absolute meat intakes in Western and Asian populations, providing mean or median meat intake ranges in this study and also across populations.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

**********

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

**********

3. Have the authors made all data underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: No

**********

4. Is the manuscript presented in an intelligible fashion and written in standard English?

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: Yes

**********

5. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: The authors have presented findings from a large cohort followed for a reasonable length of time when considering associations between dietary intake and mortality. This study is of interest to the scientific community in light of the landmark publication from the EAT Lancet commission and "The Reference Diet" suggesting a lower meat intake for many Western populations for both health benefits and a sustainable food supply for the future whilst at the same time noting that some populations will need a higher intake of meat.

In the introduction the authors comment on the novelty of this finding as meat intake is studied in a predominantly Asian population with a markedly lower meat intake than a Western population such as the United States. Given the difference in intake in these populations I would have liked to see the authors make a greater note of comparison on meat intake in Western and Asian populations for their significant findings and also when comparing to other studies. Whilst this was noted for one finding, for the remainder it was lacking.

The first paragraph of the discussion section presents overal findings for an association with higher meat intake and increased risk for men AND women. The percentage figures presented in the discussion were not presented in the results or available on any of the submitted tables. The authors also indicate that there was an overall increased risk for women as well as men and this finding was not commented on in the results or evident from the data.

Other edits and comments outlined below:

Abstract

Pg 3, Line 49: re-word for improved clarity – suggest adding “higher intake”

Methods

Pg 7, Line 1: add reference for the validation study of the FFQ

Pg 7, line 4, correct spelling x 2 should read “fried” not “fired”

Pg 7, line 14/15 add in a descriptor of “fair-moderate” to describe the validity and reproducibility of the meat intake from the FFQ compared to the food record

Pg 8, line 14 provide a definition, description or reference for metabolic equivalent task-hours

Pg 10, line 4 remove the word “both”

Discussion

General comments: authors should comment on findings in comparison to non-Asian populations and with reference to absolute meat intakes. When comparing to other studies a comment on mean or median meat intake would be helpful as you have discussed a marked difference in Asian and Western populations with regards to meat intake in introduction

Pg 12, line 5 & 6: 17% and 15% does not correspond with any data presented in tables – is this another analysis that was not reported?? If yes include in results. From Table 1 Men had 18% increased risk of dying from all-causes and in women this was not significant.

Pg 12, line 14 – relate this comment on explaining differences in age groups to average intake in Western diet – 5g/day does not seem “considerably” higher in comparison to difference with Western intake. Also of note is that the highest quartiles was not significantly different from lowest quartile – only the middle quartiles. Perhaps chance finding? Comment on number of statistical tests conducted and chance findings

Pg 12, line 20 – Elevated risk in men was only significant in older age group not younger as seems to be indicated from this paragraph

Pg 13, line 2, 3 it is important to add in here that these studies you are referring to are also in Japanese Populations

Pg 13, line 8,9 add in that this finding was in men only not women

Pg 13, line 18 please use the most up to date references from the WCRF report on red meat and cancer instead of reference 30. The Third Expert Report on Diet, Nutrition, Physical Activity and Cancer was published in 2018

Pg 14, line 8,9 again the authors need to consider the difference in absolute intake of meat in their study population and Western populations as this may be a reason that no association was found.

Page 14, line 21, 22 – have the authors considered chance findings for other statistically significant results?

**********

6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Siobhan Hickling

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

PLoS One. 2020 Dec 15;15(12):e0244007. doi: 10.1371/journal.pone.0244007.r002

Author response to Decision Letter 0

8 Nov 2020

RESPONSE TO REVIEWS

Editor Comments:

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: We thank the editor for these comments. We have revised the styles and file naming according to the instructions provided online.

2. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

Response: We thank the editor for these detailed instructions. Accordingly, we have added a data availability statement in the attached cover letter.

3. One of the noted authors is a group or consortium [JPHC Study Group]. In addition to naming the author group, please list the individual authors and affiliations within this group in the acknowledgments section of your manuscript. Please also indicate clearly a lead author for this group along with a contact email address.

Response: We thank the editor for these instructions. We have listed the individual authors and their affiliations within this group in the revised Acknowledgements section, along with information on the principal investigator.

4. Additional Editor Comments (if provided):

The study is well-organized with interesting results. However, the manuscript needs revision following all reviewer´s suggestions. Particular attention should be given to the comparison on absolute meat intakes in Western and Asian populations, providing mean or median meat intake ranges in this study and also across populations.

Response: We thank the editor for these comments. We have provided mean meat intake ranges in this study and comparison against Western populations throughout the revised manuscript. Specific revisions are described in the point-by-point answers below.

Reviewer #1 comments:

1. In the introduction the authors comment on the novelty of this finding as meat intake is studied in a predominantly Asian population with a markedly lower meat intake than a Western population such as the United States. Given the difference in intake in these populations I would have liked to see the authors make a greater note of comparison on meat intake in Western and Asian populations for their significant findings and also when comparing to other studies. Whilst this was noted for one finding, for the remainder it was lacking.

Response: We thank the editor for these comments. We have provided median meat intake ranges in this study and comparison against the Western populations as below:

“The difference may also be due to the fact that the absolute amount of intake of meat differs between the Japanese and Western populations: mean daily intake of total meat in the US population amounted to 127.9 grams per day between 2003 and 2004 (25) versus 77 grams per day in Japan as of 2003 (26). Mean intake amount in the US is almost twice that in Japan. In our study population, the crude mean intake (adjusted for the difference between the FFQ and dietary records) of total meat was 71.9 grams per day.”(Line 279-285, page 20)

Also, we have added a discussion on processed meat intake as below:

“For example, average consumption in the US was estimated to be 23.2 grams per day between 2003 and 2004 versus 12 grams per day in Japan as of 2003. In our study population, the crude mean intake (adjusted for the difference between the FFQ and dietary records) of processed meat was 7.7 grams per day.” (Line 336-340, page 23)

2. The first paragraph of the discussion section presents overall findings for an association with higher meat intake and increased risk for men AND women. The percentage figures presented in the discussion were not presented in the results or available on any of the submitted tables. The authors also indicate that there was an overall increased risk for women as well as men and this finding was not commented on in the results or evident from the data.　

Response: We thank the reviewer for pointing out this discrepancy, which occurred during the course of re-analyses. We have corrected the corresponding sentence, and the revised manuscript now reads as below:

“Compared with subjects in the lowest quartile of total meat intake, men in the highest quartile had 18% higher risk of dying from all causes, although the associations were not dose-responsive.” (Line 272-274, page 20)

3. Abstract Pg 3, Line 49: re-word for improved clarity – suggest adding “higher intake”

Response: We have added “higher intake” in the revised manuscript. (line 34, page 2)

4. Methods Pg 7, Line 1: add reference for the validation study of the FFQ

Response: Accordingly, we have added the references for the validation studies of the FFQ. (Line 120, page 6)

5. Pg 7, line 4, correct spelling should read “fried” not “fired”

Response: Accordingly, we have corrected this spelling error.

6. Pg 7, line 14/15 add in a descriptor of “fair-moderate” to describe the validity and reproducibility of the meat intake from the FFQ compared to the food record.

Response: We have added “The validity of the FFQ for the assessment of meat intake has been previously reported as fair to moderate” in the revised manuscript. (Line 131-132, page 6)

7. Pg 8, line 14 provide a definition, description or reference for metabolic equivalent task-hours

Response: We have added a reference for metabolic equivalent task-hours in the revised manuscript. (Line 154, page 7)

8. Pg 10, line 4 remove the word “both”

Response: We have removed the word “both” in the revised manuscript.

9. Discussion, General comments: authors should comment on findings in comparison to non-Asian populations and with reference to absolute meat intakes. When comparing to other studies a comment on mean or median meat intake would be helpful as you have discussed a marked difference in Asian and Western populations with regards to meat intake in introduction

Response: We thank the reviewer for the comment. We have provided mean meat intake ranges in this study and comparison against the Western populations as shown in our response to reviewer comment #1.

10. Pg 12, line 5 & 6: 17% and 15% does not correspond with any data presented in tables – is this another analysis that was not reported?? If yes include in results.

Response: Again, we thank the reviewer for pointing out this discrepancy, which occurred during the course of re-analyses. We have corrected the corresponding sentence, and the revised manuscript now reads as below:

“Compared with subjects in the lowest quartile of total meat intake, men in the highest quartile had 18% higher risk of dying from all causes, although the associations were not dose-responsive.” (Line 272-274, page 20)

11. From Table 1 Men had 18% increased risk of dying from all-causes and in women this was not significant.

Response: We thank the reviewer for pointing out this discrepancy, which occurred during the course of re-analyses. We have corrected the corresponding description as indicated in our response to comment #10 (above).

12. Pg 12, line 14 – relate this comment on explaining differences in age groups to average intake in Western diet – 5g/day does not seem “considerably” higher in comparison to difference with Western intake. Also of note is that the highest quartiles was not significantly different from lowest quartile – only the middle quartiles. Perhaps chance finding? Comment on number of statistical tests conducted and chance findings.

Response: We thank the reviewer for this valuable input. We agree that the results for women could be due to a chance finding, since the highest intake quartile did not show any significant association, as the reviewer indicated. The revised manuscript thus reads as below:

“We also noted generational differences in the association patterns between meat intake and all-cause mortality: notably, women aged 45-54 years had significantly higher risk of total mortality. However, these results could be a chance finding resulting from the multiple statistical tests conducted, given that the highest intake quartile showed no significant associations. (Line 287-291, page 20-21)

13. Pg 12, line 20 – Elevated risk in men was only significant in older age group not younger as seems to be indicated from this paragraph

Response: Yes, we have revised the corresponding sentence to improve the clarity of the manuscript as below:

“In men, in contrast, elevated risk of mortality in the highest intake quartile was seen only in the older groups, and not in the younger age group.” (Line 291-292, page 21)

14. Pg 13, line 2, 3 it is important to add in here that these studies you are referring to are also in Japanese Populations

Response: We thank the reviewer for this valuable comment. We have added corresponding text in the revised manuscript:

“For instance, previous population-based studies – both derived from Japanese populations – showed that dietary animal protein intake was associated with lower blood pressure levels and also a reduced risk of intraparenchymal hemorrhage.” (Line 297-300, page 21)

15. Pg 13, line 8,9 add in that this finding was in men only not women

Response: Accordingly, we have revised this text as below:

“On the contrary, our study reported an elevated risk of heart disease mortality in men but not in women if red meat is taken to the level of the highest intake quartile.” (Line 304-305, page 21)

16. Pg 13, line 18 please use the most up to date references from the WCRF report on red meat and cancer instead of reference The Third Expert Report on Diet, Nutrition, Physical Activity and Cancer was published in 2018.

Response: The Third Expert Report on Diet, Nutrition, Physical Activity and Cancer published in 2018 is the most recent report published to date by the WCRF Continuous Update Project (https://www.wcrf.org/int/continuous-update-project). Given the comprehensiveness of the report covering all major cancer sites and risk factors, and because of the robustness of the methodology, we thought that the 2018 report is appropriate to reference in our manuscript.

17. Pg 14, line 8,9 again the authors need to consider the difference in absolute intake of meat in their study population and Western populations as this may be a reason that no association was found.

Response: Following reviewer’s recommendation, we have added a description of the mean intake of processed meat in the revised manuscript as below:

“In our study population, the crude mean intake (adjusted for the difference between the FFQ and dietary records) of processed meat was 7.7 grams per day.” (Line 338-340, page 23)

18. Page 14, line 21, 22 – have the authors considered chance findings for other statistically significant results?

Response: We have carefully checked the possibility of chance findings for all meat types and outcomes, and cross-checked the results with p-values for trends, along with our sensitivity analyses which excluded deaths within 5 years. As for chance finding in the age-group analyses, we have added the possibility of a chance finding as suggested by the reviewer’s comment #12.

Attachment

Submitted filename: Response to Reviews.docx

Click here for additional data file. (24.8KB, docx)

Decision Letter 1

Marly A Cardoso

2 Dec 2020

Association between meat intake and mortality due to all-cause and major causes of death in a Japanese population

PONE-D-20-16630R1

Dear Dr. Inoue,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Marly A. Cardoso, Ph.D.

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Acceptance letter

Marly A Cardoso

4 Dec 2020

PONE-D-20-16630R1

Association between meat intake and mortality due to all-cause and major causes of death in a Japanese population.

Dear Dr. Inoue:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Marly A. Cardoso

Academic Editor

PLOS ONE

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Participant flow chart.

    (TIF)

    Click here for additional data file. (181.6KB, tif)
    S1 Table. Adjusted hazard ratios of mortality by meat consumption status after excluding deaths within 5 years (men).

    (DOCX)

    Click here for additional data file. (34.2KB, docx)
    S2 Table. Adjusted hazard ratios of mortality by meat consumption status after excluding deaths within 5 years (women).

    (DOCX)

    Click here for additional data file. (34.4KB, docx)
    S3 Table. Adjusted hazard ratios of mortality from ischemic heart disease and intracerebral hemorrhage by meat consumption status.

    (DOCX)

    Click here for additional data file. (32.1KB, docx)
    Attachment

    Submitted filename: Response to Reviews.docx

    Click here for additional data file. (24.8KB, docx)

    Data Availability Statement

    Regarding data accessibility, we cannot publicly share the individual data even after anonymization according to the ethical guidelines in Japan if: a) consent to public sharing of data has not been obtained from each participant, and b) there is a possibility of identifying an individual by combining the information or due to the existence of rare diseases, etc. Therefore, the investigators require the approval of the JPHC Steering Committee (SC) and the Institutional Review Board (IRB). Currently, only citizens of Japan who fulfill the requirements of conducting research projects are eligible to apply for the JPHC data and/or biospecimens. The investigator is required to submit a Project Protocol (Research question, Aim, Background, Design and analytical plan) for review by the JPHC SC. Requests can be made by contacting the JPHC SC directly (jphcadmin@ml.res.ncc.go.jp) or investigators in the JPHC. After approval is obtained from the JPHC SC, the investigator is required to obtain additional approval for the protocol under which the data and/or biospecimens are to be used from the Institutional Review Board of the National Cancer Center. This information on how to submit an application to gain access to JPHC data/or biospecimens is publicly available at http://epi.ncc.go.jp/en/jphc/805/8155.html.

    Articles from PLoS ONE are provided here courtesy of PLOS

    RESOURCES